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» Approximation Methods for Supervised Learning
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124
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ML
2010
ACM
141views Machine Learning» more  ML 2010»
14 years 11 months ago
Relational retrieval using a combination of path-constrained random walks
Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad hoc retrieval o...
Ni Lao, William W. Cohen
SIGUCCS
2003
ACM
15 years 5 months ago
Teamwork is the heart of technology
IAT Services, the central Information Technology group at the University of Missouri-Columbia, operates computing sites in general access, classroom, and residence hall settings. ...
Tammy Hohlt, Kristina A. Cunningham
AAAI
2012
13 years 3 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
85
Voted
UAI
2008
15 years 2 months ago
Learning and Solving Many-Player Games through a Cluster-Based Representation
In addressing the challenge of exponential scaling with the number of agents we adopt a cluster-based representation to approximately solve asymmetric games of very many players. ...
Sevan G. Ficici, David C. Parkes, Avi Pfeffer
87
Voted
DGO
2008
126views Education» more  DGO 2008»
15 years 2 months ago
Active learning for e-rulemaking: public comment categorization
We address the e-rulemaking problem of reducing the manual labor required to analyze public comment sets. In current and previous work, for example, text categorization techniques...
Stephen Purpura, Claire Cardie, Jesse Simons