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KDD
2002
ACM
147views Data Mining» more  KDD 2002»
14 years 9 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny
ATAL
2007
Springer
14 years 3 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
MM
2005
ACM
171views Multimedia» more  MM 2005»
14 years 2 months ago
Semantic manifold learning for image retrieval
Learning the user’s semantics for CBIR involves two different sources of information: the similarity relations entailed by the content-based features, and the relevance relatio...
Yen-Yu Lin, Tyng-Luh Liu, Hwann-Tzong Chen
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 2 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
IUI
2004
ACM
14 years 2 months ago
Sheepdog: learning procedures for technical support
Technical support procedures are typically very complex. Users often have trouble following printed instructions describing how to perform these procedures, and these instructions...
Tessa A. Lau, Lawrence D. Bergman, Vittorio Castel...