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ATAL
2007
Springer
14 years 4 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
PODS
2007
ACM
203views Database» more  PODS 2007»
14 years 10 months ago
Decision trees for entity identification: approximation algorithms and hardness results
We consider the problem of constructing decision trees for entity identification from a given relational table. The input is a table containing information about a set of entities...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Samb...
SIGECOM
2006
ACM
106views ECommerce» more  SIGECOM 2006»
14 years 4 months ago
Approximation algorithms and online mechanisms for item pricing
We present approximation and online algorithms for a number of problems of pricing items for sale so as to maximize seller’s revenue in an unlimited supply setting. Our first r...
Maria-Florina Balcan, Avrim Blum
APPROX
2005
Springer
136views Algorithms» more  APPROX 2005»
14 years 3 months ago
What About Wednesday? Approximation Algorithms for Multistage Stochastic Optimization
The field of stochastic optimization studies decision making under uncertainty, when only probabilistic information about the future is available. Finding approximate solutions to...
Anupam Gupta, Martin Pál, R. Ravi, Amitabh ...
KDD
2000
ACM
115views Data Mining» more  KDD 2000»
14 years 1 months ago
A framework for specifying explicit bias for revision of approximate information extraction rules
Information extraction is one of the most important techniques used in Text Mining. One of the main problems in building information extraction (IE) systems is that the knowledge ...
Ronen Feldman, Yair Liberzon, Binyamin Rosenfeld, ...