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123
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ML
2000
ACM
126views Machine Learning» more  ML 2000»
15 years 4 months ago
Learning to Play Chess Using Temporal Differences
In this paper we present TDLEAF( ), a variation on the TD( ) algorithm that enables it to be used in conjunction with game-tree search. We present some experiments in which our che...
Jonathan Baxter, Andrew Tridgell, Lex Weaver
139
Voted
AIEDAM
1998
87views more  AIEDAM 1998»
15 years 4 months ago
Learning to set up numerical optimizations of engineering designs
Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the object...
Mark Schwabacher, Thomas Ellman, Haym Hirsh
193
Voted
ICTAI
2010
IEEE
15 years 1 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
172
Voted
CORR
2011
Springer
183views Education» more  CORR 2011»
14 years 11 months ago
Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning
— We address the sparse signal recovery problem in the context of multiple measurement vectors (MMV) when elements in each nonzero row of the solution matrix are temporally corre...
Zhilin Zhang, Bhaskar D. Rao
CSFW
2011
IEEE
14 years 4 months ago
Regret Minimizing Audits: A Learning-Theoretic Basis for Privacy Protection
Abstract—Audit mechanisms are essential for privacy protection in permissive access control regimes, such as in hospitals where denying legitimate access requests can adversely a...
Jeremiah Blocki, Nicolas Christin, Anupam Datta, A...