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12/16/2022
Federated Learning with Flexible Control
Federated learning (FL) enables distributed model training from local da...
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04/13/2022
Joint Coreset Construction and Quantization for Distributed Machine Learning
Coresets are small, weighted summaries of larger datasets, aiming at pro...
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02/08/2021
Communication-efficient k-Means for Edge-based Machine Learning
We consider the problem of computing the k-means centers for a large hig...
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11/09/2020
Resource Allocation in One-dimensional Distributed Service Networks with Applications
We consider assignment policies that allocate resources to users, where ...
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11/03/2020
You Do (Not) Belong Here: Detecting DPI Evasion Attacks with Context Learning
As Deep Packet Inspection (DPI) middleboxes become increasingly popular,...
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07/19/2020
Connecting the Dots: Detecting Adversarial Perturbations Using Context Inconsistency
There has been a recent surge in research on adversarial perturbations t...
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07/06/2020
Sharing Models or Coresets: A Study based on Membership Inference Attack
Distributed machine learning generally aims at training a global model b...
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01/29/2020
A4 : Evading Learning-based Adblockers
Efforts by online ad publishers to circumvent traditional ad blockers to...
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05/23/2019
Geometric Laplacian Eigenmap Embedding
Graph embedding seeks to build a low-dimensional representation of a gra...
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05/13/2019
Learning and Planning in Feature Deception Games
Today's high-stakes adversarial interactions feature attackers who const...
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04/11/2019
Robust Coreset Construction for Distributed Machine Learning
Motivated by the need of solving machine learning problems over distribu...
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01/08/2019
Resource Allocation in One-dimensional Distributed Service Networks
We consider assignment policies that allocate resources to users, where ...
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01/08/2019