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NIPS
2003
15 years 7 months 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»
14 years 10 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
14 years 6 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»
13 years 8 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»
16 years 6 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