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NIPS
2008
9 years 5 months ago
Theory of matching pursuit
We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound...
Zakria Hussain, John Shawe-Taylor
NIPS
2008
9 years 5 months ago
Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm
We study the convergence and the rate of convergence of a local manifold learning algorithm: LTSA [13]. The main technical tool is the perturbation analysis on the linear invarian...
Andrew Smith, Xiaoming Huo, Hongyuan Zha
NIPS
2008
9 years 5 months ago
Self-organization using synaptic plasticity
Large networks of spiking neurons show abrupt changes in their collective dynamics resembling phase transitions studied in statistical physics. An example of this phenomenon is th...
Vicenç Gómez, Andreas Kaltenbrunner,...
NIPS
2008
9 years 5 months ago
Deflation Methods for Sparse PCA
In analogy to the PCA setting, the sparse PCA problem is often solved by iteratively alternating between two subtasks: cardinality-constrained rank-one variance maximization and m...
Lester Mackey
NIPS
2008
9 years 5 months ago
Global Ranking Using Continuous Conditional Random Fields
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
NIPS
2008
9 years 5 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
NIPS
2008
9 years 5 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
9 years 5 months ago
Supervised Dictionary Learning
It is now well established that sparse signal models are well suited for restoration tasks and can be effectively learned from audio, image, and video data. Recent research has be...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
NIPS
2008
9 years 5 months ago
Near-minimax recursive density estimation on the binary hypercube
This paper describes a recursive estimation procedure for multivariate binary densities using orthogonal expansions. For d covariates, there are 2d basis coefficients to estimate,...
Maxim Raginsky, Svetlana Lazebnik, Rebecca Willett...
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