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» On Computing Functions with Uncertainty
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179
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NIPS
2008
15 years 8 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
160
Voted
IPCO
2007
77views Optimization» more  IPCO 2007»
15 years 8 months ago
Mixed-Integer Vertex Covers on Bipartite Graphs
Let A be the edge-node incidence matrix of a bipartite graph G = (U, V ; E), I be a subset the nodes of G, and b be a vector such that 2b is integral. We consider the following mi...
Michele Conforti, Bert Gerards, Giacomo Zambelli
NIPS
2008
15 years 8 months ago
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
For supervised and unsupervised learning, positive definite kernels allow to use large and potentially infinite dimensional feature spaces with a computational cost that only depe...
Francis Bach
182
Voted
NIPS
2008
15 years 8 months ago
An Extended Level Method for Efficient Multiple Kernel Learning
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
Zenglin Xu, Rong Jin, Irwin King, Michael R. Lyu
NIPS
2008
15 years 8 months ago
Stochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models (SRMs) [15] provide a rich family of choices for learning and predicting dyadic data between two sets of entities. The models generalize matrix factor...
Shenghuo Zhu, Kai Yu, Yihong Gong
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