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ML
2007
ACM
104views Machine Learning» more  ML 2007»
15 years 6 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
EMNLP
2006
15 years 8 months ago
Phrasetable Smoothing for Statistical Machine Translation
We discuss different strategies for smoothing the phrasetable in Statistical MT, and give results over a range of translation settings. We show that any type of smoothing is a bet...
George F. Foster, Roland Kuhn, Howard Johnson
220
Voted
CSDA
2004
105views more  CSDA 2004»
15 years 7 months ago
Computational aspects of algorithms for variable selection in the context of principal components
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
Jorge Cadima, J. Orestes Cerdeira, Manuel Minhoto
SIAMJO
2000
88views more  SIAMJO 2000»
15 years 6 months ago
A Feasible BFGS Interior Point Algorithm for Solving Convex Minimization Problems
Abstract. We propose a BFGS primal-dual interior point method for minimizing a convex function on a convex set defined by equality and inequality constraints. The algorithm generat...
Paul Armand, Jean Charles Gilbert, Sophie Jan-J&ea...
ICPR
2008
IEEE
16 years 8 months ago
A discrete-time parallel update algorithm for distributed learning
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
Christian Bauckhage, Tansu Alpcan