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» On the Convergence of Bound Optimization Algorithms
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EUROCOLT
1999
Springer
13 years 12 months ago
Regularized Principal Manifolds
Many settings of unsupervised learning can be viewed as quantization problems — the minimization of the expected quantization error subject to some restrictions. This allows the ...
Alex J. Smola, Robert C. Williamson, Sebastian Mik...
JOTA
2011
149views more  JOTA 2011»
13 years 2 months ago
Globally Convergent Cutting Plane Method for Nonconvex Nonsmooth Minimization
: Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms d...
Napsu Karmitsa, Mario Tanaka Filho, José He...
UAI
2004
13 years 9 months ago
Discretized Approximations for POMDP with Average Cost
In this paper, we propose a new lower approximation scheme for POMDP with discounted and average cost criterion. The approximating functions are determined by their values at a fi...
Huizhen Yu, Dimitri P. Bertsekas
JMLR
2010
143views more  JMLR 2010»
13 years 6 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, ...
ATAL
2009
Springer
14 years 2 months ago
A distributed constraint optimization approach for coordination under uncertainty
Distributed Constraint Optimization (DCOP) provides a rich framework for modeling multi-agent coordination problems. Existing problem domains for DCOP focus on small (<100 vari...
James Atlas