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» Smooth Optimization for Effective Multiple Kernel Learning
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ICML
2010
IEEE
14 years 10 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang
94
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ICML
2009
IEEE
15 years 10 months ago
Semi-supervised learning using label mean
Semi-Supervised Support Vector Machines (S3VMs) typically directly estimate the label assignments for the unlabeled instances. This is often inefficient even with recent advances ...
Yu-Feng Li, James T. Kwok, Zhi-Hua Zhou
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
15 years 10 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin
EMNLP
2008
14 years 11 months ago
Selecting Sentences for Answering Complex Questions
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
Yllias Chali, Shafiq R. Joty
ICML
2004
IEEE
15 years 10 months ago
Support vector machine learning for interdependent and structured output spaces
Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...