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TOMACS
2010
79views more  TOMACS 2010»
14 years 4 months ago
A stochastic approximation method with max-norm projections and its applications to the Q-learning algorithm
In this paper, we develop a stochastic approximation method to solve a monotone estimation problem and use this method to enhance the empirical performance of the Q-learning algor...
Sumit Kunnumkal, Huseyin Topaloglu
NIPS
2007
14 years 11 months ago
Local Algorithms for Approximate Inference in Minor-Excluded Graphs
We present a new local approximation algorithm for computing MAP and logpartition function for arbitrary exponential family distribution represented by a finite-valued pair-wise ...
Kyomin Jung, Devavrat Shah
CIKM
2010
Springer
14 years 8 months ago
Decomposing background topics from keywords by principal component pursuit
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
Kerui Min, Zhengdong Zhang, John Wright, Yi Ma
ICCAD
2006
IEEE
152views Hardware» more  ICCAD 2006»
15 years 6 months ago
System-wide energy minimization for real-time tasks: lower bound and approximation
We present a dynamic voltage scaling (DVS) technique that minimizes system-wide energy consumption for both periodic and sporadic tasks. It is known that a system consists of proc...
Xiliang Zhong, Cheng-Zhong Xu
JMLR
2012
13 years 9 days 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