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ICML
2009
IEEE
16 years 5 months ago
Constraint relaxation in approximate linear programs
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...
Marek Petrik, Shlomo Zilberstein
159
Voted
ECML
2006
Springer
15 years 8 months ago
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Alessandro Moschitti
89
Voted
ICML
2010
IEEE
15 years 5 months ago
Internal Rewards Mitigate Agent Boundedness
Abstract--Reinforcement learning (RL) research typically develops algorithms for helping an RL agent best achieve its goals-however they came to be defined--while ignoring the rela...
Jonathan Sorg, Satinder P. Singh, Richard Lewis
118
Voted
FSS
2006
114views more  FSS 2006»
15 years 4 months ago
Fuzzy logic based variable step size algorithm for blind delayed source separation
Convergence of blind delayed source separation algorithms, which use constant learning rates, is known to be slow. We propose a fuzzy logic based approach to adaptively select the...
Vivek Nigam, Roland Priemer
KBS
2006
150views more  KBS 2006»
15 years 4 months ago
Clusterer ensemble
Ensemble methods that train multiple learners and then combine their predictions have been shown to be very effective in supervised learning. This paper explores ensemble methods ...
Zhi-Hua Zhou, Wei Tang