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» Local Minimax Learning of Approximately Polynomial Functions
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JMLR
2006
153views more  JMLR 2006»
13 years 7 months ago
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Jelle R. Kok, Nikos A. Vlassis
IJON
2007
184views more  IJON 2007»
13 years 7 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
FOCS
2010
IEEE
13 years 5 months ago
A Fourier-Analytic Approach to Reed-Muller Decoding
Abstract. We present a Fourier-analytic approach to list-decoding Reed-Muller codes over arbitrary finite fields. We use this to show that quadratic forms over any field are locall...
Parikshit Gopalan
CORR
2010
Springer
182views Education» more  CORR 2010»
13 years 7 months ago
Fast Convergence of Natural Bargaining Dynamics in Exchange Networks
Bargaining networks model the behavior of a set of players who need to reach pairwise agreements for making profits. Nash bargaining solutions in this context correspond to soluti...
Yashodhan Kanoria, Mohsen Bayati, Christian Borgs,...
ECML
2007
Springer
13 years 11 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass