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COLING
2010
13 years 2 months ago
Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints
In opinion mining of product reviews, one often wants to produce a summary of opinions based on product features/attributes. However, for the same feature, people can express it w...
Zhongwu Zhai, Bing Liu, Hua Xu, Peifa Jia
CORR
2010
Springer
105views Education» more  CORR 2010»
13 years 6 months ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
AIR
2004
111views more  AIR 2004»
13 years 7 months ago
Towards Fast Vickrey Pricing using Constraint Programming
Ensuring truthfulness amongst self-interested agents bidding against one another in an auction can be computationally expensive when prices are determined using the Vickrey-Clarke-...
Alan Holland, Barry O'Sullivan
CP
1998
Springer
13 years 11 months ago
Optimizing with Constraints: A Case Study in Scheduling Maintenance of Electric Power Units
A well-studied problem in the electric power industry is that of optimally scheduling preventative maintenance of power generating units within a power plant. We show how these pr...
Daniel Frost, Rina Dechter
ICCBR
1999
Springer
13 years 11 months ago
When Experience Is Wrong: Examining CBR for Changing Tasks and Environments
Case-based problem-solving systems reason and learn from experiences, building up case libraries of problems and solutions to guide future reasoning. The expected bene ts of this l...
David B. Leake, David C. Wilson