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ML
2007
ACM
192views Machine Learning» more  ML 2007»
15 years 4 months ago
Annealing stochastic approximation Monte Carlo algorithm for neural network training
We propose a general-purpose stochastic optimization algorithm, the so-called annealing stochastic approximation Monte Carlo (ASAMC) algorithm, for neural network training. ASAMC c...
Faming Liang
STOC
2009
ACM
123views Algorithms» more  STOC 2009»
16 years 5 months ago
An improved constant-time approximation algorithm for maximum~matchings
This paper studies constant-time approximation algorithms for problems on degree-bounded graphs. Let n and d be the number of vertices and the degree bound, respectively. This pap...
Yuichi Yoshida, Masaki Yamamoto, Hiro Ito
STACS
2010
Springer
16 years 12 hour ago
The Complexity of Approximating Bounded-Degree Boolean #CSP
The degree of a CSP instance is the maximum number of times that a variable may appear in the scope of constraints. We consider the approximate counting problem for Boolean CSPs wi...
Martin E. Dyer, Leslie Ann Goldberg, Markus Jalsen...
FOCS
2008
IEEE
15 years 11 months ago
Submodular Approximation: Sampling-based Algorithms and Lower Bounds
We introduce several generalizations of classical computer science problems obtained by replacing simpler objective functions with general submodular functions. The new problems i...
Zoya Svitkina, Lisa Fleischer
149
Voted
SECON
2007
IEEE
15 years 11 months ago
Approximation Algorithm for Base Station Placement in Wireless Sensor Networks
Base station location has significant impact on network lifetime performance for a sensor network. For a multihop sensor network, this problem is particular challenging as we need ...
Yi Shi, Yiwei Thomas Hou