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Learnability in Optimality Theory
, 1995
"... In this article we show how Optimality Theory yields a highly general Constraint Demotion principle for grammar learning. The resulting learning procedure specifically exploits the grammatical structure of Optimality Theory, independent of the content of substantive constraints defining any given gr ..."
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Cited by 528 (34 self)
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efficient convergence to a correct grammar. We discuss implications for learning from overt data only, as well as other learning issues. We argue that Optimality Theory promotes confluence of the demands of more effective learnability and deeper linguistic explanation.
The strength of weak learnability
 Machine Learning
, 1990
"... Abstract. This paper addresses the problem of improving the accuracy of an hypothesis output by a learning algorithm in the distributionfree (PAC) learning model. A concept class is learnable (or strongly learnable) if, given access to a Source of examples of the unknown concept, the learner with h ..."
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Cited by 861 (24 self)
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Abstract. This paper addresses the problem of improving the accuracy of an hypothesis output by a learning algorithm in the distributionfree (PAC) learning model. A concept class is learnable (or strongly learnable) if, given access to a Source of examples of the unknown concept, the learner
Fluctuations, effective learnability and metastability in analysis
"... This paper discusses what kind of quantitative information one can extract under which circumstances from proofs of convergence statements in analysis. We show that from proofs using only a limited amount of the lawofexcludedmiddle, one can extract functionals (B, L), where L is a learning proced ..."
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Cited by 6 (1 self)
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procedure for a rate of convergence which succeeds after at most B(a)many mind changes. This (B, L)learnability provides quantitative information strictly in between a full rate of convergence (obtainable in general only from semiconstructive proofs) and a rate of metastability in the sense of Tao
Learnability
"... LEARNABILITY. The mathematical theory of language learnability (also known as learnability theory, grammar induction, or grammatical inference) deals with idealized “learning procedures ” for acquiring grammars on the basis of exposure to evidence about languages. In one classic paradigm, presented ..."
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LEARNABILITY. The mathematical theory of language learnability (also known as learnability theory, grammar induction, or grammatical inference) deals with idealized “learning procedures ” for acquiring grammars on the basis of exposure to evidence about languages. In one classic paradigm, presented
On the Learnability
"... This paper was selected by a process of anonymous peer reviewing for presentation at ..."
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This paper was selected by a process of anonymous peer reviewing for presentation at
“Learnable
"... Abstract: Short summary of most important research results that explain why the work was done, what was accomplished, and how it pushed scientific frontiers or advanced the field. This summary will be used for archival purposes and will be added to a searchable DoD database. First, we addressed the ..."
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Abstract: Short summary of most important research results that explain why the work was done, what was accomplished, and how it pushed scientific frontiers or advanced the field. This summary will be used for archival purposes and will be added to a searchable DoD database. First, we addressed the problem of detecting the period in which information diffusion burst occurs from a single observed diffusion sequence under the assumption that the delay of the information propagation over a social network follows the exponential distribution. To be more precise, we formulated the problem of detecting the change points and finding the values of the time delay parameter in the exponential distribution as an optimization problem of maximizing the likelihood of generating the observed diffusion sequence. We devised an efficient iterative search algorithm for the change point detection whose time complexity is almost linear to the number of data points. We tested the algorithm against the real Twitter data of the 2011 Tohoku earthquake and tsunami, and experimentally confirmed that the algorithm is much more efficient than the exhaustive naive search and is much more accurate than the simple greedy search. Second, we addressed the problem of how people make their own decisions based on their neighbors ’ opinions. The model best suited to discuss this problem is the voter model and several
Boosting a Weak Learning Algorithm By Majority
, 1995
"... We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses, each of which is generated by training the given learning algorithm on a different set of examples. Our algorithm is based on ideas pr ..."
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Cited by 516 (15 self)
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presented by Schapire in his paper "The strength of weak learnability", and represents an improvement over his results. The analysis of our algorithm provides general upper bounds on the resources required for learning in Valiant's polynomial PAC learning framework, which are the best general
Mining Association Rules between Sets of Items in Large Databases
 IN: PROCEEDINGS OF THE 1993 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, WASHINGTON DC (USA
, 1993
"... We are given a large database of customer transactions. Each transaction consists of items purchased by a customer in a visit. We present an efficient algorithm that generates all significant association rules between items in the database. The algorithm incorporates buffer management and novel esti ..."
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Cited by 3260 (17 self)
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estimation and pruning techniques. We also present results of applying this algorithm to sales data obtained from a large retailing company, which shows the effectiveness of the algorithm.
Usability Analysis of Visual Programming Environments: a `cognitive dimensions' framework
 JOURNAL OF VISUAL LANGUAGES AND COMPUTING
, 1996
"... The cognitive dimensions framework is a broadbrush evaluation technique for interactive devices and for noninteractive notations. It sets out a small vocabulary of terms designed to capture the cognitivelyrelevant aspects of structure, and shows how they can be traded off against each other. T ..."
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Cited by 510 (13 self)
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. The purpose of this paper is to propose the framework as an evaluation technique for visual programming environments. We apply it to two commerciallyavailable dataflow languages (with further examples from other systems) and conclude that it is effective and insightful; other HCIbased evaluation
Results 1  10
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