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ML
2007
ACM
104views Machine Learning» more  ML 2007»
13 years 8 months ago
A general criterion and an algorithmic framework for learning in multi-agent systems
We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also...
Rob Powers, Yoav Shoham, Thuc Vu
KDD
2002
ACM
164views Data Mining» more  KDD 2002»
14 years 9 months ago
Meta-classification: Combining Multimodal Classifiers
Combining multiple classifiers is of particular interest in multimedia applications. Each modality in multimedia data can be analyzed individually, and combining multiple pieces of...
Wei-Hao Lin, Alexander G. Hauptmann
BIBM
2008
IEEE
217views Bioinformatics» more  BIBM 2008»
14 years 3 months ago
Combining Hierarchical Inference in Ontologies with Heterogeneous Data Sources Improves Gene Function Prediction
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...
ATAL
2010
Springer
13 years 10 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone
SCOPES
2004
Springer
14 years 2 months ago
Combined Data Partitioning and Loop Nest Splitting for Energy Consumption Minimization
For mobile embedded systems, the energy consumption is a limiting factor because of today’s battery capacities. Besides the processor, memory accesses consume a high amount of en...
Heiko Falk, Manish Verma