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109
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ECML
2005
Springer
15 years 7 months ago
2005
Springer
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
127
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ICML
1994
IEEE
15 years 5 months ago
1994
IEEE
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function....
125
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ICML
2006
IEEE
16 years 3 months ago
2006
IEEE
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
111
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ICML
2004
IEEE
16 years 3 months ago
2004
IEEE
This paper addresses the problem of finding a small and coherent subset of points in a given data. This problem, sometimes referred to as one-class or set covering, requires to fi...
ECML
2001
Springer
15 years 6 months ago
2001
Springer
When correct priors are known, Bayesian algorithms give optimal decisions, and accurate confidence values for predictions can be obtained. If the prior is incorrect however, these...