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» Learning Monotonic Linear Functions
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IJCAI
2007
13 years 11 months ago
Using Linear Programming for Bayesian Exploration in Markov Decision Processes
A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Pablo Samuel Castro, Doina Precup
NIPS
2004
13 years 11 months ago
Worst-Case Analysis of Selective Sampling for Linear-Threshold Algorithms
We provide a worst-case analysis of selective sampling algorithms for learning linear threshold functions. The algorithms considered in this paper are Perceptron-like algorithms, ...
Nicolò Cesa-Bianchi, Claudio Gentile, Luca ...
STOC
2003
ACM
110views Algorithms» more  STOC 2003»
14 years 10 months ago
New degree bounds for polynomial threshold functions
A real multivariate polynomial p(x1, . . . , xn) is said to sign-represent a Boolean function f : {0, 1}n {-1, 1} if the sign of p(x) equals f(x) for all inputs x {0, 1}n. We gi...
Ryan O'Donnell, Rocco A. Servedio
GECCO
2006
Springer
196views Optimization» more  GECCO 2006»
14 years 1 months ago
An anticipatory approach to improve XCSF
XCSF is a novel version of learning classifier systems (LCS) which extends the typical concept of LCS by introducing computable classifier prediction. In XCSF Classifier predictio...
Amin Nikanjam, Adel Torkaman Rahmani
JMLR
2008
148views more  JMLR 2008»
13 years 9 months ago
Linear-Time Computation of Similarity Measures for Sequential Data
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
Konrad Rieck, Pavel Laskov