b'Wenqi Wei'

research

∙ 09/16/2023

Rethinking Learning Rate Tuning in the Era of Large Language Models

Large Language Models (LLMs) represent the recent success of deep learni...

0 Hongpeng Jin, et al. ∙

research

∙ 08/19/2023

Explicit Time Embedding Based Cascade Attention Network for Information Popularity Prediction

Predicting information cascade popularity is a fundamental problem in so...

0 Xigang Sun, et al. ∙

research

∙ 06/13/2023

Few-shot Multi-domain Knowledge Rearming for Context-aware Defence against Advanced Persistent Threats

Advanced persistent threats (APTs) have novel features such as multi-sta...

0 Gaolei Li, et al. ∙

research

∙ 05/10/2023

Securing Distributed SGD against Gradient Leakage Threats

This paper presents a holistic approach to gradient leakage resilient di...

0 Wenqi Wei, et al. ∙

research

∙ 03/21/2023

STDLens: Model Hijacking-Resilient Federated Learning for Object Detection

Federated Learning (FL) has been gaining popularity as a collaborative l...

0 Ka-Ho Chow, et al. ∙

research

∙ 03/20/2023

GNN-Ensemble: Towards Random Decision Graph Neural Networks

Graph Neural Networks (GNNs) have enjoyed wide spread applications in gr...

0 Wenqi Wei, et al. ∙

research

∙ 02/08/2023

Machine Learning for Synthetic Data Generation: a Review

Data plays a crucial role in machine learning. However, in real-world ap...

0 Yingzhou Lu, et al. ∙

research

∙ 01/15/2023

EENet: Learning to Early Exit for Adaptive Inference

Budgeted adaptive inference with early exits is an emerging technique to...

0 Fatih Ilhan, et al. ∙

research

∙ 12/25/2021

Gradient Leakage Attack Resilient Deep Learning

Gradient leakage attacks are considered one of the wickedest privacy thr...

2 Wenqi Wei, et al. ∙

research

∙ 10/14/2021

Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding

Network representation learning (NRL) advances the conventional graph mi...

0 Jingya Zhou, et al. ∙

research

∙ 07/10/2021

Speech2Video: Cross-Modal Distillation for Speech to Video Generation

This paper investigates a novel task of talking face video generation so...

0 Shijing Si, et al. ∙

research

∙ 07/02/2021

Gradient-Leakage Resilient Federated Learning

Federated learning(FL) is an emerging distributed learning paradigm with...

0 Wenqi Wei, et al. ∙

research

∙ 10/20/2020

Promoting High Diversity Ensemble Learning with EnsembleBench

Ensemble learning is gaining renewed interests in recent years. This pap...

0 Yanzhao Wu, et al. ∙

research

∙ 09/14/2020

Robust Deep Learning Ensemble against Deception

Deep neural network (DNN) models are known to be vulnerable to malicious...

0 Wenqi Wei, et al. ∙

research

∙ 08/18/2020

A Real-time Robot-based Auxiliary System for Risk Evaluation of COVID-19 Infection

In this paper, we propose a real-time robot-based auxiliary system for r...

0 Wenqi Wei, et al. ∙

research

∙ 07/15/2020

Bitcoin Transaction Forecasting with Deep Network Representation Learning

Bitcoin and its decentralized computing paradigm for digital currency tr...

0 Wenqi Wei, et al. ∙

research

∙ 07/11/2020

Understanding Object Detection Through An Adversarial Lens

Deep neural networks based object detection models have revolutionized c...

12 Ka-Ho Chow, et al. ∙

research

∙ 06/05/2020

LDP-Fed: Federated Learning with Local Differential Privacy

This paper presents LDP-Fed, a novel federated learning system with a fo...

12 Stacey Truex, et al. ∙

research

∙ 04/22/2020

A Framework for Evaluating Gradient Leakage Attacks in Federated Learning

Federated learning (FL) is an emerging distributed machine learning fram...

5 Wenqi Wei, et al. ∙

research

∙ 04/09/2020

TOG: Targeted Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems

The rapid growth of real-time huge data capturing has pushed the deep le...

3 Ka-Ho Chow, et al. ∙

research

∙ 11/21/2019

Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability

Membership inference attacks seek to infer the membership of individual ...

2 Stacey Truex, et al. ∙

research

∙ 10/01/2019

Cross-Layer Strategic Ensemble Defense Against Adversarial Examples

Deep neural network (DNN) has demonstrated its success in multiple domai...

9 Wenqi Wei, et al. ∙

research

∙ 08/29/2019

Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness

Ensemble learning is a methodology that integrates multiple DNN learners...

0 Ling Liu, et al. ∙

research

∙ 08/21/2019

Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks

Deep neural networks (DNNs) have demonstrated impressive performance on ...

0 Ka-Ho Chow, et al. ∙

research

∙ 08/18/2019

Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks

Learning Rate (LR) is an important hyper-parameter to tune for effective...

0 Yanzhao Wu, et al. ∙

research

∙ 05/15/2019

Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy

Local Differential Privacy (LDP) is popularly used in practice for priva...

0 Mehmet Emre Gursoy, et al. ∙

research

∙ 10/29/2018

A Comparative Measurement Study of Deep Learning as a Service Framework

Big data powered Deep Learning (DL) and its applications have blossomed ...

0 Yanzhao Wu, et al. ∙

research

∙ 06/29/2018

Adversarial Examples in Deep Learning: Characterization and Divergence

The burgeoning success of deep learning has raised the security and priv...

0 Wenqi Wei, et al. ∙

research

∙ 06/28/2018

Towards Demystifying Membership Inference Attacks

Membership inference attacks seek to infer membership of individual trai...

0 Stacey Truex, et al. ∙

Wenqi Wei

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