82 search results - page 2 / 17 » Balancing Exploration and Exploitation in Learning to Rank O... |
89
Voted
GECCO
2006
Springer
15 years 1 months ago
2006
Springer
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...
126
Voted
PKDD
2010
Springer
14 years 8 months ago
2010
Springer
Abstract. We present an implementation of model-based online reinforcement learning (RL) for continuous domains with deterministic transitions that is specifically designed to achi...
74
Voted
ICML
2005
IEEE
15 years 11 months ago
2005
IEEE
Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Inter...
105
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EMNLP
2009
14 years 8 months ago
2009
There have been increasing needs for task specific rankings in web search such as rankings for specific query segments like long queries, time-sensitive queries, navigational quer...
152
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CVPR
2012
IEEE
13 years 3 months ago
2012
IEEE
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...