
Blockterm Tensor Neural Networks
Deep neural networks (DNNs) have achieved outstanding performance in a w...
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Heuristic Rank Selection with Progressively Searching Tensor Ring Network
Recently, Tensor Ring Networks (TRNs) have been applied in deep networks...
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Structured Graph Learning for Clustering and Semisupervised Classification
Graphs have become increasingly popular in modeling structures and inter...
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Deep Embedded Multiview Clustering with Collaborative Training
Multiview clustering has attracted increasing attentions recently by ut...
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Contextualized Code Representation Learning for Commit Message Generation
Automatic generation of highquality commit messages for code commits ca...
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RelationGuided Representation Learning
Deep autoencoders (DAEs) have achieved great success in learning data r...
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Adversarial Training Based MultiSource Unsupervised Domain Adaptation for Sentiment Analysis
Multisource unsupervised domain adaptation (MSUDA) for sentiment analy...
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ReadNet:Towards Accurate ReID with Limited and Noisy Samples
Person reidentification (ReID) is an essential crosscamera retrieval t...
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Mutual Information Gradient Estimation for Representation Learning
Mutual Information (MI) plays an important role in representation learni...
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Discrete Variational Attention Models for Language Generation
Variational autoencoders have been widely applied for natural language g...
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SelfPaced Deep Regression Forests with Consideration on Underrepresented Samples
Deep discriminative models (e.g. deep regression forests, deep Gaussian ...
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Multiview Subspace Clustering via Partition Fusion
Multiview clustering is an important approach to analyze multiview dat...
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Structure Learning with Similarity Preserving
Leveraging on the underlying lowdimensional structure of data, lowrank...
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A New Corpus for LowResourced Sindhi Language with Word Embeddings
Representing words and phrases into dense vectors of real numbers which ...
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Largescale Multiview Subspace Clustering in Linear Time
A plethora of multiview subspace clustering (MVSC) methods have been pr...
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Deep Minimax Probability Machine
Deep neural networks enjoy a powerful representation and have proven eff...
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On Model Robustness Against Adversarial Examples
We study the model robustness against adversarial examples, referred to ...
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Multigraph Fusion for Multiview Spectral Clustering
A panoply of multiview clustering algorithms has been developed to deal...
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Multiple Partitions Aligned Clustering
Multiview clustering is an important yet challenging task due to the di...
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Structured Pruning of Recurrent Neural Networks through Neuron Selection
Recurrent neural networks (RNNs) have recently achieved remarkable succe...
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Clustering with Similarity Preserving
Graphbased clustering has shown promising performance in many tasks. A ...
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Additive Adversarial Learning for Unbiased Authentication
Authentication is a task aiming to confirm the truth between data instan...
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Lowrank Kernel Learning for Graphbased Clustering
Constructing the adjacency graph is fundamental to graphbased clusterin...
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Similarity Learning via Kernel Preserving Embedding
Data similarity is a key concept in many datadriven applications. Many ...
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DART: DomainAdversarial ResidualTransfer Networks for Unsupervised CrossDomain Image Classification
The accuracy of deep learning (e.g., convolutional neural networks) for ...
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Robust Graph Learning from Noisy Data
Learning graphs from data automatically has shown encouraging performanc...
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Latent Dirichlet Allocation in Generative Adversarial Networks
Mode collapse is one of the key challenges in the training of Generative...
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Deep Densitybased Image Clustering
Recently, deep clustering, which is able to perform feature learning tha...
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Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition
Recurrent Neural Networks (RNNs) and their variants, such as LongShort ...
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SelfPaced MultiTask Clustering
Multitask clustering (MTC) has attracted a lot of research attentions i...
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Selfweighted Multiple Kernel Learning for Graphbased Clustering and Semisupervised Classification
Multiple kernel learning (MKL) method is generally believed to perform b...
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SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks
Going deeper and wider in neural architectures improves the accuracy, wh...
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BTNets: Simplifying Deep Neural Networks via Block Term Decomposition
Recently, deep neural networks (DNNs) have been regarded as the stateof...
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Learning Compact Recurrent Neural Networks with BlockTerm Tensor Decomposition
Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. H...
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Two Birds with One Stone: Iteratively Learn Facial Attributes with GANs
Generating high fidelity identitypreserving faces has a wide range of a...
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Unified Spectral Clustering with Optimal Graph
Spectral clustering has found extensive use in many areas. Most traditio...
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Stochastic Sequential Neural Networks with Structured Inference
Unsupervised structure learning in highdimensional time series data has...
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Simple and Efficient Parallelization for Probabilistic Temporal Tensor Factorization
Probabilistic Temporal Tensor Factorization (PTTF) is an effective algor...
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Tensor Decomposition via Variational AutoEncoder
Tensor decomposition is an important technique for capturing the highor...
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Distributed Flexible Nonlinear Tensor Factorization
Tensor factorization is a powerful tool to analyse multiway data. Compa...
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Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis
Given genetic variations and various phenotypical traits, such as Magnet...
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Robust Metric Learning by Smooth Optimization
Most existing distance metric learning methods assume perfect side infor...
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Sparse matrixvariate Gaussian process blockmodels for network modeling
We face network data from various sources, such as protein interactions ...
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Zenglin Xu
verfied profile
Professor and PhD Advisor at University of Electronic Science & Technology of China, director of Statistical Machine Intelligence and LEarning (SMILE) Lab at University of Electronic Science and Technology of China since 2014. He has been working at as a researcher at Purdue University from 20102014, Postdoctoral Researcher at Max Planck Institute for Informatics 20092010, Research assistant at The Chinese University of Hong Kong from 20052009, visiting scholar at Michigan State University in 2007 and 2008.