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ICML
2005
IEEE
16 years 5 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
140
Voted
ICDM
2005
IEEE
163views Data Mining» more  ICDM 2005»
15 years 9 months ago
Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning
Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert)...
Thomas Takeo Osugi, Kun Deng, Stephen D. Scott
LOCA
2009
Springer
15 years 8 months ago
Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning
Abstract. Activity recognition has attracted increasing attention in recent years due to its potential to enable a number of compelling contextaware applications. As most approache...
Maja Stikic, Bernt Schiele
AGP
1997
IEEE
15 years 8 months ago
An Algorithm for Learning Abductive Rules
We propose an algorithm for learning abductive logic programs from examples. We consider the Abductive Concept Learning framework, an extension of the Inductive Logic Programming ...
Evelina Lamma, Paola Mello, Michela Milano, Fabriz...
ECML
2006
Springer
15 years 7 months ago
Scaling Model-Based Average-Reward Reinforcement Learning for Product Delivery
Reinforcement learning in real-world domains suffers from three curses of dimensionality: explosions in state and action spaces, and high stochasticity. We present approaches that ...
Scott Proper, Prasad Tadepalli