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CDC
2008
IEEE
124views Control Systems» more  CDC 2008»
15 years 4 months ago
A proximal center-based decomposition method for multi-agent convex optimization
— In this paper we develop a new dual decomposition method for optimizing a sum of convex objective functions corresponding to multiple agents but with coupled constraints. In ou...
Ion Necoara, Johan A. K. Suykens
JMLR
2010
143views more  JMLR 2010»
14 years 8 months ago
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Jin Yu, S. V. N. Vishwanathan, Simon Günter, ...
CAV
2000
Springer
187views Hardware» more  CAV 2000»
15 years 1 months ago
Combining Decision Diagrams and SAT Procedures for Efficient Symbolic Model Checking
In this paper we show how to do symbolic model checking using Boolean Expression Diagrams (BEDs), a non-canonical representation for Boolean formulas, instead of Binary Decision Di...
Poul Frederick Williams, Armin Biere, Edmund M. Cl...
SIMPRA
2008
125views more  SIMPRA 2008»
14 years 9 months ago
Identification of Wiener models using optimal local linear models
The Wiener model is a versatile nonlinear block oriented model structure for miscellaneous applications. In this paper a method for identifying the parameters of such a model usin...
Martin Kozek, Sabina Sinanovic
CDC
2010
IEEE
112views Control Systems» more  CDC 2010»
14 years 4 months ago
Online Convex Programming and regularization in adaptive control
Online Convex Programming (OCP) is a recently developed model of sequential decision-making in the presence of time-varying uncertainty. In this framework, a decisionmaker selects ...
Maxim Raginsky, Alexander Rakhlin, Serdar Yük...