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» Geometric constraint satisfaction using optimization methods
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AUTOMATICA
2005
108views more  AUTOMATICA 2005»
15 years 1 months ago
Enlarging the domain of attraction of MPC controllers
This paper presents a method for enlarging the domain of attraction of nonlinear model predictive control (MPC). The usual way of guaranteeing stability of nonlinear MPC is to add...
Daniel Limón, T. Alamo, Eduardo F. Camacho
JMLR
2008
137views more  JMLR 2008»
15 years 1 months ago
Online Learning of Complex Prediction Problems Using Simultaneous Projections
We describe and analyze an algorithmic framework for online classification where each online trial consists of multiple prediction tasks that are tied together. We tackle the prob...
Yonatan Amit, Shai Shalev-Shwartz, Yoram Singer
JMLR
2010
149views more  JMLR 2010»
14 years 8 months ago
Learning Bayesian Network Structure using LP Relaxations
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
ICCD
2007
IEEE
99views Hardware» more  ICCD 2007»
15 years 5 months ago
Power reduction of chip multi-processors using shared resource control cooperating with DVFS
This paper presents a novel power reduction method for chip multi-processors (CMPs) under real-time constraints. While the power consumption of processing units (PUs) on CMPs can ...
Ryo Watanabe, Masaaki Kondo, Hiroshi Nakamura, Tak...
ICML
2004
IEEE
15 years 6 months ago
Learning a kernel matrix for nonlinear dimensionality reduction
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Kilian Q. Weinberger, Fei Sha, Lawrence K. Saul