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» Universal Sparse Modeling
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107
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ICANN
2005
Springer
15 years 6 months ago
Smooth Bayesian Kernel Machines
Abstract. In this paper, we consider the possibility of obtaining a kernel machine that is sparse in feature space and smooth in output space. Smooth in output space implies that t...
Rutger W. ter Borg, Léon J. M. Rothkrantz
76
Voted
EMNLP
2007
15 years 2 months ago
Online Large-Margin Training for Statistical Machine Translation
We achieved a state of the art performance in statistical machine translation by using a large number of features with an online large-margin training algorithm. The millions of p...
Taro Watanabe, Jun Suzuki, Hajime Tsukada, Hideki ...
125
Voted
STOC
2009
ACM
144views Algorithms» more  STOC 2009»
16 years 1 months ago
Homology flows, cohomology cuts
We describe the first algorithm to compute maximum flows in surface-embedded graphs in near-linear time. Specifically, given a graph embedded on a surface of genus g, with two spe...
Erin W. Chambers, Jeff Erickson, Amir Nayyeri
135
Voted
IEEEICCI
2009
IEEE
15 years 7 months ago
Interval sets and interval-set algebras
An interval set is an interval in the power set lattice based on a universal set and is a family of subsets of the universal set. Interval sets and interval-set algebras provide a...
Yiyu Yao
ISMIS
2003
Springer
15 years 6 months ago
Granular Computing Based on Rough Sets, Quotient Space Theory, and Belief Functions
Abstract. A model of granular computing (GrC) is proposed by reformulating, re-interpreting, and combining results from rough sets, quotient space theory, and belief functions. Two...
Y. Y. Yao, Churn-Jung Liau, Ning Zhong