b'Dacheng Tao'

research

∙ 06/25/2022

Topology-aware Generalization of Decentralized SGD

This paper studies the algorithmic stability and generalizability of dec...

Tongtian Zhu, et al. ∙

research

∙ 06/20/2022

Variational Distillation for Multi-View Learning

Information Bottleneck (IB) based multi-view learning provides an inform...

Xudong Tian, et al. ∙

research

∙ 06/19/2022

EATFormer: Improving Vision Transformer Inspired by Evolutionary Algorithm

Motivated by biological evolution, this paper explains the rationality o...

Jiangning Zhang, et al. ∙

research

∙ 06/17/2022

Boosting Factorization Machines via Saliency-Guided Mixup

Factorization machines (FMs) are widely used in recommender systems due ...

Chenwang Wu, et al. ∙

research

∙ 06/09/2022

A Relational Intervention Approach for Unsupervised Dynamics Generalization in Model-Based Reinforcement Learning

The generalization of model-based reinforcement learning (MBRL) methods ...

Jixian Guo, et al. ∙

research

∙ 06/07/2022

Recent Advances for Quantum Neural Networks in Generative Learning

Quantum computers are next-generation devices that hold promise to perfo...

Jinkai Tian, et al. ∙

research

∙ 06/03/2022

Understanding deep learning via decision boundary

This paper discovers that the neural network with lower decision boundar...

Shiye Lei, et al. ∙

research

∙ 06/02/2022

Modeling Image Composition for Complex Scene Generation

We present a method that achieves state-of-the-art results on challengin...

Zuopeng Yang, et al. ∙

research

∙ 06/01/2022

DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training

Personalized federated learning is proposed to handle the data heterogen...

Rong Dai, et al. ∙

research

∙ 05/30/2022

E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation

Sequence-to-sequence (seq2seq) learning has become a popular trend for p...

Qihuang Zhong, et al. ∙

research

∙ 05/28/2022

Parameter-Efficient and Student-Friendly Knowledge Distillation

Knowledge distillation (KD) has been extensively employed to transfer th...

Jun Rao, et al. ∙

research

∙ 05/28/2022

Visual Superordinate Abstraction for Robust Concept Learning

Concept learning constructs visual representations that are connected to...

Qi Zheng, et al. ∙

research

∙ 05/24/2022

Penalized Proximal Policy Optimization for Safe Reinforcement Learning

Safe reinforcement learning aims to learn the optimal policy while satis...

Linrui zhang, et al. ∙

research

∙ 05/21/2022

Mapping Emulation for Knowledge Distillation

This paper formalizes the source-blind knowledge distillation problem th...

Jing Ma, et al. ∙

research

∙ 05/19/2022

Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search

Existing trackers usually select a location or proposal with the maximum...

Xiao Wang, et al. ∙

research

∙ 05/18/2022

Revisiting PINNs: Generative Adversarial Physics-informed Neural Networks and Point-weighting Method

Physics-informed neural networks (PINNs) provide a deep learning framewo...

Wensheng Li, et al. ∙

research

∙ 05/10/2022

Theory of Quantum Generative Learning Models with Maximum Mean Discrepancy

The intrinsic probabilistic nature of quantum mechanics invokes endeavor...

Yuxuan Du, et al. ∙

research

∙ 05/03/2022

HL-Net: Heterophily Learning Network for Scene Graph Generation

Scene graph generation (SGG) aims to detect objects and predict their pa...

Xin Lin, et al. ∙

research

∙ 04/26/2022

Neural Maximum A Posteriori Estimation on Unpaired Data for Motion Deblurring

Real-world dynamic scene deblurring has long been a challenging task sin...

Youjian Zhang, et al. ∙

research

∙ 04/24/2022

Source-Free Domain Adaptation via Distribution Estimation

Domain Adaptation aims to transfer the knowledge learned from a labeled ...

Ning Ding, et al. ∙

research

∙ 04/21/2022

A Model-Agnostic Data Manipulation Method for Persona-based Dialogue Generation

Towards building intelligent dialogue agents, there has been a growing i...

Yu Cao, et al. ∙

research

∙ 04/16/2022

BLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation

Data augmentations (DA) are the cores to achieving robust sequence-to-se...

Zheng Zhang, et al. ∙

research

∙ 04/16/2022

Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation

For multilingual sequence-to-sequence pretrained language models (multil...

Changtong Zan, et al. ∙

research

∙ 04/16/2022

A Contrastive Cross-Channel Data Augmentation Framework for Aspect-based Sentiment Analysis

Aspect-Based Sentiment Analysis is a fine-grained sentiment analysis tas...

Bing Wang, et al. ∙

research

∙ 04/15/2022

Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Graph neural networks have emerged as a leading architecture for many gr...

Chuang Liu, et al. ∙

research

∙ 04/13/2022

Defensive Patches for Robust Recognition in the Physical World

To operate in real-world high-stakes environments, deep learning systems...

Jiakai Wang, et al. ∙

research

∙ 04/10/2022

Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentation

Panoptic Part Segmentation (PPS) aims to unify panoptic segmentation and...

Xiangtai Li, et al. ∙

research

∙ 04/10/2022

Fashionformer: A simple, Effective and Unified Baseline for Human Fashion Segmentation and Recognition

Human fashion understanding is one important computer vision task since ...

Shilin Xu, et al. ∙

research

∙ 04/04/2022

BatchFormerV2: Exploring Sample Relationships for Dense Representation Learning

Attention mechanisms have been very popular in deep neural networks, whe...

Zhi Hou, et al. ∙

research

∙ 03/27/2022

Discovering Human-Object Interaction Concepts via Self-Compositional Learning

A comprehensive understanding of human-object interaction (HOI) requires...

Zhi Hou, et al. ∙

research

∙ 03/24/2022

Knowledge Removal in Sampling-based Bayesian Inference

The right to be forgotten has been legislated in many countries, but its...

Shaopeng Fu, et al. ∙

research

∙ 03/17/2022

Gaussian initializations help deep variational quantum circuits escape from the barren plateau

Variational quantum circuits have been widely employed in quantum simula...

Kaining Zhang, et al. ∙

research

∙ 03/17/2022

Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning

Federated Learning (FL) is an emerging distributed learning paradigm und...

Lin Zhang, et al. ∙

research

∙ 03/17/2022

Do We Really Need a Learnable Classifier at the End of Deep Neural Network?

Modern deep neural networks for classification usually jointly learn a b...

Yibo Yang, et al. ∙

research

∙ 03/10/2022

Contrastive Boundary Learning for Point Cloud Segmentation

Point cloud segmentation is fundamental in understanding 3D environments...

Liyao Tang, et al. ∙

research

∙ 03/08/2022

ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation

Point cloud classifiers with rotation robustness have been widely discus...

Robin Wang, et al. ∙

research

∙ 03/08/2022

Where Does the Performance Improvement Come From? – A Reproducibility Concern about Image-Text Retrieval

This paper seeks to provide the information retrieval community with som...

Jun Rao, et al. ∙

research

∙ 03/03/2022

BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning

Despite the success of deep neural networks, there are still many challe...

Zhi Hou, et al. ∙

research

∙ 02/15/2022

Hyper-relationship Learning Network for Scene Graph Generation

Generating informative scene graphs from images requires integrating and...

Yibing Zhan, et al. ∙

research

∙ 01/27/2022

Achieving Personalized Federated Learning with Sparse Local Models

Federated learning (FL) is vulnerable to heterogeneously distributed dat...

Tiansheng Huang, et al. ∙

research

∙ 01/19/2022

Improving Neural Machine Translation by Denoising Training

We present a simple and effective pretraining strategy Denoising Trainin...

Liang Ding, et al. ∙

research

∙ 01/13/2022

TransVOD: End-to-end Video Object Detection with Spatial-Temporal Transformers

Detection Transformer (DETR) and Deformable DETR have been proposed to e...

Qianyu Zhou, et al. ∙

research

∙ 01/13/2022

Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) is a fine-grained task of sentime...

Qihuang Zhong, et al. ∙

research

∙ 01/01/2022

Quality-aware Part Models for Occluded Person Re-identification

Occlusion poses a major challenge for person re-identification (ReID). E...

Pengfei Wang, et al. ∙

research

∙ 12/30/2021

Few-shot Backdoor Defense Using Shapley Estimation

Deep neural networks have achieved impressive performance in a variety o...

Jiyang Guan, et al. ∙

research

∙ 12/22/2021

SkipNode: On Alleviating Over-smoothing for Deep Graph Convolutional Networks

Over-smoothing is a challenging problem, which degrades the performance ...

Weigang Lu, et al. ∙

research

∙ 12/21/2021

PONet: Robust 3D Human Pose Estimation via Learning Orientations Only

Conventional 3D human pose estimation relies on first detecting 2D body ...

Jue Wang, et al. ∙

research

∙ 12/15/2021

Self-Ensembling GAN for Cross-Domain Semantic Segmentation

Deep neural networks (DNNs) have greatly contributed to the performance ...

Yonghao Xu, et al. ∙

research

∙ 12/13/2021

DGL-GAN: Discriminator Guided Learning for GAN Compression

Generative Adversarial Networks (GANs) with high computation costs, e.g....

Yuesong Tian, et al. ∙

research

∙ 12/12/2021

Spatial-Temporal-Fusion BNN: Variational Bayesian Feature Layer

Bayesian neural networks (BNNs) have become a principal approach to alle...

Shiye Lei, et al. ∙

Dacheng Tao

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