This directory is created automatically and some papers may be mislabeled. Only document within the CiteSeer database are listed. The directory is intended to provide entry points for browsing the database and is not intended to be authoritative. Papers may not appear in all relevant categories. For example, papers in a sub-category may not appear in higher level categories.
426 Bagging Predictors - Breiman (1996)(Correct)
Bagging predictors is a method for generating multiple versions of a predictor and using these to get an aggregated predictor. The aggregation averages over the versions when predicting a numerical ou... / classification trees Artificial Intelligence Frontiers in Statistics br ftp ics.uci.edu pub machine-learning-databases The data are
291 Experiments with a New Boosting Algorithm - Freund, Schapire (1996)(Correct)
In an earlier paper, we introduced a new "boosting"
algorithm called AdaBoost which, theoretically, can be used to
significantly reduce the error of any learning algorithm that consistently
generate... / of Pattern Recognition and Artificial Intelligence - . br Machine Learning Proceedings of the
273 Fast Planning Through Planning Graph Analysis - Blum, Furst (1995)(Correct)
We introduce a new approach to planning in STRIPS-like domains based on constructing
and analyzing a compact structure we call a Planning Graph. We describe a new planner,
Graphplan, that uses this p... / efficiency gains. Artificial Intelligence - .
249 Hard and Easy Distributions of SAT Problems - Mitchell, Selman, Levesque (1992)(Correct)
We report results from large-scale experiments in satisfiability
testing. As has been observed by others, testing
the satisfiability of random formulas often appears surprisingly
easy. Here we show th... / National Conference on Artificial Intelligence AAAI- San Jose CA
236 Reinforcement Learning: A Survey - Leslie Pack Kaelbling, Michael L.. (1996)(Correct)
This paper surveys the field of reinforcement learning from a computer-science perspective.
It is written to be accessible to researchers familiar with machine learning. Both
the historical basis of t... / Journal of Artificial Intelligence Research - br to researchers familiar with machine learning. Both the historical basis
210 Irrelevant Features and the Subset Selection Problem - John, Kohavi, Pfleger (1994)(Correct)
We address the problem of finding a subset of features that allows a supervised induction algorithm to induce small high-accuracy concepts. We examine notions of relevance and irrelevance, and show th... / National Conference on Artificial Intelligence - . MIT Press. br W. Cohen Haym Hirsh eds.Machine Learning Proceedings of the Eleventh
183 The Oz Programming Model - Smolka (1995)(Correct)
The Oz Programming Model (OPM) is a concurrent programming model subsuming higher- order functional and object-oriented programming as facets of a general model. This is particularly interesting for c... / German Research Center for Artificial Intelligence DFKI
171 Minimizing Conflicts: A Heuristic Repair Method for.. - Minton, Johnston, Philips, Laird (1992)(Correct)
This paper describes a simple heuristic approach to solving large-scale constraint satisfaction and
scheduling problems. In this approach one starts with an inconsistent assignment for a set of variab... / satisfaction problems. Artificial Intelligence - . br reuse. In Minton S.editor Machine Learning Methods for Planning and
167 Letizia: An Agent That Assists Web Browsing - Lieberman (1995)(Correct)
Letizia is a user interface agent that assists a
user browsing the World Wide Web. As the
user operates a conventional Web browser such
as Netscape, the agent tracks user behavior and
attempts to anti... / general topics such as Artificial Intelligence. Our user is particularly
158 Intelligent Agents: Theory and Practice - Wooldridge, Jennings (1995)(Correct)
The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most impor... / become important in both Artificial Intelligence AI and mainstream br in distributed artificial intelligence. Artificial Intelligence Review
143 An Introduction to Least Commitment Planning - Weld (1994)(Correct)
Recent developments have clarified the process of generating partially
ordered, partially specified sequences of actions whose execution
will achive an agent's goal. This paper summarizes a progressio... / agents has forced Artificial Intelligence researchers to br architecture for general intelligence. Artificial Intelligence
140 The INQUERY Retrieval System - Callan, Croft, Harding(Correct)
As larger and more heterogeneous text
databases become available, information
retrieval research will depend on
the development of powerful, efficient
and flexible retrieval engines. In this paper,
we... / Sixth IEEE Conference on Artificial Intelligence Applications .
135 The Complexity of Concept Languages - Donini, Lenzerini, Nardi, Nutt (1995)(Correct)
The basic feature of Terminological Knowledge Representation Systems is to represent
knowledge by means of taxonomies, here called terminologies, and to provide
a specialized reasoning engine to do in... / German Research Center for Artificial Intelligence Deutsches
120 WebWatcher: A Tour Guide for the World Wide Web - Joachims, Freitag, Mitchell (1997)(Correct)
We explore the notion of a tour guide software agent for assisting users browsing the World Wide Web. A Web tour guide agent provides assistance similar to that provided by a human tour guide in a mus... / Joint Conference on Artificial Intelligence Montreal August . br can learn that a term such as machine learning matches a hyperlink such as
118 An Algorithm for Probabilistic Planning - Kushmerick, Hanks, Weld (1995)(Correct)
We define the probabilistic planning problem in terms of a probability distribution
over initial world states, a boolean combination of propositions representing the goal,
a probability threshold, and... / To appear in Artificial Intelligence Abstract We define
113 Extracting Semistructured Information from the Web - Hammer, Garcia-Molina, Cho, Aranha.. (1997)(Correct)
We describe a configurable tool for extracting semistructured data from a set of HTML pages and for converting the extracted information into database objects. The input to the extractor is a declarat... / data it does not use artificial intelligence to understand the br al. attempt to insert machine learning techniques into their
106 The Ontolingua Server: a Tool for Collaborative Ontology Construction - Farquhar, Fikes, Rice (1996)(Correct)
Reusable ontologies are becoming increasingly important for tasks such as information integration, knowledge-level interoperation, and knowledgebase development. We have developed a set of tools and s... / Joint Conference on Artificial Intelligence. Montreal Canada. br agents such as medical expert systems can query an Ontolingua Server
103 Acting Optimally in Partially Observable Stochastic Domains - Cassandra, Kaelbling, Littman (1994)(Correct)
In this paper, we describe the partially observable
Markov decision process (pomdp) approach to finding
optimal or near-optimal control strategies for partially
observable stochastic environments, giv... / has been addressed in the artificial intelligence AI community using br International Conference on Machine Learning. Amherst Massachusetts
103 Wrappers for Feature Subset Selection - Kohavi, John (1997)(Correct)
In the feature subset selection problem, a learning algorithm is faced with the problem of selecting a relevant subset of features upon which to focus its attention, while ignoring the rest. To achiev... / International Workshop on Artificial Intelligence and Statistics Ft. br problem. In supervised machine learning an induction algorithm is
99 On The Acceptability Of Arguments And Its Fundamental Role In.. - Dung (1995)(Correct)
The purpose of this paper is to study the fundamental mechanism, humans use in argumentation, and to explore ways to implement this mechanism on computers. We do so by first developing a theory for ar... / Annals of Mathematics and Artificial Intelligence -
93 Efficient Algorithms for Discovering Association Rules - Mannila, Toivonen, Verkamo (1994)(Correct)
Association rules are statements of the form "for 90 % of the rows of the relation, if the row has value 1 in the columns in set W , then it has 1 also in column B". Agrawal, Imielinski, and Swami int... / intersection of databases artificial intelligence and machine learning br artificial intelligence and machine learning see e.g. The area
92 Operations for Learning with Graphical Models - Buntine (1994)(Correct)
This paper is a multidisciplinary review of empirical, statistical learning from a graphical
model perspective. Well-known examples of graphical models include Bayesian networks,
directed graphs repre... / Journal of Artificial Intelligence Research - br While there are no common machine learning algorithms explained in this
91 Greedy Attribute Selection - Caruana, Freitag (1994)(Correct)
Many real-world domains bless us with a wealth
of attributes to use for learning. This blessing is
often a curse: most inductive methods generalize
worse given too many attributes than if given a
goo... / th National Conference on Artificial Intelligence . L. Breiman br tasks. INTRODUCTION As machine learning is applied to real-world
88 Reinforcement Learning with Perceptual Aliasing: The Perceptual.. - Chrisman (1992)(Correct)
It is known that Perceptual Aliasing may significantly
diminish the effectiveness of reinforcement
learning algorithms [ Whitehead and Ballard,
1991 ] . Perceptual aliasing occurs when multiple
situat... / Approach to Artificial Intelligence. MIT Press. Jordan br Proc. Eighth International Machine Learning Workshop. Monahan George
88 A System for Induction of Oblique Decision Trees - Murthy, Kasif, Salzberg (1994)(Correct)
This article describes a new system for induction of oblique decision trees. This system,
OC1, combines deterministic hill-climbing with two forms of randomization to find a good
oblique split (in the... / Journal of Artificial Intelligence Research - br and opportunity for automated machine learning techniques. The advent of
87 The Parti-game Algorithm for Variable Resolution Reinforcement.. - Moore, Atkeson (1995)(Correct)
Parti-game is a new algorithm for learning feasible trajectories to goal regions in
high dimensional continuous state-spaces. In high dimensions it is essential that learning does not
plan uniformly... / problem in other areas of artificial intelligence such as planning and br Machine Learning - To appear c fl
86 Factorial Hidden Markov Models - Zoubin Ghahramani, Michael I. Jordan (1997)(Correct)
Hidden Markov models (HMMs) have proven to be one of the most widely used tools
for learning probabilistic models of time series data. In an HMM, information about the past
is conveyed through a sin... / Eds.Uncertainty in Artificial Intelligence Proceedings of the br Machine Learning - c fl
81 Knowledge Compilation Using Horn Approximations - Selman, Kautz (1991)(Correct)
We present a new approach to developing fast and efficient knowledge representation
systems. Previous approaches to the problem of tractable inference
have used restricted languages or incomplete infe... / National Conference on Artificial Intelligence AAAI- Anaheim CA
81 Towards Flexible Teamwork - Tambe (1997)(Correct)
Many AI researchers are today striving to build agent teams for complex, dynamic
multi-agent domains, with intended applications in arenas such as education, training,
entertainment, information integ... / Journal of Artificial Intelligence Research - br as a basis for general intelligence. Artificial Intelligence
80 Data Mining: An Overview from a Database Perspective - Chen, Han, Yu (1996)(Correct)
Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an i... / knowledge-base systems artificial intelligence machine learning br topic in database systems and machine learning and by many industrial
78 SLIQ: A Fast Scalable Classifier for Data Mining - Mehta, Agrawal, Rissanen (1996)(Correct)
Classification is an important problem in the emerging field
of data mining. Although classification has been studied extensively in
the past, most of the classification algorithms are designed only... / largest dataset in the Irvine Machine Learning repositary is only KB br Nets Machine Learning and Expert Systems. Morgan Kaufman .
77 Mining Association Rules with Item Constraints - Srikant, Vu, Agrawal(Correct)
The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice, users are often int... / American Association for Artificial Intelligence www.aaai.org All
77 The Schema Theorem and Price's Theorem - Altenberg (1995)(Correct)
Holland's Schema Theorem is widely taken to be the foundation for explanations of the power of genetic algorithms (GAs). Yet some dissent has been expressed as to its implications. Here, dissenting ar... / in genetic algorithms. Artificial Intelligence - . Vose br in Search Optimization and Machine Learning. Addison Wesley.
75 Higher-Order Logic Programming - Nadathur, Miller (1986)(Correct)
ly,
if a tactic R holds of G1 and G2, i.e., if (R G1 G2) is solvable from a presentation of primitive
tactics as a set of definite clauses, then satisfying the goal G2 in the object-language should su... / the Handbook of Logic in Artificial Intelligence and Logic Programming
75 Learning in the Presence of Malicious Errors - Kearns (1993)(Correct)
In this paper we study an extension of the distribution-free model of learning introduced by Valiant [23] (also known as the probably approximately correct or PAC model) that allows the presence of ma... / Joint Conference on Artificial Intelligence pp. - . br motivation for the model of machine learning we study. This model was
75 SIFT - A Tool for Wide-Area Information Dissemination - Yan (1995)(Correct)
The dissemination model is becoming increasingly
important in wide-area information system. In this
model, the user subscribes to an information dissemination
service by submitting profiles that descr... / retrieval IR and artificial intelligence approaches. With few
71 An Equivalence Between Sparse Approximation and Support Vector.. - Girosi (1997)(Correct)
This paper shows a relationship between two different approximation techniques: the
Support Vector Machines (SVM), proposed by V. Vapnik (1995), and a sparse approximation
scheme that resembles the Ba... / Institute Of Technology Artificial Intelligence Laboratory And br Support vector networks. Machine Learning - . I.
69 Mean Field Theory for Sigmoid Belief Networks - Saul, Jaakkola, Jordan (1996)(Correct)
We develop a mean field theory for sigmoid belief networks based on ideas from statistical mechanics. Our mean field theory provides a tractable approximation to the true probability distribution in t... / Journal of Artificial Intelligence Research - br in very large probabilistic expert systems. International Journal of
69 A Comparison of Two Learning Algorithms for Text Categorization - Lewis, Ringuette (1994)(Correct)
This paper examines the use of inductive learning to categorize natural language documents into predefined content categories. Categorization of text is of increasing importance in information retriev... / Heuristic classification. Artificial Intelligence - . br text categorization has mixed machine learning and knowledge engineering
68 An Experimental Comparison of Three Methods for Constructing.. - Dietterich (1998)(Correct)
Bagging and boosting are methods that generate a diverse ensemble of classifiers
by manipulating the training data given to a "base" learning algorithm. Breiman has pointed
out that they rely for th... / National Conference on Artificial Intelligence pp. - br Machine Learning - c fl
68 Theory of Generalized Annotated Logic Programming and its Applications - Kifer, Subrahmanian (1992)(Correct)
Annotated logics were introduced in [43] and later studied in [5, 7, 31, 32]. In [31],
annotations were extended to allow variables and functions, and it was argued that such logics
can be used to pro... / Approach to Reasoning in Artificial Intelligence Computational br formal semantics for rule-based expert systems with uncertainty. In this
66 Error-Correcting Output Coding Corrects Bias and Variance - Kong, Dietterich (1995)(Correct)
Previous research has shown that a technique
called error-correcting output coding
(ECOC) can dramatically improve the
classification accuracy of supervised learning
algorithms that learn to classify ... / English text to speech A machine learning approach. Tech. rep. br Nilsson N. J. Learning Machines. McGrawHill New York.
65 Cooperative Mobile Robotics: Antecedents and Directions - Cao, Fukunaga, Kahng (1997)(Correct)
There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying ... / distributed robotics artificial intelligence mobile robots br in search optimization and machine learning. Addison Wesley . .
65 The Structure-Mapping Engine: Algorithm and Examples - Falkenhainer, Forbus, Gentner (1989)(Correct)
This paper describes the Structure-Mapping Engine (SME), a program for studying analogical processing. SME has been built to explore Gentner's Structure-mapping theory of analogy, and provides a "tool... / This paper appeared in Artificial Intelligence pp - . br it a useful component in machine learning systems as well. We review
65 Dynamic Parameter Encoding for Genetic Algorithms - Schraudolph, Belew (1992)(Correct)
The common use of static binary place-value codes for real-valued parameters of the phenotype in Holland's genetic algorithm (GA) forces either the sacrifice of representational precision for efficien... / revised for publication in Machine Learning July Abstract
64 Toward Optimal Feature Selection - Koller, Sahami (1996)(Correct)
In this paper, we examine a method for feature subset selection based on Information Theory. Initially, a framework for defining the theoretically optimal, but computationally intractable, method for ... / feature subset selection in machine learning. As defined by John
62 Residual Algorithms: Reinforcement Learning with Function.. - Leemon Baird (1995)(Correct)
A number of reinforcement learning algorithms have
been developed that are guaranteed to converge to the
optimal solution when used with lookup tables. It is
shown, however, that these algorithms can ... / of temporal differences. Machine Learning - . Tesauro G. br in temporal difference learning. Machine Learning .
62 Transfer of Learning by Composing Solutions of Elemental Sequential.. - Singh (1992)(Correct)
Although building sophisticated learning agents that operate in complex environments will require learning to perform multiple tasks, most applications of reinforcement learning have focussed on singl... / weak method for learning. Artificial Intelligence - . Maes P. br by the agent. In the machine learning literature closed loop
61 Automatically Constructing a Dictionary for Information Extraction.. - Riloff (1993)(Correct)
Knowledge-based natural language processing systems have
achieved good success with certain tasks but they are often
criticized because they depend on a domain-specific
dictionary that requires a grea... / National Conference on Artificial Intelligence AAAI Press MIT br An Alternative View. Machine Learning - . Fisher D. H.
61 Bounds on the Sample Complexity of Bayesian Learning Using.. - Haussler (1994)(Correct)
In this paper we study a Bayesian or average-case model of concept learning with
a twofold goal: to provide more precise characterizations of learning curve (sample
complexity) behavior that depend on... / of neural networks artificial intelligence cognitive science and br from the frequent claims of machine learning practitioners that sample
61 An Evolutionary Algorithm that Constructs Recurrent Neural Networks - Angeline, Saunders, Pollack (1994)(Correct)
Standard methods for inducing both the structure and weight values of recurrent neural
networks fit an assumed class of architectures to every task. This simplification is necessary
because the intera... / Pollack Laboratory for Artificial Intelligence Research Computer and br in Search Optimization and Machine Learning. Addison Wesley Publishing
60 Rule Induction with CN2: Some Recent Improvements - Clark, Boswell (1991)(Correct)
The CN2 algorithm induces an ordered list of classification rules from examples using entropy as its search heuristic. In this short paper, we describe two improvements to this algorithm. Firstly, we ... / In Machine Learning -Proceedings of the Fifth br case study. In Applications of Expert Systems pages -
60 A Theoretical Evaluation of Selected Backtracking Algorithms - Kondrak (1994)(Correct)
In recent years, numerous new backtracking algorithms have been proposed. The algorithms are usually evaluated by empirical testing. This method, however, has its limitations. Our thesis adopts a diff... / Joint Conference on Artificial Intelligence pages - .
