b'Ling Liu'

research

∙ 09/06/2023

Fast and Resource-Efficient Object Tracking on Edge Devices: A Measurement Study

Object tracking is an important functionality of edge video analytic sys...

0 Sanjana Vijay Ganesh, 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

∙ 05/18/2023

Comparing Biases and the Impact of Multilingual Training across Multiple Languages

Studies in bias and fairness in natural language processing have primari...

0 Sharon Levy, 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

∙ 03/29/2023

BERT4ETH: A Pre-trained Transformer for Ethereum Fraud Detection

As various forms of fraud proliferate on Ethereum, it is imperative to s...

0 Sihao Hu, 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

∙ 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

∙ 11/30/2022

Automatic Discovery of Multi-perspective Process Model using Reinforcement Learning

Process mining is a methodology for the derivation and analysis of proce...

0 Sunghyun Sim, et al. ∙

research

∙ 11/28/2022

Metric Learning as a Service with Covariance Embedding

With the emergence of deep learning, metric learning has gained signific...

0 Imam Mustafa Kamal, et al. ∙

research

∙ 10/24/2022

Selecting and Composing Learning Rate Policies for Deep Neural Networks

The choice of learning rate (LR) functions and policies has evolved from...

0 Yanzhao Wu, et al. ∙

research

∙ 10/18/2022

Embedded Silicon-Organic Integrated Neuromorphic System

The development of artificial intelligence (AI) and robotics are both ba...

0 Shengjie Zheng, et al. ∙

research

∙ 10/18/2022

The Brain-Inspired Cooperative Shared Control for Brain-Machine Interface

In the practical application of brain-machine interface technology, the ...

0 Shengjie Zheng, et al. ∙

research

∙ 08/29/2022

Lattice Codes for Lattice-Based PKE

The public key encryption (PKE) protocol in lattice-based cryptography (...

0 Shanxiang Lyu, 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

∙ 10/22/2021

Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering

This paper introduces a two-phase deep feature engineering framework for...

10 Zhongwei Xie, 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

∙ 08/09/2021

Learning Joint Embedding with Modality Alignments for Cross-Modal Retrieval of Recipes and Food Images

This paper presents a three-tier modality alignment approach to learning...

4 Zhongwei Xie, et al. ∙

research

∙ 08/02/2021

Learning TFIDF Enhanced Joint Embedding for Recipe-Image Cross-Modal Retrieval Service

It is widely acknowledged that learning joint embeddings of recipes with...

8 Zhongwei Xie, et al. ∙

research

∙ 08/02/2021

Efficient Deep Feature Calibration for Cross-Modal Joint Embedding Learning

This paper introduces a two-phase deep feature calibration framework for...

0 Zhongwei Xie, et al. ∙

research

∙ 07/27/2021

Parallel Detection for Efficient Video Analytics at the Edge

Deep Neural Network (DNN) trained object detectors are widely deployed i...

0 Yanzhao Wu, et al. ∙

research

∙ 07/08/2021

PNC Enabled IIoT: A General Framework for Channel-Coded Asymmetric Physical-Layer Network Coding

This paper investigates the application of physical-layer network coding...

0 Zhaorui Wang, 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

∙ 05/19/2021

Computational Morphology with Neural Network Approaches

Neural network approaches have been applied to computational morphology ...

0 Ling Liu, et al. ∙

research

∙ 04/25/2021

RDMAbox : Optimizing RDMA for Memory Intensive Workloads

We present RDMAbox, a set of low level RDMA opti-mizations that provide ...

0 Juhyun Bae, et al. ∙

research

∙ 04/13/2021

Can a Transformer Pass the Wug Test? Tuning Copying Bias in Neural Morphological Inflection Models

Deep learning sequence models have been successfully applied to the task...

0 Ling Liu, et al. ∙

research

∙ 01/25/2021

Set Reconciliation for Blockchains with Slepian-Wolf Coding: Deletion Polar Codes

In this paper, we propose a polar coding based scheme for set reconcilia...

0 Ling Liu, 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

∙ 09/14/2020

Utility-Optimized Synthesis of Differentially Private Location Traces

Differentially private location trace synthesis (DPLTS) has recently eme...

0 Mehmet Emre Gursoy, et al. ∙

research

∙ 08/03/2020

Efficient Orchestration of Host and Remote Shared Memory for Memory Intensive Workloads

Since very few contributions to the development of an unified memory orc...

0 Juhyun Bae, et al. ∙

research

∙ 07/16/2020

Data Poisoning Attacks Against Federated Learning Systems

Federated learning (FL) is an emerging paradigm for distributed training...

0 Vale Tolpegin, 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

∙ 10/18/2019

DLB: Deep Learning Based Load Balancing

Load balancing mechanisms have been widely adopted by distributed platfo...

0 Xiaoke Zhu, et al. ∙

research

∙ 10/09/2019

On adaptivity of wavelet thresholding estimators with negatively super-additive dependent noise

This paper considers the nonparametric regression model with negatively ...

0 Yuncai Yu, 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

∙ 09/25/2019

Decentralized Trust Management: Risk Analysis and Trust Aggregation

Decentralized trust management is used as a referral benchmark for assis...

0 Xinxin Fan, 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

∙ 08/23/2019

Delivering Scientific Influence Analysis as a Service on Research Grants Repository

Research grants have played an important role in seeding and promoting f...

0 Yuming Wang, 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

∙ 07/15/2019

Utility-aware and privacy-preserving mobile query services

Location-based queries enable fundamental services for mobile road netwo...

0 Emre Yigitoglu, et al. ∙

research

∙ 07/15/2019

On the Polarization of Rényi Entropy

Existing polarization theories have mostly been concerned with Shannon's...

0 Mengfan Zheng, et al. ∙

research

∙ 07/08/2019

StackVault: Protection from Untrusted Functions

Data exfiltration attacks have led to huge data breaches. Recently, the ...

0 Qi Zhang, 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

∙ 04/03/2019

Differentially Private Model Publishing for Deep Learning

Deep learning techniques based on neural networks have shown significant...

0 Lei Yu, et al. ∙

Ling Liu

Featured Co-authors