b'Chen Zhu'

research

∙ 08/19/2023

Physics-Guided Human Motion Capture with Pose Probability Modeling

Incorporating physics in human motion capture to avoid artifacts like fl...

0 Jingyi Ju, et al. ∙

research

∙ 07/19/2023

Multi-Grained Multimodal Interaction Network for Entity Linking

Multimodal entity linking (MEL) task, which aims at resolving ambiguous ...

0 Pengfei Luo, et al. ∙

research

∙ 07/03/2023

A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics

In today's competitive and fast-evolving business environment, it is a c...

0 Chuan Qin, et al. ∙

research

∙ 06/28/2023

On the Exploitability of Instruction Tuning

Instruction tuning is an effective technique to align large language mod...

0 Manli Shu, et al. ∙

research

∙ 05/31/2023

A Survey on Large Language Models for Recommendation

Large Language Models (LLMs) have emerged as powerful tools in the field...

0 Likang Wu, et al. ∙

research

∙ 05/21/2023

Social Context-aware GCN for Video Character Search via Scene-prior Enhancement

With the increasing demand for intelligent services of online video plat...

0 Wenjun Peng, et al. ∙

research

∙ 05/03/2023

DELTA: Direct Embedding Enhancement and Leverage Truncated Conscious Attention for Recommendation System

Click-Through Rate (CTR) prediction is the most critical task in product...

0 Chen Zhu, et al. ∙

research

∙ 12/15/2022

Multi-Level Association Rule Mining for Wireless Network Time Series Data

Key performance indicators(KPIs) are of great significance in the monito...

0 Chen Zhu, et al. ∙

research

∙ 12/11/2022

CPMLHO:Hyperparameter Tuning via Cutting Plane and Mixed-Level Optimization

The hyperparameter optimization of neural network can be expressed as a ...

0 Shuo Yang, et al. ∙

research

∙ 11/02/2022

Heterogeneous Trajectory Forecasting via Risk and Scene Graph Learning

Heterogeneous trajectory forecasting is critical for intelligent transpo...

0 Jianwu Fang, et al. ∙

research

∙ 05/20/2022

Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors

Deep learning is increasingly moving towards a transfer learning paradig...

17 Ravid Shwartz-Ziv, et al. ∙

research

∙ 05/12/2022

Outage Analysis of Aerial Semi-Grant-Free NOMA Systems

In this paper, we analyze the outage performance of unmanned aerial vehi...

0 Hongjiang Lei, et al. ∙

research

∙ 01/31/2022

Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations

Existing techniques for model inversion typically rely on hard-to-tune r...

0 Amin Ghiasi, et al. ∙

research

∙ 10/27/2021

VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization

Most state-of-the-art Graph Neural Networks (GNNs) can be defined as a f...

31 Mucong Ding, et al. ∙

research

∙ 10/26/2021

Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task

Self-supervised learning (SSL) has achieved great success in a variety o...

0 Jiuhai Chen, et al. ∙

research

∙ 07/05/2021

Long-Short Transformer: Efficient Transformers for Language and Vision

Transformers have achieved success in both language and vision domains. ...

12 Chen Zhu, et al. ∙

research

∙ 04/18/2021

The Intrinsic Dimension of Images and Its Impact on Learning

It is widely believed that natural image data exhibits low-dimensional s...

0 Phillip Pope, et al. ∙

research

∙ 02/16/2021

GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training

Changes in neural architectures have fostered significant breakthroughs ...

0 Chen Zhu, et al. ∙

research

∙ 12/08/2020

LAMP: Label Augmented Multimodal Pretraining

Multi-modal representation learning by pretraining has become an increas...

0 Jia Guo, et al. ∙

research

∙ 12/01/2020

Modifying Memories in Transformer Models

Large Transformer models have achieved impressive performance in many na...

0 Chen Zhu, et al. ∙

research

∙ 10/24/2020

Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks

Adversarial Training is proved to be an efficient method to defend again...

0 Huimin Zeng, et al. ∙

research

∙ 10/15/2020

Spherical Knowledge Distillation

Knowledge distillation aims at obtaining a small but effective deep mode...

6 Jia Guo, et al. ∙

research

∙ 10/14/2020

Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer

When large scale training data is available, one can obtain compact and ...

0 Chen Zhu, et al. ∙

research

∙ 06/21/2020

Adaptive Learning Rates with Maximum Variation Averaging

Adaptive gradient methods such as RMSProp and Adam use exponential movin...

19 Chen Zhu, et al. ∙

research

∙ 06/11/2020

Large-Scale Adversarial Training for Vision-and-Language Representation Learning

We present VILLA, the first known effort on large-scale adversarial trai...

6 Zhe Gan, et al. ∙

research

∙ 04/20/2020

Headless Horseman: Adversarial Attacks on Transfer Learning Models

Transfer learning facilitates the training of task-specific classifiers ...

0 Ahmed Abdelkader, et al. ∙

research

∙ 03/14/2020

Certified Defenses for Adversarial Patches

Adversarial patch attacks are among one of the most practical threat mod...

0 Ping-Yeh Chiang, et al. ∙

research

∙ 02/23/2020

SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback

The recent development of online recommender systems has a focus on coll...

0 Chao Wang, et al. ∙

research

∙ 02/22/2020

Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers

Convex relaxations are effective for training and certifying neural netw...

5 Chen Zhu, et al. ∙

research

∙ 12/11/2019

Learning from Noisy Anchors for One-stage Object Detection

State-of-the-art object detectors rely on regressing and classifying an ...

12 Hengduo Li, et al. ∙

research

∙ 09/29/2019

Strong Baseline Defenses Against Clean-Label Poisoning Attacks

Targeted clean-label poisoning is a type of adversarial attack on machin...

0 Neal Gupta, et al. ∙

research

∙ 09/25/2019

FreeLB: Enhanced Adversarial Training for Language Understanding

Adversarial training, which minimizes the maximal risk for label-preserv...

0 Chen Zhu, et al. ∙

research

∙ 05/20/2019

Adversarially robust transfer learning

Transfer learning, in which a network is trained on one task and re-purp...

2 Ali Shafahi, et al. ∙

research

∙ 05/15/2019

Transferable Clean-Label Poisoning Attacks on Deep Neural Nets

In this paper, we explore clean-label poisoning attacks on deep convolut...

0 Chen Zhu, et al. ∙

research

∙ 12/21/2018

Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach

The wide spread use of online recruitment services has led to informatio...

14 Chuan Qin, et al. ∙

research

∙ 10/26/2018

Fine-grained Video Categorization with Redundancy Reduction Attention

For fine-grained categorization tasks, videos could serve as a better so...

8 Chen Zhu, et al. ∙

research

∙ 10/08/2018

Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning

Person-Job Fit is the process of matching the right talent for the right...

0 Chen Zhu, et al. ∙

research

∙ 10/02/2018

Fusion of Monocular Vision and Radio-based Ranging for Global Scale Estimation and Drift Mitigation

Monocular vision-based Simultaneous Localization and Mapping (SLAM) is u...

0 Young-Hee Lee, et al. ∙

research

∙ 06/13/2018

Learning Visual Knowledge Memory Networks for Visual Question Answering

Visual question answering (VQA) requires joint comprehension of images a...

0 Zhou Su, et al. ∙

research

∙ 02/28/2018

Compressing Neural Networks using the Variational Information Bottleneck

Neural networks can be compressed to reduce memory and computational req...

0 Bin Dai, et al. ∙

research

∙ 12/08/2017

Collaborative Company Profiling: Insights from an Employee's Perspective

Company profiling is an analytical process to build an indepth understan...

0 Hao Lin, et al. ∙

research

∙ 12/08/2017

Recruitment Market Trend Analysis with Sequential Latent Variable Models

Recruitment market analysis provides valuable understanding of industry-...

0 Chen Zhu, et al. ∙

research

∙ 12/06/2017

Measuring the Popularity of Job Skills in Recruitment Market: A Multi-Criteria Approach

To cope with the accelerating pace of technological changes, talents are...

0 Tong Xu, et al. ∙

research

∙ 08/07/2017

Structured Attentions for Visual Question Answering

Visual attention, which assigns weights to image regions according to th...

0 Chen Zhu, et al. ∙

Chen Zhu

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