Results 11  20
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9,447
Proving the correctness of multiprocess programs.
 IEEE Transactions on Software Engineering,
, 1977
"... AbstractThe inductive assertion method is generalized to permit formal, machineverifiable proofs of correctness for multiprocess programs. Individual processes are represented by ordinary flowcharts, and no special synchronization mechanisms are assumed, so the method can be applied to a large cl ..."
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Cited by 391 (17 self)
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AbstractThe inductive assertion method is generalized to permit formal, machineverifiable proofs of correctness for multiprocess programs. Individual processes are represented by ordinary flowcharts, and no special synchronization mechanisms are assumed, so the method can be applied to a large
Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier
"... The simple Bayesian classifier (SBC) is commonly thought to assume that attributes are independent given the class, but this is apparently contradicted by the surprisingly good performance it exhibits in many domains that contain clear attribute dependences. No explanation for this has been proposed ..."
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Cited by 361 (8 self)
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The simple Bayesian classifier (SBC) is commonly thought to assume that attributes are independent given the class, but this is apparently contradicted by the surprisingly good performance it exhibits in many domains that contain clear attribute dependences. No explanation for this has been
EXERCISES IN THE BIRATIONAL GEOMETRY OF ALGEBRAIC VARIETIES
, 2008
"... The book [KM98] gave an introduction to the birational geometry of algebraic varieties, as the subject stood in 1998. The developments of the last decade made the more advanced parts of Chapters 6 and 7 less important and the detailed treatment of surface singularities in Chapter 4 less necessary. H ..."
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Cited by 322 (1 self)
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literature and in “true ” applications. (CalabiYau): These are completely classified (Abelian, K3, Enriques, hyperelliptic) and their geometry is rich. They are of great interest to other mathematicians. (General type): They have a canonical model with Du Val singularities and ample canonical class
An Evolutionary Algorithm that Constructs Recurrent Neural Networks
 IEEE TRANSACTIONS ON NEURAL NETWORKS
"... 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 interactions between network structure and function are not well understood. Evolutionary computation, whi ..."
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Cited by 266 (14 self)
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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 interactions between network structure and function are not well understood. Evolutionary computation
Selftaught learning: Transfer learning from unlabeled data
 Proceedings of the Twentyfourth International Conference on Machine Learning
, 2007
"... We present a new machine learning framework called “selftaught learning ” for using unlabeled data in supervised classification tasks. We do not assume that the unlabeled data follows the same class labels or generative distribution as the labeled data. Thus, we would like to use a large number of ..."
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Cited by 299 (20 self)
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We present a new machine learning framework called “selftaught learning ” for using unlabeled data in supervised classification tasks. We do not assume that the unlabeled data follows the same class labels or generative distribution as the labeled data. Thus, we would like to use a large number
A type and effect system for atomicity
 In PLDI 03: Programming Language Design and Implementation
, 2003
"... Ensuring the correctness of multithreaded programs is difficult, due to the potential for unexpected and nondeterministic interactions between threads. Previous work addressed this problem by devising tools for detecting race conditions, a situation where two threads simultaneously access the same d ..."
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Cited by 252 (22 self)
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is required, namely atomicity. Atomic methods can be assumed to execute serially, without interleaved steps of other threads. Thus, atomic methods are amenable to sequential reasoning techniques, which significantly simplifies both formal and informal reasoning about program correctness. This paper presents a
Estimation and prediction for stochastic blockstructures.
 Journal of the American Statistical Association
, 2001
"... A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is proposed. The probability model assumes that the vertices of the digraph are partitioned into several unobserved (latent) classes and that the probability distribution of the relation between two vertices depen ..."
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Cited by 231 (5 self)
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A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is proposed. The probability model assumes that the vertices of the digraph are partitioned into several unobserved (latent) classes and that the probability distribution of the relation between two vertices
Addressing the Curse of Imbalanced Training Sets: OneSided Selection
 In Proceedings of the Fourteenth International Conference on Machine Learning
, 1997
"... Adding examples of the majority class to the training set can have a detrimental effect on the learner's behavior: noisy or otherwise unreliable examples from the majority class can overwhelm the minority class. The paper discusses criteria to evaluate the utility of classifiers induced f ..."
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Cited by 234 (1 self)
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Adding examples of the majority class to the training set can have a detrimental effect on the learner's behavior: noisy or otherwise unreliable examples from the majority class can overwhelm the minority class. The paper discusses criteria to evaluate the utility of classifiers induced
SPUDD: Stochastic planning using decision diagrams
 In Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence
, 1999
"... Recently, structured methods for solving factored Markov decisions processes (MDPs) with large state spaces have been proposed recently to allow dynamic programming to be applied without the need for complete state enumeration. We propose and examine a new value iteration algorithm for MDPs that use ..."
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Cited by 234 (23 self)
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that uses algebraic decision diagrams (ADDs) to represent value functions and policies, assuming an ADD input representation of the MDP. Dynamic programming is implemented via ADD manipulation. We demonstrate our method on a class of large MDPs (up to 63 million states) and show that significant gains can
Results 11  20
of
9,447