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07/05/2023
Personalized Federated Learning via Amortized Bayesian Meta-Learning
Federated learning is a decentralized and privacy-preserving technique t...
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06/26/2023
Practical Privacy-Preserving Gaussian Process Regression via Secret Sharing
Gaussian process regression (GPR) is a non-parametric model that has bee...
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06/06/2023
Enabling Intelligent Interactions between an Agent and an LLM: A Reinforcement Learning Approach
Large language models (LLMs) encode a vast amount of world knowledge acq...
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05/09/2023
BadCS: A Backdoor Attack Framework for Code search
With the development of deep learning (DL), DL-based code search models ...
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03/20/2023
Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition
Named entity recognition (NER) is an important research problem in natur...
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03/02/2023
Stochastic Clustered Federated Learning
Federated learning is a distributed learning framework that takes full a...
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02/21/2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
Trustworthy artificial intelligence (AI) technology has revolutionized d...
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12/20/2022
When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods
With increasing privacy concerns on data, recent studies have made signi...
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12/19/2022
MultiCoder: Multi-Programming-Lingual Pre-Training for Low-Resource Code Completion
Code completion is a valuable topic in both academia and industry. Recen...
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10/30/2022
Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid
Few-shot learning (FSL) targets at generalization of vision models towar...
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10/11/2022
ViLPAct: A Benchmark for Compositional Generalization on Multimodal Human Activities
We introduce ViLPAct, a novel vision-language benchmark for human activi...
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10/11/2022
Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
Transformer-based models have achieved great success on sentence pair mo...
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07/09/2022
A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
Transformer-based models have demonstrated state-of-the-art performance ...
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06/16/2022
ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization
Graph Neural Networks (GNNs) have attracted much attention due to their ...
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06/16/2022
Channel Importance Matters in Few-Shot Image Classification
Few-Shot Learning (FSL) requires vision models to quickly adapt to brand...
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05/26/2022
Aggregating Gradients in Encoded Domain for Federated Learning
Malicious attackers and an honest-but-curious server can steal private c...
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05/05/2022
Contrastive Multi-view Hyperbolic Hierarchical Clustering
Hierarchical clustering recursively partitions data at an increasingly f...
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03/12/2022
MarkBERT: Marking Word Boundaries Improves Chinese BERT
We present a Chinese BERT model dubbed MarkBERT that uses word informati...
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02/14/2022
Source Code Summarization with Structural Relative Position Guided Transformer
Source code summarization aims at generating concise and clear natural l...
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02/03/2022
Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT
Nowadays, the industrial Internet of Things (IIoT) has played an integra...
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01/31/2022
Heterogeneous Federated Learning via Grouped Sequential-to-Parallel Training
Federated learning (FL) is a rapidly growing privacy-preserving collabor...
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12/14/2021
Exploring Category-correlated Feature for Few-shot Image Classification
Few-shot classification aims to adapt classifiers to novel classes with ...
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12/13/2021
Self-Paced Deep Regression Forests with Consideration on Ranking Fairness
Deep discriminative models (DDMs), such as deep regression forests, deep...
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11/09/2021
Label-Aware Distribution Calibration for Long-tailed Classification
Real-world data usually present long-tailed distributions. Training on i...
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07/24/2021
FedLab: A Flexible Federated Learning Framework
Federated learning (FL) is a machine learning field in which researchers...
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07/20/2021
Kernel Selection for Stein Variational Gradient Descent
Stein variational gradient descent (SVGD) and its variants have shown pr...
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07/20/2021
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAE
Recent studies show that advanced priors play a major role in deep gener...
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07/20/2021
Boosting few-shot classification with view-learnable contrastive learning
The goal of few-shot classification is to classify new categories with f...
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07/16/2021
Rectifying the Shortcut Learning of Background: Shared Object Concentration for Few-Shot Image Recognition
Few-Shot image classification aims to utilize pretrained knowledge learn...
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06/16/2021
Discrete Auto-regressive Variational Attention Models for Text Modeling
Variational autoencoders (VAEs) have been widely applied for text modeli...
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05/10/2021
AFINet: Attentive Feature Integration Networks for Image Classification
Convolutional Neural Networks (CNNs) have achieved tremendous success in...
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04/11/2021
TedNet: A Pytorch Toolkit for Tensor Decomposition Networks
Tensor Decomposition Networks(TDNs) prevail for their inherent compact a...
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04/08/2021
Pseudo-supervised Deep Subspace Clustering
Auto-Encoder (AE)-based deep subspace clustering (DSC) methods have achi...
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03/10/2021
Partial Differential Equations is All You Need for Generating Neural Architectures – A Theory for Physical Artificial Intelligence Systems
In this work, we generalize the reaction-diffusion equation in statistic...
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03/05/2021
Contrastive Disentanglement in Generative Adversarial Networks
Disentanglement is defined as the problem of learninga representation th...
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02/28/2021
A Survey on Deep Semi-supervised Learning
Deep semi-supervised learning is a fast-growing field with a range of pr...
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02/26/2021
Graph-based Semi-supervised Learning: A Comprehensive Review
Semi-supervised learning (SSL) has tremendous value in practice due to i...
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01/25/2021
MultiFace: A Generic Training Mechanism for Boosting Face Recognition Performance
Deep Convolutional Neural Networks (DCNNs) and their variants have been ...
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01/03/2021
RegNet: Self-Regulated Network for Image Classification
The ResNet and its variants have achieved remarkable successes in variou...
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12/30/2020
A Subword Guided Neural Word Segmentation Model for Sindhi
Deep neural networks employ multiple processing layers for learning text...
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12/02/2020
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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10/10/2020
Block-term Tensor Neural Networks
Deep neural networks (DNNs) have achieved outstanding performance in a w...
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09/22/2020
Heuristic Rank Selection with Progressively Searching Tensor Ring Network
Recently, Tensor Ring Networks (TRNs) have been applied in deep networks...
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08/31/2020
Structured Graph Learning for Clustering and Semi-supervised Classification
Graphs have become increasingly popular in modeling structures and inter...
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07/26/2020
Deep Embedded Multi-view Clustering with Collaborative Training
Multi-view clustering has attracted increasing attentions recently by ut...
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07/14/2020
Contextualized Code Representation Learning for Commit Message Generation
Automatic generation of high-quality commit messages for code commits ca...
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07/11/2020
Relation-Guided Representation Learning
Deep auto-encoders (DAEs) have achieved great success in learning data r...
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06/10/2020
Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis
Multi-source unsupervised domain adaptation (MS-UDA) for sentiment analy...
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05/12/2020
ReadNet:Towards Accurate ReID with Limited and Noisy Samples
Person re-identification (ReID) is an essential cross-camera retrieval t...
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05/03/2020