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MP
2006
137views more  MP 2006»
13 years 7 months ago
New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
Yu-Hong Dai, Roger Fletcher
JMLR
2012
11 years 10 months ago
Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation
This paper considers additive factorial hidden Markov models, an extension to HMMs where the state factors into multiple independent chains, and the output is an additive function...
J. Zico Kolter, Tommi Jaakkola
EURODAC
1994
IEEE
186views VHDL» more  EURODAC 1994»
13 years 11 months ago
Algorithms for a switch module routing problem
We consider a switch module routing problem for symmetric array FPGAs. The work is motivated by two applications. The rst is that of eciently evaluating switch module designs [8]...
Shashidhar Thakur, D. F. Wong, S. Muthukrishnan
ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 7 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
SIAMJO
2011
13 years 2 months ago
A Unifying Polyhedral Approximation Framework for Convex Optimization
Abstract. We propose a unifying framework for polyhedral approximation in convex optimization. It subsumes classical methods, such as cutting plane and simplicial decomposition, bu...
Dimitri P. Bertsekas, Huizhen Yu