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» Hedging predictions in machine learning
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AAMAS
2011
Springer
14 years 11 months ago
Using focal point learning to improve human-machine tacit coordination
We consider an automated agent that needs to coordinate with a human partner when communication between them is not possible or is undesirable (tacit coordination games). Specifi...
Inon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschei...
ICML
1999
IEEE
16 years 5 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
MLDM
2005
Springer
15 years 10 months ago
Using Clustering to Learn Distance Functions for Supervised Similarity Assessment
Assessing the similarity between objects is a prerequisite for many data mining techniques. This paper introduces a novel approach to learn distance functions that maximizes the c...
Christoph F. Eick, Alain Rouhana, Abraham Bagherje...
BMCBI
2004
140views more  BMCBI 2004»
15 years 4 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard
CDC
2010
IEEE
196views Control Systems» more  CDC 2010»
14 years 11 months ago
Convergence and convergence rate of stochastic gradient search in the case of multiple and non-isolated extrema
The asymptotic behavior of stochastic gradient algorithms is studied. Relying on some results of differential geometry (Lojasiewicz gradient inequality), the almost sure pointconve...
Vladislav B. Tadic