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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...
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08/19/2023
Explicit Time Embedding Based Cascade Attention Network for Information Popularity Prediction
Predicting information cascade popularity is a fundamental problem in so...
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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...
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05/10/2023
Securing Distributed SGD against Gradient Leakage Threats
This paper presents a holistic approach to gradient leakage resilient di...
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03/21/2023
STDLens: Model Hijacking-Resilient Federated Learning for Object Detection
Federated Learning (FL) has been gaining popularity as a collaborative l...
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03/20/2023
GNN-Ensemble: Towards Random Decision Graph Neural Networks
Graph Neural Networks (GNNs) have enjoyed wide spread applications in gr...
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02/08/2023
Machine Learning for Synthetic Data Generation: a Review
Data plays a crucial role in machine learning. However, in real-world ap...
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01/15/2023
EENet: Learning to Early Exit for Adaptive Inference
Budgeted adaptive inference with early exits is an emerging technique to...
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12/25/2021
Gradient Leakage Attack Resilient Deep Learning
Gradient leakage attacks are considered one of the wickedest privacy thr...
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10/14/2021
Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding
Network representation learning (NRL) advances the conventional graph mi...
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07/10/2021
Speech2Video: Cross-Modal Distillation for Speech to Video Generation
This paper investigates a novel task of talking face video generation so...
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07/02/2021
Gradient-Leakage Resilient Federated Learning
Federated learning(FL) is an emerging distributed learning paradigm with...
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10/20/2020
Promoting High Diversity Ensemble Learning with EnsembleBench
Ensemble learning is gaining renewed interests in recent years. This pap...
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09/14/2020
Robust Deep Learning Ensemble against Deception
Deep neural network (DNN) models are known to be vulnerable to malicious...
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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...
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07/15/2020
Bitcoin Transaction Forecasting with Deep Network Representation Learning
Bitcoin and its decentralized computing paradigm for digital currency tr...
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07/11/2020
Understanding Object Detection Through An Adversarial Lens
Deep neural networks based object detection models have revolutionized c...
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06/05/2020
LDP-Fed: Federated Learning with Local Differential Privacy
This paper presents LDP-Fed, a novel federated learning system with a fo...
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04/22/2020
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning
Federated learning (FL) is an emerging distributed machine learning fram...
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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...
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11/21/2019
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability
Membership inference attacks seek to infer the membership of individual ...
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10/01/2019
Cross-Layer Strategic Ensemble Defense Against Adversarial Examples
Deep neural network (DNN) has demonstrated its success in multiple domai...
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08/29/2019
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness
Ensemble learning is a methodology that integrates multiple DNN learners...
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08/21/2019
Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks
Deep neural networks (DNNs) have demonstrated impressive performance on ...
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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...
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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...
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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 ...
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06/29/2018
Adversarial Examples in Deep Learning: Characterization and Divergence
The burgeoning success of deep learning has raised the security and priv...
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06/28/2018
