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MOR
2007
149views more  MOR 2007»
14 years 9 months ago
LP Rounding Approximation Algorithms for Stochastic Network Design
Real-world networks often need to be designed under uncertainty, with only partial information and predictions of demand available at the outset of the design process. The field ...
Anupam Gupta, R. Ravi, Amitabh Sinha
ANNPR
2006
Springer
15 years 1 months ago
Simple and Effective Connectionist Nonparametric Estimation of Probability Density Functions
Abstract. Estimation of probability density functions (pdf) is one major topic in pattern recognition. Parametric techniques rely on an arbitrary assumption on the form of the unde...
Edmondo Trentin
SIGMOD
1998
ACM
121views Database» more  SIGMOD 1998»
15 years 1 months ago
New Sampling-Based Summary Statistics for Improving Approximate Query Answers
In large data recording and warehousing environments, it is often advantageous to provide fast, approximate answers to queries, whenever possible. Before DBMSs providing highly-ac...
Phillip B. Gibbons, Yossi Matias
ICCV
2011
IEEE
13 years 9 months ago
Distributed Cosegmentation via Submodular Optimization on Anisotropic Diffusion
The saliency of regions or objects in an image can be significantly boosted if they recur in multiple images. Leveraging this idea, cosegmentation jointly segments common regions...
Gunhee Kim, Eric P. Xing, Li Fei-Fei, Takeo Kanade
APPROX
2009
Springer
138views Algorithms» more  APPROX 2009»
15 years 4 months ago
Submodular Maximization over Multiple Matroids via Generalized Exchange Properties
Submodular-function maximization is a central problem in combinatorial optimization, generalizing many important NP-hard problems including Max Cut in digraphs, graphs and hypergr...
Jon Lee, Maxim Sviridenko, Jan Vondrák