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SIAMJO
2008
66views more  SIAMJO 2008»
15 years 6 months ago
Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization
Recently, a semidefinite programming (SDP) relaxation approach has been proposed to solve the sensor network localization problem. Although it achieves high accuracy in estimating ...
Zizhuo Wang, Song Zheng, Yinyu Ye, Stephen Boyd
SIAMSC
2008
147views more  SIAMSC 2008»
15 years 6 months ago
Global and Finite Termination of a Two-Phase Augmented Lagrangian Filter Method for General Quadratic Programs
We present a two-phase algorithm for solving large-scale quadratic programs (QPs). In the first phase, gradient-projection iterations approximately minimize an augmented Lagrangian...
Michael P. Friedlander, Sven Leyffer
JMLR
2010
129views more  JMLR 2010»
15 years 26 days ago
Learning Polyhedral Classifiers Using Logistic Function
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Naresh Manwani, P. S. Sastry

Publication
240views
14 years 4 months ago
Bayesian multitask inverse reinforcement learning
We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or ...
Christos Dimitrakakis, Constantin A. Rothkopf
ICCV
2003
IEEE
16 years 8 months ago
Multiclass Spectral Clustering
We propose a principled account on multiclass spectral clustering. Given a discrete clustering formulation, we first solve a relaxed continuous optimization problem by eigendecomp...
Stella X. Yu, Jianbo Shi