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» Superset Learning Based on Generalized Loss Minimization
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IJCNN
2000
IEEE
15 years 2 months ago
Continuous Optimization of Hyper-Parameters
Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
Yoshua Bengio
SIAMCOMP
2000
109views more  SIAMCOMP 2000»
14 years 9 months ago
Dual-Bounded Generating Problems: Partial and Multiple Transversals of a Hypergraph
Abstract. We consider two natural generalizations of the notion of transversal to a finite hypergraph, arising in data-mining and machine learning, the so called multiple and parti...
Endre Boros, Vladimir Gurvich, Leonid Khachiyan, K...
ML
2002
ACM
167views Machine Learning» more  ML 2002»
14 years 9 months ago
Linear Programming Boosting via Column Generation
We examine linear program (LP) approaches to boosting and demonstrate their efficient solution using LPBoost, a column generation based simplex method. We formulate the problem as...
Ayhan Demiriz, Kristin P. Bennett, John Shawe-Tayl...
NIPS
1998
14 years 11 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
CIKM
2008
Springer
15 years 4 hour ago
AdaSum: an adaptive model for summarization
Topic representation mismatch is a key problem in topic-oriented summarization for the specified topic is usually too short to understand/interpret. This paper proposes a novel ad...
Jin Zhang, Xueqi Cheng, Gaowei Wu, Hongbo Xu