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» Generalizing over Several Learning Settings
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ECML
2004
Springer
14 years 1 months ago
Batch Reinforcement Learning with State Importance
Abstract. We investigate the problem of using function approximation in reinforcement learning where the agent’s policy is represented as a classifier mapping states to actions....
Lihong Li, Vadim Bulitko, Russell Greiner
ML
2010
ACM
119views Machine Learning» more  ML 2010»
13 years 6 months ago
A cooperative coevolutionary algorithm for instance selection for instance-based learning
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
Nicolás García-Pedrajas, Juan Antoni...
MM
2009
ACM
209views Multimedia» more  MM 2009»
14 years 2 months ago
Brain state decoding for rapid image retrieval
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...
JAIR
2006
102views more  JAIR 2006»
13 years 7 months ago
Multiple-Goal Heuristic Search
This paper presents a new framework for anytime heuristic search where the task is to achieve as many goals as possible within the allocated resources. We show the inadequacy of t...
Dmitry Davidov, Shaul Markovitch
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 10 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham