42 citations · 207 across the 76 of their papers we have counts for
5 papers · 1 filter
Training set cleansing of backdoor poisoning by self-supervised representation learning
H. Wang, S. Karami, O. Dia +6
A backdoor or Trojan attack is an important type of data poisoning attack against deep neural network (DNN) classifiers, wherein the training dataset is poisoned with a small numbe…
Analysis of Distributed Deep Learning in the Cloud
Aakash Sharma, Vivek M. Bhasi, Sonali Singh +6
We aim to resolve this problem by introducing a comprehensive distributed deep learning (DDL) profiler, which can determine the various execution "stalls" that DDL suffers from whi…
Cluster Resource Management for Dynamic Workloads by Online Optimization
Nader Alfares, George Kesidis, Ata Fatahi Baarzi +1
Over the past ten years, many different approaches have been proposed for different aspects of the problem of resources management for long running, dynamic and diverse workloads s…
MM-BD: Post-Training Detection of Backdoor Attacks with Arbitrary Backdoor Pattern Types Using a Maximum Margin Statistic
Hang Wang, Zhen Xiang, David J. Miller +1
Backdoor attacks are an important type of adversarial threat against deep neural network classifiers, wherein test samples from one or more source classes will be (mis)classified t…
Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios
Zhen Xiang, David J. Miller, George Kesidis
Backdoor attacks (BAs) are an emerging threat to deep neural network classifiers. A victim classifier will predict to an attacker-desired target class whenever a test sample is emb…