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AAAI
2010
13 years 9 months ago
Smooth Optimization for Effective Multiple Kernel Learning
Multiple Kernel Learning (MKL) can be formulated as a convex-concave minmax optimization problem, whose saddle point corresponds to the optimal solution to MKL. Most MKL methods e...
Zenglin Xu, Rong Jin, Shenghuo Zhu, Michael R. Lyu...
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
14 years 8 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang
IUI
2006
ACM
14 years 1 months ago
Are two talking heads better than one?: when should use more than one agent in e-learning?
Recent interest in the use of software character agents raises the issue of how many agents should be used in online learning. In this paper we review evidence concerning the rela...
Hua Wang, Mark H. Chignell, Mitsuru Ishizuka
ICML
2004
IEEE
14 years 8 months ago
Distribution kernels based on moments of counts
Many applications in text and speech processing require the analysis of distributions of variable-length sequences. We recently introduced a general kernel framework, rational ker...
Corinna Cortes, Mehryar Mohri
NIPS
2008
13 years 9 months ago
Multi-label Multiple Kernel Learning
We present a multi-label multiple kernel learning (MKL) formulation in which the data are embedded into a low-dimensional space directed by the instancelabel correlations encoded ...
Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye