
FedLab: A Flexible Federated Learning Framework
Federated learning (FL) is a machine learning field in which researchers...
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Kernel Selection for Stein Variational Gradient Descent
Stein variational gradient descent (SVGD) and its variants have shown pr...
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ByPEVAE: Bayesian Pseudocoresets Exemplar VAE
Recent studies show that advanced priors play a major role in deep gener...
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Boosting fewshot classification with viewlearnable contrastive learning
The goal of fewshot classification is to classify new categories with f...
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Rectifying the Shortcut Learning of Background: Shared Object Concentration for FewShot Image Recognition
FewShot image classification aims to utilize pretrained knowledge learn...
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Discrete Autoregressive Variational Attention Models for Text Modeling
Variational autoencoders (VAEs) have been widely applied for text modeli...
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AFINet: Attentive Feature Integration Networks for Image Classification
Convolutional Neural Networks (CNNs) have achieved tremendous success in...
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TedNet: A Pytorch Toolkit for Tensor Decomposition Networks
Tensor Decomposition Networks(TDNs) prevail for their inherent compact a...
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Pseudosupervised Deep Subspace Clustering
AutoEncoder (AE)based deep subspace clustering (DSC) methods have achi...
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Partial Differential Equations is All You Need for Generating Neural Architectures – A Theory for Physical Artificial Intelligence Systems
In this work, we generalize the reactiondiffusion equation in statistic...
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Contrastive Disentanglement in Generative Adversarial Networks
Disentanglement is defined as the problem of learninga representation th...
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A Survey on Deep Semisupervised Learning
Deep semisupervised learning is a fastgrowing field with a range of pr...
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Graphbased Semisupervised Learning: A Comprehensive Review
Semisupervised learning (SSL) has tremendous value in practice due to i...
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MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance
Deep Convolutional Neural Networks (DCNNs) and their variants have been ...
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RegNet: SelfRegulated Network for Image Classification
The ResNet and its variants have achieved remarkable successes in variou...
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A Subword Guided Neural Word Segmentation Model for Sindhi
Deep neural networks employ multiple processing layers for learning text...
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CRaDLe: Deep Code Retrieval Based on Semantic Dependency Learning
Code retrieval is a common practice for programmers to reuse existing co...
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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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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.