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Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition

by Thomas G. Dietterich - Journal of Artificial Intelligence Research , 2000
"... This paper presents a new approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into a hierarchy of smaller MDPs and decomposing the value function of the target MDP into an additive combination of the value functions of the smaller MDPs. Th ..."
Abstract - Cited by 443 (6 self) - Add to MetaCart
This paper presents a new approach to hierarchical reinforcement learning based on decomposing the target Markov decision process (MDP) into a hierarchy of smaller MDPs and decomposing the value function of the target MDP into an additive combination of the value functions of the smaller MDPs

The rate-distortion function for source coding with side information at the decoder

by Aaron D. Wyner, Jacob Ziv - IEEE Trans. Inform. Theory , 1976
"... Abstract-Let {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a seque ..."
Abstract - Cited by 1060 (1 self) - Add to MetaCart
the infimum is with respect to all auxiliary random variables Z (which take values in a finite set 3) that satisfy: i) Y,Z conditiofally independent given X; ii) there exists a functionf: “Y x E +.%, such that E[D(X,f(Y,Z))] 5 d. Let Rx, y(d) be the rate-distortion function which results when the encoder

Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition

by Y. C. Pati, R. Rezaiifar, P. S. Krishnaprasad - in Conference Record of The Twenty-Seventh Asilomar Conference on Signals, Systems and Computers , 1993
"... In this paper we describe a recursive algorithm to compute representations of functions with respect to nonorthogonal and possibly overcomplete dictionaries of elementary building blocks e.g. aiEne (wa.velet) frames. We propoeea modification to the Matching Pursuit algorithm of Mallat and Zhang (199 ..."
Abstract - Cited by 637 (1 self) - Add to MetaCart
In this paper we describe a recursive algorithm to compute representations of functions with respect to nonorthogonal and possibly overcomplete dictionaries of elementary building blocks e.g. aiEne (wa.velet) frames. We propoeea modification to the Matching Pursuit algorithm of Mallat and Zhang

A Scalable Content-Addressable Network

by Sylvia Ratnasamy , Paul Francis, Mark Handley, Richard Karp, Scott Shenker - IN PROC. ACM SIGCOMM 2001 , 2001
"... Hash tables – which map “keys ” onto “values” – are an essential building block in modern software systems. We believe a similar functionality would be equally valuable to large distributed systems. In this paper, we introduce the concept of a Content-Addressable Network (CAN) as a distributed infra ..."
Abstract - Cited by 3371 (32 self) - Add to MetaCart
Hash tables – which map “keys ” onto “values” – are an essential building block in modern software systems. We believe a similar functionality would be equally valuable to large distributed systems. In this paper, we introduce the concept of a Content-Addressable Network (CAN) as a distributed

Advances in Prospect Theory: Cumulative Representation of Uncertainty

by Amos Tversky, Daniel Kahneman - JOURNAL OF RISK AND UNCERTAINTY, 5:297-323 (1992) , 1992
"... We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows differ ..."
Abstract - Cited by 1717 (17 self) - Add to MetaCart
different weighting functions for gains and for losses. Two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting functions. A review of the experimental evidence and the results of a new experiment confirm a

End-To-End Arguments In System Design

by Jerome H. Saltzer, David P. Reed, David D. Clark , 1984
"... This paper presents a design principle that helps guide placement of functions among the modules of a distributed computer system. The principle, called the end-to-end argument, suggests that functions placed at low levels of a system may be redundant or of little value when compared with the cost o ..."
Abstract - Cited by 1037 (10 self) - Add to MetaCart
This paper presents a design principle that helps guide placement of functions among the modules of a distributed computer system. The principle, called the end-to-end argument, suggests that functions placed at low levels of a system may be redundant or of little value when compared with the cost

The Concept of a Linguistic Variable and its Application to Approximate Reasoning

by L. A. Zadeh - Journal of Information Science , 1975
"... By a linguistic variable we mean a variable whose values are words or sentences in a natural or artificial language. I:or example, Age is a linguistic variable if its values are linguistic rather than numerical, i.e., young, not young, very young, quite young, old, not very oldand not very young, et ..."
Abstract - Cited by 1430 (9 self) - Add to MetaCart
rule which generates the terms in T(z); and M is a semantic rule which associates with each linguistic value X its meaning, M(X), where M(X) denotes a fuzzy subset of U The meaning of a linguistic value X is characterized by a compatibility function, c: l / + [0, I], which associates with each u in U

Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments

by John Geweke - IN BAYESIAN STATISTICS , 1992
"... Data augmentation and Gibbs sampling are two closely related, sampling-based approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accurac ..."
Abstract - Cited by 604 (12 self) - Add to MetaCart
accuracy of the approximations to the expected value of functions of interest under the posterior. In this paper methods from spectral analysis are used to evaluate numerical accuracy formally and construct diagnostics for convergence. These methods are illustrated in the normal linear model

Notions of Computation and Monads

by Eugenio Moggi , 1991
"... The i.-calculus is considered a useful mathematical tool in the study of programming languages, since programs can be identified with I-terms. However, if one goes further and uses bn-conversion to prove equivalence of programs, then a gross simplification is introduced (programs are identified with ..."
Abstract - Cited by 867 (15 self) - Add to MetaCart
with total functions from calues to values) that may jeopardise the applicability of theoretical results, In this paper we introduce calculi. based on a categorical semantics for computations, that provide a correct basis for proving equivalence of programs for a wide range of notions of computation.

Object Detection with Discriminatively Trained Part Based Models

by Pedro F. Felzenszwalb, Ross B. Girshick, David McAllester, Deva Ramanan
"... We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their ..."
Abstract - Cited by 1422 (49 self) - Add to MetaCart
, their value had not been demonstrated on difficult benchmarks such as the PASCAL datasets. Our system relies on new methods for discriminative training with partially labeled data. We combine a margin-sensitive approach for data-mining hard negative examples with a formalism we call latent SVM. A latent SVM
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