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NIPS
2003
14 years 11 days ago
Max-Margin Markov Networks
In typical classification tasks, we seek a function which assigns a label to a single object. Kernel-based approaches, such as support vector machines (SVMs), which maximize the ...
Benjamin Taskar, Carlos Guestrin, Daphne Koller
ICDE
2011
IEEE
245views Database» more  ICDE 2011»
13 years 2 months ago
Stochastic skyline operator
— In many applications involving the multiple criteria optimal decision making, users may often want to make a personal trade-off among all optimal solutions. As a key feature, t...
Xuemin Lin, Ying Zhang, Wenjie Zhang, Muhammad Aam...
EMSOFT
2011
Springer
12 years 10 months ago
From boolean to quantitative synthesis
Motivated by improvements in constraint-solving technology and by the increase of routinely available computational power, partial-program synthesis is emerging as an effective a...
Pavol Cerný, Thomas A. Henzinger
TKDE
2012
192views Formal Methods» more  TKDE 2012»
12 years 1 months ago
Discriminative Feature Selection by Nonparametric Bayes Error Minimization
Feature selection is fundamental to knowledge discovery from massive amount of high-dimensional data. In an effort to establish theoretical justification for feature selection al...
Shuang-Hong Yang, Bao-Gang Hu
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 11 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson