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ICML
2002
IEEE
14 years 10 months ago
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs
One of the central challenges in reinforcement learning is to balance the exploration/exploitation tradeoff while scaling up to large problems. Although model-based reinforcement ...
Carlos Guestrin, Relu Patrascu, Dale Schuurmans
AAAI
2010
13 years 10 months ago
To Max or Not to Max: Online Learning for Speeding Up Optimal Planning
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...
Carmel Domshlak, Erez Karpas, Shaul Markovitch
MM
2010
ACM
137views Multimedia» more  MM 2010»
13 years 9 months ago
Self-diagnostic peer-assisted video streaming through a learning framework
Quality control and resource optimization are challenging problems in peer-assisted video streaming systems, due to their large scales and unreliable peer behavior. Such systems a...
Di Niu, Baochun Li, Shuqiao Zhao
ICMLA
2010
13 years 7 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
CVPR
2001
IEEE
14 years 11 months ago
Bayesian Learning of Sparse Classifiers
Bayesian approaches to supervised learning use priors on the classifier parameters. However, few priors aim at achieving "sparse" classifiers, where irrelevant/redundant...
Anil K. Jain, Mário A. T. Figueiredo