Showing 2013 · cs.LGShow all

8 papers · 2 filters

cs.LG2013★ 25 cited

Online Bayesian Passive-Aggressive Learning

Tianlin Shi, Jun Zhu

Online Passive-Aggressive (PA) learning is an effective framework for performing max-margin online learning. But the deterministic formulation and estimated single large-margin mod…

cs.LG2013★ 1 cited

Discriminative Relational Topic Models

Ning Chen, Jun Zhu, Fei Xia +1

Many scientific and engineering fields involve analyzing network data. For document networks, relational topic models (RTMs) provide a probabilistic generative process to describe…

cs.LG2013★ 9 cited

Improved Bayesian Logistic Supervised Topic Models with Data Augmentation

Jun Zhu, Xun Zheng, Bo Zhang

Supervised topic models with a logistic likelihood have two issues that potentially limit their practical use: 1) response variables are usually over-weighted by document word coun…

cs.LG2013★ 1 cited

Relaxed Sparse Eigenvalue Conditions for Sparse Estimation via Non-convex Regularized Regression

Zheng Pan, Changshui Zhang

Non-convex regularizers usually improve the performance of sparse estimation in practice. To prove this fact, we study the conditions of sparse estimations for the sharp concave re…

cs.LG2013★ 289 cited

A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems

Pinghua Gong, Changshui Zhang, Zhaosong Lu +2

Non-convex sparsity-inducing penalties have recently received considerable attentions in sparse learning. Recent theoretical investigations have demonstrated their superiority over…

cs.LG2013★ 63 cited

Denoising Deep Neural Networks Based Voice Activity Detection

Xiao-Lei Zhang, Ji Wu

Recently, the deep-belief-networks (DBN) based voice activity detection (VAD) has been proposed. It is powerful in fusing the advantages of multiple features, and achieves the stat…

cs.LG2013

Heuristic Ternary Error-Correcting Output Codes Via Weight Optimization and Layered Clustering-Based Approach

Xiao-Lei Zhang

One important classifier ensemble for multiclass classification problems is Error-Correcting Output Codes (ECOCs). It bridges multiclass problems and binary-class classifiers by de…

cs.LG2013

Convex Discriminative Multitask Clustering

Xiao-Lei Zhang

Multitask clustering tries to improve the clustering performance of multiple tasks simultaneously by taking their relationship into account. Most existing multitask clustering algo…