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09/07/2023
MS-UNet-v2: Adaptive Denoising Method and Training Strategy for Medical Image Segmentation with Small Training Data
Models based on U-like structures have improved the performance of medic...
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07/27/2023
Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance
Many studies have proposed machine-learning (ML) models for malware dete...
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04/18/2023
BadVFL: Backdoor Attacks in Vertical Federated Learning
Federated learning (FL) enables multiple parties to collaboratively trai...
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12/13/2022
Towards Efficient and Domain-Agnostic Evasion Attack with High-dimensional Categorical Inputs
Our work targets at searching feasible adversarial perturbation to attac...
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12/13/2022
AdvCat: Domain-Agnostic Robustness Assessment for Cybersecurity-Critical Applications with Categorical Inputs
Machine Learning-as-a-Service systems (MLaaS) have been largely develope...
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09/07/2022
Cerberus: Exploring Federated Prediction of Security Events
Modern defenses against cyberattacks increasingly rely on proactive appr...
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06/29/2021
Attack Transferability Characterization for Adversarially Robust Multi-label Classification
Despite of the pervasive existence of multi-label evasion attack, it is ...
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12/17/2020
Characterizing the Evasion Attackability of Multi-label Classifiers
Evasion attack in multi-label learning systems is an interesting, widely...
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12/19/2019
Robust Multi-Output Learning with Highly Incomplete Data via Restricted Boltzmann Machines
In a standard multi-output classification scenario, both features and la...
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11/17/2019
Prototypical Networks for Multi-Label Learning
We propose to address multi-label learning by jointly estimating the dis...
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05/08/2019
Robust Federated Training via Collaborative Machine Teaching using Trusted Instances
Federated learning performs distributed model training using local data ...
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05/07/2019
Collaborative and Privacy-Preserving Machine Teaching via Consensus Optimization
In this work, we define a collaborative and privacy-preserving machine t...
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07/07/2016
Mini-Batch Spectral Clustering
The cost of computing the spectrum of Laplacian matrices hinders the app...
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10/19/2012
