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05/09/2023
Towards Building the Federated GPT: Federated Instruction Tuning
While “instruction-tuned" generative large language models (LLMs) have d...
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12/28/2022
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning
Federated Learning (FL) has received increasing attention due to its pri...
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10/06/2022
Join-Chain Network: A Logical Reasoning View of the Multi-head Attention in Transformer
Developing neural architectures that are capable of logical reasoning ha...
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09/30/2022
Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction
Due to limited communication capacities of edge devices, most existing f...
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09/08/2022
FADE: Enabling Large-Scale Federated Adversarial Training on Resource-Constrained Edge Devices
Adversarial Training (AT) has been proven to be an effective method of i...
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05/30/2022
A Small Leak Will Sink Many Ships: Vulnerabilities Related to Mini Programs Permissions
As a new format of mobile application, mini programs, which function wit...
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05/30/2022
GAN-based Medical Image Small Region Forgery Detection via a Two-Stage Cascade Framework
Using generative adversarial network (GAN)<cit.> for data enhancement of...
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04/27/2021
Towards Fair Federated Learning with Zero-Shot Data Augmentation
Federated learning has emerged as an important distributed learning para...
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02/26/2021
Safe Distributional Reinforcement Learning
Safety in reinforcement learning (RL) is a key property in both training...
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02/10/2021
FLOP: Federated Learning on Medical Datasets using Partial Networks
The outbreak of COVID-19 Disease due to the novel coronavirus has caused...
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04/29/2019
Typer vs. CAPTCHA: Private information based CAPTCHA to defend against crowdsourcing human cheating
Crowdsourcing human-solving or online typing attacks are destructive pro...
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03/30/2019
Medical Imaging Device Security: An Exploratory Study
Recent years have witnessed a boom of connected medical devices, which b...
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02/11/2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
The posteriors over neural network weights are high dimensional and mult...
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11/21/2018
Self-Adversarially Learned Bayesian Sampling
Scalable Bayesian sampling is playing an important role in modern machin...
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11/20/2018
Variance Reduction in Stochastic Particle-Optimization Sampling
Stochastic particle-optimization sampling (SPOS) is a recently-developed...
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09/05/2018