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» Predictive State Temporal Difference Learning
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ECAI
2004
Springer
15 years 2 months ago
A Backtracking Strategy for Order-Independent Incremental Learning
Agents that exist in an environment that changes over time, and are able to take into account the temporal nature of experience, are commonly called incremental learners. It is wid...
Nicola Di Mauro, Floriana Esposito, Stefano Ferill...
BC
2002
108views more  BC 2002»
14 years 9 months ago
Spike-timing-dependent plasticity: common themes and divergent vistas
Abstract. Recent experimental observations of spiketiming-dependent synaptic plasticity (STDP) have revitalized the study of synaptic learning rules. The most surprising aspect of ...
Ádám Kepecs, Mark C. W. van Rossum, ...
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 1 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
CVPR
2012
IEEE
12 years 12 months ago
Bridging the past, present and future: Modeling scene activities from event relationships and global rules
This paper addresses the discovery of activities and learns the underlying processes that govern their occurrences over time in complex surveillance scenes. To this end, we propos...
Jagannadan Varadarajan, Rémi Emonet, Jean-M...
BMCBI
2008
112views more  BMCBI 2008»
14 years 9 months ago
A simplified approach to disulfide connectivity prediction from protein sequences
Background: Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on differen...
Marc Vincent, Andrea Passerini, Matthieu Labb&eacu...