59 Knowledge-Based Artificial Neural Networks - Towell, Shavlik (1994)(Correct)
Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples
to develop a method for accurately classifying examples not seen during training. The challenge of
hybrid... / submitted to Artificial Intelligence. Accepted br Madison WI Keywords machine learning connectionism
59 Knowledge Discovery in Databases: An Attribute-Oriented Approach - Han, Cai, Cercone (1992)(Correct)
Knowledge discovery in databases, or data mining,
is an important issue in the development of data- and
knowledge-base systems. An attribute-oriented induction
method has been developed for knowledge ... / Machine Learning An Artificial Intelligence Approach Vol. Morgan br The method integrates a machine learning paradigm especially
59 Face Recognition Under Varying Pose - Beymer (1993)(Correct)
Researchers in computer vision and pattern recognition have worked on automatic techniques for recognizing
human faces for the last 20 years. While some systems, especially template-based ones, have b... / Institute Of Technology Artificial Intelligence Laboratory A.i. Memo No.
58 Spacetime Constraints Revisited - Ngo, Marks (1993)(Correct)
The Spacetime Constraints (SC) paradigm, whereby the animator
specifies what an animated figure should do but not how to do it, is
a very appealing approach to animation. However, the algorithms
avail... / CR Categories I. . Artificial Intelligence Learning- br International Conference on Machine Learning pages - Austin
56 On the Optimality of the Simple Bayesian Classifier under Zero-One.. - Domingos, Pazzani (1997)(Correct)
The simple Bayesian classifier is known to be optimal when attributes are independent
given the class, but the question of whether other sufficient conditions for its optimality exist has
so far not... / European Conference on Artificial Intelligence. Stockholm Sweden br a gradual recognition among machine learning researchers that the Bayesian
56 Multiagent Systems: A Survey from a Machine Learning Perspective - Stone, Veloso (1997)(Correct)
Distributed Artificial Intelligence (DAI) has existed as a subfield of AI for less than two decades. DAI is concerned with systems that consist of multiple independent entities that interact in a doma... / Abstract Distributed Artificial Intelligence DAI has existed as a br Systems A Survey from a Machine Learning Perspective Peter Stone
56 Computational Complexity of Terminological Reasoning in BACK - Nebel (1988)(Correct)
Terminological reasoning is a mode of reasoning all hybrid knowledge
representation systems based on KL-ONE rely on. After a short introduction
of what terminological reasoning amounts to, it is prove... / BACK Published in Artificial Intelligence -
56 Records for Logic Programming - Smolka, Treinen (1994)(Correct)
CFT is a new constraint system providing records as logical data
structure for constraint (logic) programming. It can be seen as a generalization
of the rational tree system employed in Prolog II, whe... / German Research Center for Artificial Intelligence DFKI
56 A Guide to the Literature on Learning Probabilistic Networks From Data - Buntine (1996)(Correct)
This literature review discusses different methods
under the general rubric of learning Bayesian networks
from data, and includes some overlapping work on more general
probabilistic networks. Connecti... / contingency tables in artificial intelligence to model probabilistic br independently until recently machine learning which originally focused on
56 Learning Decision Trees using the Fourier Spectrum - Kushilevitz, Mansour (1991)(Correct)
This work gives a polynomial time algorithm for learning decision trees with respect
to the uniform distribution. (This algorithm uses membership queries.) The decision tree
model that is considered i... / a theoretical basis for machine learning. These efforts involved
55 Reinforcement Learning with Replacing Eligibility Traces - Singh (1996)(Correct)
The eligibility trace is one of the basic mechanisms used in reinforcement learning to handle delayed reward. In this paper we introduce a new kind of eligibility trace, the replacing trace, analyze i... / of Machine Learning An Artificial Intelligence Approach chapter . br Machine Learning - c fl
55 HTN Planning: Complexity and Expressivity - Kutluhan Erol(Correct)
Most practical work on AI planning systems during the
last fifteen years has been based on hierarchical task
network (HTN) decomposition, but until now, there
has been very little analytical work on t... / for conjunctive goals. Artificial Intelligence - .
54 Active Learning with Statistical Models - Cohn, Ghahramani, Jordan (1996)(Correct)
For many types of machine learning algorithms, one can compute the statistically "optimal
" way to select training data. In this paper, we review how optimal data selection
techniques have been used w... / Journal of Artificial Intelligence Research - br Abstract For many types of machine learning algorithms one can compute
54 Empirical Support for Winnow and Weighted-Majority Algorithms.. - Blum (1995)(Correct)
This paper describes experimental results on using Winnow and Weighted-Majority based algorithms on a real-world calendar scheduling domain. These two algorithms have been highly studied in the theore... / National Conference on Artificial Intelligence. DeSantis A. br studied in the theoretical machine learning literature. We show here that
52 Tractable Inference for Complex Stochastic Processes - Boyen (1998)(Correct)
The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system, these tasks typicall... / on Uncertainty in Artificial Intelligence UAI- pages - br Olesen and J. Pedersen. An expert system for control of waste water
52 Deception Considered Harmful - Grefenstette (1992)(Correct)
A central problem in the theory of genetic algorithms is the characterization
of problems that are difficult for GAs to optimize. Many attempts to
characterize such problems focus on the notion of Dec... / for Applied Research in Artificial Intelligence Code Naval br in search optimization and machine learning. Reading Addison-Wesley.
