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» On the Convergence of Bound Optimization Algorithms
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ISAAC
2003
Springer
129views Algorithms» more  ISAAC 2003»
15 years 11 months ago
Polynomial Time Approximate Sampler for Discretized Dirichlet Distribution
Abstract. In this paper, we propose a Markov chain for sampling a random vector distributed according to a discretized Dirichlet distribution. We show that our Markov chain is rapi...
Tomomi Matsui, Mitsuo Motoki, Naoyuki Kamatani
ICCV
2005
IEEE
16 years 8 months ago
A New Framework for Approximate Labeling via Graph Cuts
A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification ...
Nikos Komodakis, Georgios Tziritas
COCOA
2007
Springer
16 years 24 days ago
A Lagrangian Relaxation Approach for the Multiple Sequence Alignment Problem
Abstract. We present a branch-and-bound (bb) algorithm for the multiple sequence alignment problem (MSA), one of the most important problems in computational biology. The upper bou...
Ernst Althaus, Stefan Canzar
CORR
2011
Springer
205views Education» more  CORR 2011»
14 years 10 months ago
Parallel Coordinate Descent for L1-Regularized Loss Minimization
We propose Shotgun, a parallel coordinate descent algorithm for minimizing L1regularized losses. Though coordinate descent seems inherently sequential, we prove convergence bounds...
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Car...
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
16 years 24 days ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya