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AAAI
2006
13 years 10 months ago
Action Selection in Bayesian Reinforcement Learning
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Tao Wang
EENERGY
2010
14 years 1 months ago
Towards energy-aware scheduling in data centers using machine learning
As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to find better an...
Josep Lluis Berral, Iñigo Goiri, Ramon Nou,...
ICCS
1993
Springer
14 years 1 months ago
Towards Domain-Independent Machine Intelligence
Adaptive predictive search (APS), is a learning system framework, which given little initial domain knowledge, increases its decision-making abilities in complex problems domains....
Robert Levinson
WSDM
2012
ACM
301views Data Mining» more  WSDM 2012»
12 years 4 months ago
Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization
As massive repositories of real-time human commentary, social media platforms have arguably evolved far beyond passive facilitation of online social interactions. Rapid analysis o...
Ankan Saha, Vikas Sindhwani
ICCBR
2010
Springer
14 years 1 months ago
Imitating Inscrutable Enemies: Learning from Stochastic Policy Observation, Retrieval and Reuse
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...