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JMLR
2010
103views more  JMLR 2010»
13 years 3 months ago
Learning Nonlinear Dynamic Models from Non-sequenced Data
Virtually all methods of learning dynamic systems from data start from the same basic assumption: the learning algorithm will be given a sequence of data generated from the dynami...
Tzu-Kuo Huang, Le Song, Jeff Schneider
UAI
2008
13 years 10 months ago
Convergent Message-Passing Algorithms for Inference over General Graphs with Convex Free Energies
Inference problems in graphical models can be represented as a constrained optimization of a free energy function. It is known that when the Bethe free energy is used, the fixedpo...
Tamir Hazan, Amnon Shashua
PG
2003
IEEE
14 years 2 months ago
Bounding Recursive Procedural Models Using Convex Optimization
We present an algorithm to construct a tight bounding polyhedron for a recursive procedural model. We first use an iterated function system (IFS) to represent the extent of the p...
Orion Sky Lawlor, John C. Hart
ALT
2004
Springer
14 years 5 months ago
Convergence of a Generalized Gradient Selection Approach for the Decomposition Method
The decomposition method is currently one of the major methods for solving the convex quadratic optimization problems being associated with support vector machines. For a special c...
Nikolas List
EOR
2002
87views more  EOR 2002»
13 years 8 months ago
On the finite convergence of successive SDP relaxation methods
Let F be a subset of the n-dimensional Euclidean space Rn represented in terms of a compact convex subset C0 and a set PF of nitely or in nitely many quadratic functions on Rn such...
Masakazu Kojima, Levent Tunçel