63 citations · 235 across the 37 of their papers we have counts for
15 papers · 1 filter
fMBN-E: Efficient Unsupervised Network Structure Ensemble and Selection for Clustering
Xiao-Lei Zhang
It is known that unsupervised nonlinear dimensionality reduction and clustering is sensitive to the selection of hyperparameters, particularly for deep learning based methods, whic…
Partial AUC optimization based deep speaker embeddings with class-center learning for text-independent speaker verification
Zhongxin Bai, Xiao-Lei Zhang, Jingdong Chen
Deep embedding based text-independent speaker verification has demonstrated superior performance to traditional methods in many challenging scenarios. Its loss functions can be gen…
Deep topic modeling by multilayer bootstrap network and lasso
Jianyu Wang, Xiao-Lei Zhang
Topic modeling is widely studied for the dimension reduction and analysis of documents. However, it is formulated as a difficult optimization problem. Current approximate solutions…
Learning the kernel matrix by resampling
Xiao-Lei Zhang
In this abstract paper, we introduce a new kernel learning method by a nonparametric density estimator. The estimator consists of a group of k-centroids clusterings. Each clusterin…
Multilayer bootstrap network for unsupervised speaker recognition
Xiao-Lei Zhang
We apply multilayer bootstrap network (MBN), a recent proposed unsupervised learning method, to unsupervised speaker recognition. The proposed method first extracts supervectors fr…
Unsupervised model compression for multilayer bootstrap networks
Xiao-Lei Zhang
Recently, multilayer bootstrap network (MBN) has demonstrated promising performance in unsupervised dimensionality reduction. It can learn compact representations in standard data…
Deep Distributed Random Samplings for Supervised Learning: An Alternative to Random Forests?
Xiao-Lei Zhang
In (\cite{zhang2014nonlinear,zhang2014nonlinear2}), we have viewed machine learning as a coding and dimensionality reduction problem, and further proposed a simple unsupervised dim…
Multilayer bootstrap networks
Xiao-Lei Zhang
Multilayer bootstrap network builds a gradually narrowed multilayer nonlinear network from bottom up for unsupervised nonlinear dimensionality reduction. Each layer of the network…
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…