63 citations · 235 across the 37 of their papers we have counts for
7 papers · 1 filter
Learning Deep Representations By Distributed Random Samplings
Xiao-Lei Zhang
In this paper, we propose an extremely simple deep model for the unsupervised nonlinear dimensionality reduction -- deep distributed random samplings, which performs like a stack o…
Learning Deep Representation Without Parameter Inference for Nonlinear Dimensionality Reduction
Xiao-Lei Zhang
Unsupervised deep learning is one of the most powerful representation learning techniques. Restricted Boltzman machine, sparse coding, regularized auto-encoders, and convolutional…
Simple Deep Random Model Ensemble
Xiao-Lei Zhang, Ji Wu
Representation learning and unsupervised learning are two central topics of machine learning and signal processing. Deep learning is one of the most effective unsupervised represen…
Transfer Learning for Voice Activity Detection: A Denoising Deep Neural Network Perspective
Xiao-Lei Zhang, Ji Wu
Mismatching problem between the source and target noisy corpora severely hinder the practical use of the machine-learning-based voice activity detection (VAD). In this paper, we tr…
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…
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…
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…