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NIPS
2007
15 years 5 months ago
Convex Learning with Invariances
Incorporating invariances into a learning algorithm is a common problem in machine learning. We provide a convex formulation which can deal with arbitrary loss functions and arbit...
Choon Hui Teo, Amir Globerson, Sam T. Roweis, Alex...
ICRA
2002
IEEE
115views Robotics» more  ICRA 2002»
15 years 9 months ago
DEEP: Dual-Space Expansion for Estimating Penetration Depth Between Convex Polytopes
Abstract— We present an incremental algorithm to estimate the penetration depth between convex polytopes in 3D. The algorithm incrementally seeks a “locally optimal solution”...
Young J. Kim, Ming C. Lin, Dinesh Manocha
CDC
2009
IEEE
117views Control Systems» more  CDC 2009»
15 years 9 months ago
Risk sensitive robust support vector machines
— We propose a new family of classification algorithms in the spirit of support vector machines, that builds in non-conservative protection to noise and controls overfitting. O...
Huan Xu, Constantine Caramanis, Shie Mannor, Sungh...
CVPR
2008
IEEE
16 years 6 months ago
Enforcing convexity for improved alignment with constrained local models
Constrained local models (CLMs) have recently demonstrated good performance in non-rigid object alignment/tracking in comparison to leading holistic approaches (e.g., AAMs). A maj...
Yang Wang, Simon Lucey, Jeffrey F. Cohn
CCE
2004
15 years 4 months ago
Computational studies using a novel simplicial-approximation based algorithm for MINLP optimization
Significant advances have been made in the last two decades for the effective solution of mixed integer non-linear programming (MINLP) problems, mainly by exploiting the special s...
Vishal Goyal, Marianthi G. Ierapetritou