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» Approximation algorithms for budgeted learning problems
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ML
2002
ACM
168views Machine Learning» more  ML 2002»
14 years 9 months ago
On Average Versus Discounted Reward Temporal-Difference Learning
We provide an analytical comparison between discounted and average reward temporal-difference (TD) learning with linearly parameterized approximations. We first consider the asympt...
John N. Tsitsiklis, Benjamin Van Roy
JMLR
2008
133views more  JMLR 2008»
14 years 9 months ago
Algorithms for Sparse Linear Classifiers in the Massive Data Setting
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
Suhrid Balakrishnan, David Madigan
NIPS
2000
14 years 11 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
ATAL
2008
Springer
14 years 11 months ago
Emerging coordination in infinite team Markov games
In this paper we address the problem of coordination in multi-agent sequential decision problems with infinite statespaces. We adopt a game theoretic formalism to describe the int...
Francisco S. Melo, M. Isabel Ribeiro
JALC
2007
90views more  JALC 2007»
14 years 9 months ago
Learning Unary Automata
We determine the complexity of learning problems for unary regular languages. We begin by investigating the minimum consistent dfa (resp. nfa) problem which is known not to be app...
Gregor Gramlich, Ralf Herrmann