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ICML
2010
IEEE
14 years 10 months ago
Learning Efficiently with Approximate Inference via Dual Losses
Many structured prediction tasks involve complex models where inference is computationally intractable, but where it can be well approximated using a linear programming relaxation...
Ofer Meshi, David Sontag, Tommi Jaakkola, Amir Glo...
COMPGEOM
1996
ACM
15 years 1 months ago
Developing a Practical Projection-Based Parallel Delaunay Algorithm
In this paper we are concerned with developing a practical parallel algorithm for Delaunay triangulation that works well on general distributions, particularly those that arise in...
Guy E. Blelloch, Gary L. Miller, Dafna Talmor
WDAG
2007
Springer
85views Algorithms» more  WDAG 2007»
15 years 3 months ago
Fully Distributed Algorithms for Convex Optimization Problems
Damon Mosk-Aoyama, Tim Roughgarden, Devavrat Shah
80
Voted
PAMI
2008
162views more  PAMI 2008»
14 years 9 months ago
Bayes Optimality in Linear Discriminant Analysis
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
Onur C. Hamsici, Aleix M. Martínez
SIAMJO
2008
212views more  SIAMJO 2008»
14 years 9 months ago
Convergence Rate of an Optimization Algorithm for Minimizing Quadratic Functions with Separable Convex Constraints
A new active set algorithm for minimizing quadratic functions with separable convex constraints is proposed by combining the conjugate gradient method with the projected gradient. ...
Radek Kucera