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LION
2007
Springer
192views Optimization» more  LION 2007»
15 years 3 months ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto
CORR
2011
Springer
157views Education» more  CORR 2011»
14 years 1 months ago
Large-Scale Convex Minimization with a Low-Rank Constraint
We address the problem of minimizing a convex function over the space of large matrices with low rank. While this optimization problem is hard in general, we propose an efficient...
Shai Shalev-Shwartz, Alon Gonen, Ohad Shamir
ATAL
2004
Springer
15 years 3 months ago
A Study of Limited-Precision, Incremental Elicitation in Auctions
We investigate the design of iterative, limited-precision mechanisms for single-good auctions with dominant strategy equilibria. Our aim is to design mechanisms that minimize the ...
Alexander Kress, Craig Boutilier
PERCOM
2007
ACM
15 years 9 months ago
Sensor Scheduling for Optimal Observability Using Estimation Entropy
We consider sensor scheduling as the optimal observability problem for partially observable Markov decision processes (POMDP). This model fits to the cases where a Markov process ...
Mohammad Rezaeian
SIAMJO
2010
246views more  SIAMJO 2010»
14 years 8 months ago
A Singular Value Thresholding Algorithm for Matrix Completion
This paper introduces a novel algorithm to approximate the matrix with minimum nuclear norm among all matrices obeying a set of convex constraints. This problem may be understood a...
Jian-Feng Cai, Emmanuel J. Candès, Zuowei S...