51 Provably Bounded-Optimal Agents - Russell, Subramanian (1995)(Correct)
Since its inception, artificial intelligence has relied upon a theoretical foundation centred around perfect rationality as the desired property of intelligent systems. We argue, as others have done, ... / Journal of Artificial Intelligence Research -
49 Improving Generalization with Active Learning - Cohn, Atlas, al. (1992)(Correct)
Active learning differs from passive "learning from examples" in that the learning algorithm assumes
at least some control over what part of the input domain it receives information about. In some sit... / Generalization as search. Artificial Intelligence - . L. Y. br If As published in Machine Learning - . A
49 Distributed Intelligent Agents - Sycara, Decker, Pannu, Williamson.. (1996)(Correct)
We are investigating techniques for developing distributed and
adaptive collections of agents that coordinate to retrieve, filter and
fuse information relevant to the user, task and situation, as well... / National Conference on Artificial Intelligence. AAAI . Oren br examples and utilize various machine learning techniques to adapt to new
48 Has a Consensus NL Generation Architecture Appeared, and is it.. - Reiter (1994)(Correct)
I survey some recent applications-oriented
NL generation systems, and claim that despite
very different theoretical backgrounds,
these systems have a remarkably similar architecture
in terms of the mo... / of Edinburgh Department of Artificial Intelligence. The Edinburgh work was
48 Locating the Phase Transition in Binary Constraint Satisfaction.. - Smith (1994)(Correct)
The phase transition in binary constraint satisfaction problems, i.e. the transition from a region in which almost all problems have many solutions to a region in which almost all problems have no sol... / B M Smith Division of Artificial Intelligence May Abstract The
48 The RoboCup Synthetic Agent Challenge 97 - Kitano, Tambe, Stone (1997)(Correct)
RoboCup Challenge offers a set of challenges for intelligent agent researchers using a friendly competition in a dynamic, real-time, multiagent domain. While RoboCup in general envisions longer range ... / To appear in Applied Artificial Intelligence AAI Journal . br a novel opportunity for machine learning planning and multi-agent
47 Competitive Environments Evolve Better Solutions for Complex Tasks - Angeline, Pollack (1993)(Correct)
In the typical genetic algorithm experiment, the fitness function is constructed to be independent of the contents of the population to provide a consistent objective measure. Such objectivity entails... / B. Pollack Laboratory for Artificial Intelligence Research Computer and br is a long standing topic in machine learning Samuel Tesauro
46 Selection of Relevant Features and Examples in Machine Learning - Blum, Langley (1997)(Correct)
In this survey, we review work in machine learning on methods for handling data sets containing large amounts of irrelevant information. We focus on two key issues: the problem of selecting relevant f... / in the special issue of Artificial Intelligence on Relevance'R. br Features and Examples in Machine Learning Avrim L. Blum
46 Web Mining: Information and Pattern Discovery on the World Wide Web - Cooley, Mobasher, Srivastava (1997)(Correct)
Application of data mining techniques to the World Wide Web, referred to as Web mining, has been the focus of several recent research projects and papers. However, there is no established vocabulary, ... / AAAI Spring Symposium on Machine Learning in Information Access br Nets Machine Learning and Expert Systems. Morgan Kaufmann San Mateo
46 Local Learning in Probabilistic Networks With Hidden Variables - Russell (1995)(Correct)
Probabilistic networks, which provide compact descriptions of complex stochastic relationships among several random variables, are rapidly becoming the tool of choice for uncertain reasoning in artifi... / for uncertain reasoning in artificial intelligence. We show that networks br networks from data. Machine Learning - . Dayan
45 Incremental Multi-Step Q-Learning - Peng, Williams (1996)(Correct)
This paper presents a novel incremental algorithm that combines Q-learning, a
well-known dynamic programming-based reinforcement learning method, with the TD() return
estimation process, which is ty... / less data and less time. Machine Learning - . Pendrith br C. H. Dayan P. Q-learning. Machine Learning - .
43 Context-Specific Independence in Bayesian Networks - Boutilier, Friedman, Goldszmidt.. (1996)(Correct)
Bayesiannetworks provide a languagefor qualitatively representing the conditional independence properties of a distribution. This allows a natural and compact representation of the distribution, eases... / and Bayesian networks. Artificial Intelligence - . br trees also known in the machine learning community as decision trees
43 Relational Learning of Pattern-Match Rules for Information Extraction - Califf, Mooney (1997)(Correct)
Information extraction is a form of shallow text
processing that locates a specified set of relevant
items in a natural-language document. Systems
for this task require significant domain-specific
kno... / National Conference on Artificial Intelligence - . Califf M. br them a good application for machine learning. This paper presents a
43 Overcoming Incomplete Perception with Utile Distinction Memory - McCallum (1993)(Correct)
This paper presents a method by which a
reinforcement learning agent can solve the
incomplete perception problem using memory.
The agent uses a hidden Markov model
(HMM) to represent its internal stat... / International Conference on Machine Learning Austin Texas . Morgan
43 Cooperative Information Gathering: A Distributed Problem Solving.. - Oates, Prasad, Lesser(Correct)
We contrast two approaches to the problem of information gathering that may be characterized as distributed processing and distributed problem solving. The former is characteristic of most existing in... / systems and distributed artificial intelligence. This approach called br International Conference on Machine Learning Chicago IL .
42 A Comparative Evaluation of Voting and Meta-learning on Partitioned.. - Philip Chan (1995)(Correct)
Much of the research in inductive learning
concentrates on problems with relatively small
amounts of data. With the coming age of very
large network computing, it is likely that orders
of magnitude mo... / language processing and artificial intelligence. IEEE Trans. Know. Data. br Proc. Eighth Intl. Work. Machine Learning pp. - Chan P.
42 Automatic SAT-Compilation of Planning Problems - Ernst, Millstein, Weld (1997)(Correct)
Recent work by Kautz et al. provides tantalizing
evidence that large, classical planning problems
may be efficiently solved by translating them into
propositional satisfiability problems, using stocha... / Joint Conference on Artificial Intelligence IJCAI- Nagoya
42 Feature Subset Selection Using A Genetic Algorithm - Yang, Honavar (1998)(Correct)
Practical pattern classification and knowledge discovery problems require selection of a subset of attributes or features (from a much larger set) to represent the patterns to be classified. This pape... / I. . Artificial Intelligence Learning - br were obtained from the machine learning data repository at the
42 Information Extraction from HTML: Application of a General Machine.. - Freitag (1998)(Correct)
Because the World Wide Web consists primarily of
text, information extraction is central to any effort that
would use the Web as a resource for knowledge discovery.
We show how information extraction ... / American Association for Artificial Intelligence www.aaai.org All br Application of a General Machine Learning Approach Dayne Freitag
41 Data Mining - The Search for Knowledge in Databases - Holsheimer, Siebes (1991)(Correct)
Data mining is the search for relationships and global patterns that exist in large databases, but are `hidden'
among the vast amounts of data, such as a relationship between patient data and their me... / in machine learning-an artificial intelligence research area. A machine br as taken from the area of machine learning. Another important problem
41 Biological Metaphors and the Design of Modular Artificial Neural.. - Boers, Kuiper (1992)(Correct)
In this thesis, a method is proposed with which good modular artificial neural network structures can be found automatically using a computer program. A number of biological metaphors are incorporated... / The human brain Artificial intelligence The neuron Neurons br in search optimization and machine learning. Addison-Wesley Reading
41 Tracking the Best Expert - Mark Herbster (1995)(Correct)
We generalize the recent worst-case loss bounds
for on-line algorithms where the additional loss
of the algorithm on the whole sequence of examples
over the loss of the best expert is bounded.
The gen... / linear-threshold algorithm. Machine Learning - . Lit
41 Using meta-logic to reconcile reactive with rational agents - Kowalski (1995)(Correct)
In this paper I outline an attempt to reconcile the traditional Artificial
Intelligence notion of a logic-based rational agent with the contrary notion of
a reactive agent that acts "instinctively" ... / reconcile the traditional Artificial Intelligence notion of a logic-based br to less promising ones. In expert system approaches on the other
41 Adaptive Web Sites: an AI Challenge - Perkowitz (1997)(Correct)
The creation of a complex web site is a thorny problem in user interface design. First, different visitors have distinct goals. Second, even a single visitor may have different needs at different time... / Many advances in artificial intelligence both practical and br projects in plan recognition machine learning knowledge representation
40 Preferential Semantics for Goals - Wellman, Doyle (1991)(Correct)
Goals, as typically conceived in AI planning, provide
an insufficient basis for choice of action, and hence are
deficient as the sole expression of an agent's objectives.
Decision-theoretic utilities ... / National Conference on Artificial Intelligence AAAI- July
40 Behavior of Database Production Rules: Termination, Confluence, and.. - Aiken, Widom, Hellerstein (1992)(Correct)
Static analysis methods are given for determining whether arbitrary sets of database production rules are (1) guaranteed to terminate unknown Proc. of 1992 ACM-SIGMOD Conference, pages 59--68
Behavi... / AAAI National Conference on Artificial Intelligence . SJGP M. br efficient knowledge-bases and expert systems. However it can be very
40 Powerful Techniques for the Automatic Generation of Invariants - Bensalem (1996)(Correct)
When proving invariance properties of programs one is faced
with two problems. The first problem is related to the necessity of proving
tautologies of the considered assertion language, whereas the ... / rd Int. Joint Conf. on Artificial Intelligence Stanford CA . .
39 Tight Performance Bounds on Greedy Policies Based on Imperfect Value.. - Williams (1993)(Correct)
Consider a given value function on states of a Markov decision problem, as might result from applying a reinforcement learning algorithm. Unless this value function equals the corresponding optimal va... / optimalvalue functions. Machine Learning. Sutton R. S. br C. H. Dayan P. Q-learning. Machine Learning - .
39 Convergence results for the EM approach to mixtures of experts.. - Jordan, Xu (1993)(Correct)
The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts a... / Institute Of Technology Artificial Intelligence Laboratory And br statistics literature and the machine learning literature where
39 Model-Based Monitoring of Dynamic Systems - Dvorak (1989)(Correct)
Industrial process plants such as chemical refineries
and electric power generation are examples
of continuous-variable dynamic systems (CVDS)
whose operation is continuously monitored for abnormal
be... / Joint Conference on Artificial Intelligence IJCAI- Los Altos br Induction of Decision Trees. Machine Learning - . . Paul A.
39 Using experience in learning and problem solving - Koton (1989)(Correct)
This paper contains a brief overview of case-based reasoning (CBR) with an emphasis on
European activities in the field. The main objective was to have a balance between brevity
and expressiveness and... / and Enric Plaza IIIA-Artificial Intelligence Research Institute br in automated reasoning and machine learning. In case-based reasoning a
39 Planning for Temporally Extended Goals - Bacchus (1996)(Correct)
In planning, goals have been traditionally been viewed as specifying a set of desirable final states. Any plan that transforms the current state to one of these desirable states is viewed to be correc... / Joint Conference on Artificial Intelligence IJCAI pages
39 Algebraic Functions For Recognition - Shashua (1994)(Correct)
In the general case, a trilinear relationship between three perspective views is shown to exist. The trilinearity
result is shown to be of much practical use in visual recognition by alignment --- yi... / Institute Of Technology Artificial Intelligence Laboratory And Center
38 A Tourist Guide through Treewidth - Bodlaender (1993)(Correct)
A short overview is given of many recent results in algorithmic graph theory that deal with the notions treewidth, and pathwidth. We discuss algorithms that find tree-decompositions, algorithms that u... / details see e.g. . Expert systems Graphs modelling certain
37 Subsumption Algorithms for Concept Languages - Hollunder, Nutt (1990)(Correct)
We investigate the subsumption problem in logic-based knowledge representation
languages of the kl-one family and give decision procedures.
All our languages contain as a kernel the logical connective... / German Research Center for Artificial Intelligence Postfach D-
37 Representing Continuous Change in The Event Calculus - Shanahan (1990)(Correct)
The Event Calculus of Kowalski and Sergot only deals with discrete
change. This paper introduces a simplified version of the Event Calculus and
extends it to deal with continuous change, as in the hei... / of Action and Time Artificial Intelligence vol p .
36 On the Complexity of Blocks-World Planning - Gupta (1992)(Correct)
In this paper, we show that in the best-known version of the blocks world (and
several related versions), planning is difficult, in the sense that finding an optimal plan
is NP-hard. However, the NP-h... / Artificial Intelligence - - August
36 Integrating Classification and Association Rule Mining - Liu (1998)(Correct)
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy so... / American Association for Artificial Intelligence www.aaai.org All br existing algorithms in the machine learning literature that can be used
36 PAC-Learnability of Determinate Logic Programs - Dzeroski, Muggleton, Russell (1992)(Correct)
The field of Inductive Logic Programming
(ILP) is concerned with inducing logic programs
from examples in the presence of background
knowledge. This paper defines the ILP
problem, and describes the v... / and Valiant's model. Artificial Intelligence - . br successes within the field of machine learning have derived from systems
35 A Knowledge-Based Configurator that Supports Sales, Engineering, and.. - Jon Wright (1993)(Correct)
INTRODUCTION
PROSE (PRoduct OfferingS Expertise) is a knowledge based engineering and ordering
platform that supports sales and order processing at AT&T Network Systems (AT&T-NS).
The cornerstone of ... / pioneered in the artificial intelligence community was developed br Barker and Dennis E. O'Connor Expert Systems for Configuration at Digital
35 Learning to Classify Text from Labeled and Unlabeled Documents - Nigam, McCallum, Thrun, Mitchell (1998)(Correct)
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper shows that the accuracy... / American Association for Artificial Intelligence www.aaai.org All br scarce labeled data in machine learning problems especially when
35 An Adaptive Web Page Recommendation Service - Balabanovic (1997)(Correct)
An adaptive recommendation service seeks to adapt
to its users, providing increasingly personalized recommendations
over time. In this paper we introduce
the "Fab" adaptive web page recommendation ser... / Joint Conference on Artificial Intelligence. Mauldin M. L.and br lies at the intersection of machine learning ML and IR and there is a
34 Issues and Approaches in the Design of Collective Autonomous Agents - Mataric (1995)(Correct)
The problem of synthesizing and analyzing collective autonomous agents has only recently begun to be practically studied by the robotics community. This paper overviews the most prominent directions o... / was performed at the MIT Artificial Intelligence Laboratory. of br International Conference on Machine Learning ML- Morgan Kauffman
34 Coevolving High-Level Representations - Angeline (1994)(Correct)
Several evolutionary simulations allow for a dynamic resizing of the
genotype. This is an important alternative to constraining the genotype's
maximum size and complexity. In this paper, we add an add... / B. Pollack Laboratory for Artificial Intelligence Research Computer and br in Search Optimization and Machine Learning Reading MA
33 The Behavior Language; User's Guide - Brooks (1990)(Correct)
The Behavior Language is a rule-based real-time parallel robot programming language originally based on ideas from [Brooks 86], [Connell 89], and [Maes 89]. It compiles into a modified and extended ve... / Institute Of Technology Artificial Intelligence Laboratory A. I. Memo
33 Classification And Detection Of Computer Intrusions - Kumar (1995)(Correct)
Some computer security breaches cannot be prevented using access and information flow control techniques. These breaches may be a consequence of system software bugs, hardware or software failures, in... / Joint Conference on Artificial Intelligence August . CKS br International Conference on Machine Learning pages - . Morgan
33 DAMN: A Distributed Architecture for Mobile Navigation - Rosenblatt (1997)(Correct)
ion
Increasing
Responsiveness
Page 20 Section 2.1: Architectural Issues
Figure 2-7 : Hierarchical architecture with recursive task decomposition.
(Figure reproduced from [65], with permission.)
Whi... / people at the Hughes Artificial Intelligence Center and the br human decision-making process. Machine learning techniques such as
32 Caching and Lemmaizing in Model Elimination Theorem Provers - Astrachan (1992)(Correct)
Theorem provers based on model elimination have exhibited
extremely high inference rates but have lacked a redundancy control
mechanism such as subsumption. In this paper we report on work done
to m... / ola cs.duke.edu Artificial Intelligence Center SRI br D. Michie. Memo functions and machine learning. Nature - April
32 Representing Control: A Study of the CPS Transformation - Danvy, Filinski (1992)(Correct)
continuations:
A mathematical semantics for handling full functional jumps. In Proceedings of the
1988 ACM Conference on Lisp and Functional Programming, pages 52--62, Snowbird, Utah,
July 1988.
[19] ... / Report AI-TR- Artificial Intelligence Laboratory Massachusetts
32 Surface Approximation and Geometric Partitions - Agarwal, Suri (1994)(Correct)
Motivated by applications in computer graphics, visualization, and scientific computation, we study the computational complexity of the following problem: Given a set S of n points sampled from a biva... / following problem arising in machine learning given n red' and m
32 Lamarckian Learning in Multi-agent Environments - Grefenstette (1991)(Correct)
Genetic algorithms gain much of their power from
mechanisms derived from the field of population
genetics. However, it is possible, and in some
cases desirable, to augment the standard mechanisms
with... / for Applied Research in Artificial Intelligence Code Naval br to explore the application of machine learning techniques to reactive
32 Reasoning With Characteristic Models - Henry Kautz (1993)(Correct)
Formal AI systems traditionally represent knowledge using logical formulas.
We will show, however, that for certain kinds of information, a modelbased
representation is more compact and enables faster... / National Conference on Artificial Intelligence AAAI- Washington
31 Representing Action: Indeterminacy and Ramifications - Giunchiglia (1997)(Correct)
We define and study a high-level language for describing actions, more
expressive than the action language A introduced by Gelfond and Lifschitz.
The new language, AR, allows us to describe actions wi... / of the central problems of Artificial Intelligence. Existing approaches
31 LIME: Linda Meets Mobility - Picco, Murphy, Roman (1999)(Correct)
Lime is a system designed to assist in the rapid development of dependable mobile applications over both wired and ad hoc networks. Mobile agents reside on mobile hosts and all communication takes pla... / ranging from economics to artificial intelligence and is at the core of a
31 Compiling Prior Knowledge Into an Explicit Bias - Cohen (1992)(Correct)
Current theory-guided learning systems are inflexible, in that they are committed to performing one particular class of theory corrections; this is problematic because in some cases special-purpose th... / National Conference on Artificial Intelligence Boston Massachusetts br International Conference on Machine Learning Compiling Prior Knowledge
30 A Computational Market Model for Distributed Configuration Design - Wellman (1995)(Correct)
This paper presents a precise market model for a well-defined class of distributed
configuration design problems. Given a design problem, the model defines a
computational economy to allocate basic re... / congruent with much work in Artificial Intelligence where we attempt to
30 Equational Reasoning and Term Rewriting Systems - Plaisted (1993)(Correct)
ordering structures and computational complexity. Technical
Report CSD-TR-621, University of London, May 1990.
[Che81] P. Chew. Unique normal forms in term rewriting systems with repeated variables. I... / the Handbook of Logic in Artificial Intelligence and Logic Programming
30 Genetic Algorithms and Artificial Life - Mitchell, Forrest (1993)(Correct)
Genetic algorithms are computational models of evolution that play a central role in many artificial-life models. We review the history and current scope of research on genetic algorithms in artificia... / Research Notes in Artificial Intelligence Los Altos CA . br GAs have been used for many machine-learning applications including
29 Multiresolution Sampling Procedure for Analysis and Synthesis of.. - De Bonet (1998)(Correct)
This paper outlines a technique for treating input texture images
as probability density estimators from which new textures, with
similar appearance and structural properties, can be sampled. In a
two... / Learning Vision Group Artificial Intelligence Laboratory Massachusetts
29 Easy Problems are Sometimes Hard - Gent, Walsh (1994)(Correct)
We present a detailed experimental investigation of the easy-hard-easy phase transition for randomly generated instances of satisfiability problems. Problems in the hard part of the phase transition h... / from the department of Artificial Intelligence Edinburgh. This version
29 Experiments on Multistrategy Learning by Meta-Learning - Chan (1993)(Correct)
In this paper, we propose meta-learning as a general technique
to combine the results of multiple learning algorithms,
each applied to a set of training data. We detail several metalearning
strategies... / language processing and artificial intelligence. IEEE Trans. Know. Data. br encouraging results. Machine learning techniques are central to
29 Pattern Associativity and the Retrieval of Semantic Networks - Levinson (1992)(Correct)
p.
