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» The Localization Hypothesis and Machines
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ICML
2003
IEEE
16 years 1 months ago
Q-Decomposition for Reinforcement Learning Agents
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...
Stuart J. Russell, Andrew Zimdars
103
Voted
MICRO
1996
IEEE
96views Hardware» more  MICRO 1996»
15 years 5 months ago
Exceeding the Dataflow Limit via Value Prediction
For decades, the serialization constraints imposed by true data dependences have been regarded as an absolute limit--the dataflow limit--on the parallel execution of serial progra...
Mikko H. Lipasti, John Paul Shen
ICML
2004
IEEE
16 years 1 months ago
Boosting margin based distance functions for clustering
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
75
Voted
ALT
2007
Springer
15 years 9 months ago
Prescribed Learning of R.E. Classes
Abstract. This work extends studies of Angluin, Lange and Zeugmann on the dependence of learning on the hypotheses space chosen for the class. In subsequent investigations, uniform...
Sanjay Jain, Frank Stephan, Nan Ye
MLDM
2005
Springer
15 years 6 months ago
Multivariate Discretization by Recursive Supervised Bipartition of Graph
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
Sylvain Ferrandiz, Marc Boullé