b'Wei Tang'

DeepAI

Featured Co-authors

Yang Liu
344 publications
Philip S. Yu
261 publications
Jie Chen
178 publications
Fan Yang
176 publications
Meng Wang
175 publications
Ping Luo
142 publications
Jiawei Zhang
122 publications
Xiangnan He
108 publications
Xiang Wang
100 publications
Nanning Zheng
79 publications
Qixiang Ye
76 publications

research

∙ 12/18/2022

Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision

Weakly supervised machine learning algorithms are able to learn from amb...

Wei Tang, et al. ∙

research

∙ 11/17/2022

Dynamic Predictive Sampling Analog to Digital Converter for Sparse Signal Sensing

This paper presents a dynamic predictive sampling (DPS) based analog-to-...

Xiaochen Tang, et al. ∙

research

∙ 11/17/2022

Fully Digital Second-order Level-crossing Sampling ADC for Data Saving in Sensing Sparse Signals

This paper presents a fully integrated second-order level-crossing sampl...

Mario Renteria-Pinon, et al. ∙

research

∙ 11/16/2022

UniRel: Unified Representation and Interaction for Joint Relational Triple Extraction

Relational triple extraction is challenging for its difficulty in captur...

Wei Tang, et al. ∙

research

∙ 10/12/2022

LACV-Net: Semantic Segmentation of Large-Scale Point Cloud Scene via Local Adaptive and Comprehensive VLAD

Large-scale point cloud semantic segmentation is an important task in 3D...

Ziyin Zeng, et al. ∙

research

∙ 07/17/2022

Rationality-Robust Information Design: Bayesian Persuasion under Quantal Response

We relax the receiver's full rationality assumption in Bayesian persuasi...

Yiding Feng, et al. ∙

research

∙ 06/23/2022

Learning to Refactor Action and Co-occurrence Features for Temporal Action Localization

The main challenge of Temporal Action Localization is to retrieve subtle...

Kun Xia, et al. ∙

research

∙ 04/21/2022

LibDB: An Effective and Efficient Framework for Detecting Third-Party Libraries in Binaries

Third-party libraries (TPLs) are reused frequently in software applicati...

Wei Tang, et al. ∙

research

∙ 02/12/2022

Online Bayesian Recommendation with No Regret

We introduce and study the online Bayesian recommendation problem for a ...

Yiding Feng, et al. ∙

research

∙ 12/20/2021

Translational Concept Embedding for Generalized Compositional Zero-shot Learning

Generalized compositional zero-shot learning means to learn composed con...

He Huang, et al. ∙

research

∙ 08/05/2021

Time-aware Path Reasoning on Knowledge Graph for Recommendation

Reasoning on knowledge graph (KG) has been studied for explainable recom...

Yuyue Zhao, et al. ∙

research

∙ 07/31/2021

Unlimited Neighborhood Interaction for Heterogeneous Trajectory Prediction

Understanding complex social interactions among agents is a key challeng...

Fang Zheng, et al. ∙

research

∙ 07/27/2021

Enriching Local and Global Contexts for Temporal Action Localization

Effectively tackling the problem of temporal action localization (TAL) n...

Zixin Zhu, et al. ∙

research

∙ 03/30/2021

Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context

Weakly-supervised Temporal Action Localization (WS-TAL) methods learn to...

Ziyi Liu, et al. ∙

research

∙ 03/28/2021

ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization

The object of Weakly-supervised Temporal Action Localization (WS-TAL) is...

Ziyi Liu, et al. ∙

research

∙ 03/05/2021

Competitive Information Disclosure with Multiple Receivers

This paper analyzes a model of competition in Bayesian persuasion in whi...

Bolin Ding, et al. ∙

research

∙ 11/22/2020

BigBen: Telemetry Processing for Internet-wide Event Monitoring

This paper describes BigBen, a network telemetry processing system desig...

Meenakshi Syamkumar, et al. ∙

research

∙ 11/09/2020

Two-Stream Appearance Transfer Network for Person Image Generation

Pose guided person image generation means to generate a photo-realistic ...

Chengkang Shen, et al. ∙

research

∙ 10/22/2020

Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization

Weakly-supervised Temporal Action Localization (W-TAL) aims to classify ...

Yuanhao Zhai, et al. ∙

research

∙ 09/28/2020

Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score

Scene graph parsing aims to detect objects in an image scene and recogni...

He Huang, et al. ∙

research

∙ 09/16/2020

The 1st Tiny Object Detection Challenge:Methods and Results

The 1st Tiny Object Detection (TOD) Challenge aims toencourage research ...

Xuehui Yu, et al. ∙

research

∙ 07/30/2020

Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge

Multi-label zero-shot classification aims to predict multiple unseen cla...

He Huang, et al. ∙

research

∙ 04/15/2020

Combining Visible Light and Infrared Imaging for Efficient Detection of Respiratory Infections such as COVID-19 on Portable Device

Coronavirus Disease 2019 (COVID-19) has become a serious global epidemic...

Zheng Jiang, et al. ∙

research

∙ 02/24/2020

Fair Bandit Learning with Delayed Impact of Actions

Algorithmic fairness has been studied mostly in a static setting where t...

Wei Tang, et al. ∙

research

∙ 09/05/2019

Scalable Double Regularization for 3D Nano-CT Reconstruction

Nano-CT (computerized tomography) has emerged as a non-destructive high-...

Wei Tang, et al. ∙

research

∙ 11/27/2018

A Compositional Textual Model for Recognition of Imperfect Word Images

Printed text recognition is an important problem for industrial OCR syst...

Wei Tang, et al. ∙

research

∙ 10/19/2018

MsCGAN: Multi-scale Conditional Generative Adversarial Networks for Person Image Generation

To synthesize high quality person images with arbitrary poses is challen...

Wei Tang, et al. ∙

research

∙ 12/21/2017

ReabsNet: Detecting and Revising Adversarial Examples

Though deep neural network has hit a huge success in recent studies and ...

Jiefeng Chen, et al. ∙

research

∙ 12/15/2017

Study on a Poisson's Equation Solver Based On Deep Learning Technique

In this work, we investigated the feasibility of applying deep learning ...

Tao Shan, et al. ∙