1011-1024, Wiley, New York, 1987.
[58] C. Stanfill and D. Waltz, Toward memory-based reasoning. Comm. of the ACM, 29(12), 12131228
(December 1986).
[59] E. H. Sussenguth Jr., A graph-theoretic alg... / ed.Encyclopedia of Artificial Intelligence p. - Wiley
28 A Formal Framework for Agency and Autonomy - Luck, d'Inverno (1995)(Correct)
With the recent rapid growth of interest in MultiAgent Systems, both in artificial intelligence and software engineering, has come an associated difficulty concerning basic terms and concepts. In part... / Systems both in artificial intelligence and software
28 Computational Neuroethology: A Provisional Manifesto - Cliff (1991)(Correct)
This paper is concerned with approaches to computational modelling of the neural mechanisms underlying behaviour. It examines the relationship between computational neuroscience (e.g. [52, 34]) and th... / of cognitive science and artificial intelligence see e.g. br . . AI Artificial Intelligence or Artificial Insects Moreover
28 Flexible Discriminant Analysis by Optimal Scoring - Hastie, Tibshirani, Buja (1993)(Correct)
Fisher's linear discriminant analysis is a valuable tool for multigroup
classification. With a large number of predictors, one can find
a reduced number of discriminant coordinate functions that are "... / is becoming popular in the artificial intelligence community. There have
28 A Logic of Relative Desire - Doyle, al. (1991)(Correct)
Although many have proposed formal characterizations of belief structures as bases for rational action, the problem of characterizing rational desires has attracted little attention. AI relies heavi... / approach to planning in artificial intelligence represents desires by
28 Learning in the Presence of Concept Drift and Hidden Contexts - Widmer, Kubat (1996)(Correct)
On-line learning in domains where the target concept depends on some hidden context poses serious problems. Context shifts can induce changes in the target concepts, producing what is known as concept... / of Medical Cybernetics and Artificial Intelligence University of Vienna br we discuss related research in Machine Learning and some relevant results in
27 Co-Evolving Soccer Softbot Team Coordination with Genetic Programming - Luke (1997)(Correct)
Genetic Programming is a promising new method
for automatically generating functions and algorithms
through natural selection. In contrast to
other learning methods, Genetic Programming's automatic
pr... / robotics and agent-based Artificial Intelligence by presenting a domain
27 Pitfalls of Agent-Oriented Development - Wooldridge, Jennings (1998)(Correct)
While the theoretical and experimental foundations of agent-based
systems are becoming increasingly well understood, comparatively
little effort has been devoted to understanding the pragmatics of
(mu... / and failures of Artificial Intelligence AI often believe that br to that experienced against expert systems logic programming and all
27 A Robot Controller Using Learning by Imitation - Hayes, Demiris (1994)(Correct)
Roboticists have already invested considerable energy in building robot controllers which model the
learning capacities of single animals. In this paper we present a new type of controller which dra... / Department of Artificial Intelligence University of Edinburgh
27 Learning Dynamic Bayesian Networks - Ghahramani (1997)(Correct)
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (HMMs) used in speec... / Lecture Notes in Artificial Intelligence. Springer-Verlag. . br was first suggested in the machine learning literature by Saul and
27 On the Complexity of Solving Markov Decision Problems - Littman, Dean, Kaelbling (1995)(Correct)
Markov decision problems (MDPs) provide
the foundations for a number of problems
of interest to AI researchers studying automated
planning and reinforcement learning.
In this paper, we summarize resul... / and practitioners in artificial intelligence and operations research br International Conference on Machine Learning page . Kalai G.
27 Factor Graphs and the Sum-Product Algorithm - Kschischang, Frey, Loeliger (1998)(Correct)
A factor graph is a bipartite graph that expresses how a "global" function of many variables factors into a product of "local" functions. Factor graphs subsume many other graphical models including Ba... / of algorithms developed in artificial intelligence signal processing and br J. Frey Graphical Models for Machine Learning and Digital Communication.
27 Weakly Learning DNF and Characterizing Statistical Query Learning.. - Blum (1994)(Correct)
We present new results, both positive and negative, on the well-studied problem of learning disjunctive normal form (DNF) expressions. We first prove that an algorithm due to Kushilevitz and Mansour [... / proposed in the experimental machine learning communities such as the ID
27 A Framework for Combining Symbolic and Neural Learning - Shavlik (1992)(Correct)
This article describes an approach to combining symbolic and connectionist approaches to
machine learning. A three-stage framework is presented and the research of several groups is
reviewed with resp... / network approaches to artificial intelligence and presents a framework br connectionist approaches to machine learning. A three-stage framework is
26 Data Mining Approaches for Intrusion Detection - Lee, Stolfo (1998)(Correct)
In this paper we discuss our research in developing general and systematic methods for intrusion detection. The key ideas are to use data mining techniques to discover consistent and useful patterns o... / . Fra J. Frank. Artificial intelligence and intrusion detection br pattern recognition machine learning and database. Several types
26 Multi-class Support Vector Machines - Weston, Watkins (1998)(Correct)
this paper. Thanks
also to M. Stitson for writing the code for one-against-one and one-against-all SV
classification. We also thank Kai Vogtlaender for useful comments.
In communication with V. Vapnik... / problems from the UCI machine learning repository Where no br set of functions which the learning machine implements is chosen a
26 A Linear Method for Deviation Detection in Large Databases - Arning, Agrawal, Raghavan (1996)(Correct)
We describe the problem of finding deviations in large
data bases. Normally, explicit information outside the
data, like integrity constraints or predefined patterns,
is used for deviation detection. ... / . Machine Learning An Artificial Intelligence Approach volume I. br the fields of Databases and Machine Learning for a long time. Deviations