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02/09/2023
Distributed Learning with Curious and Adversarial Machines
The ubiquity of distributed machine learning (ML) in sensitive public do...
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11/16/2022
Impact of Redundancy on Resilience in Distributed Optimization and Learning
This report considers the problem of resilient distributed optimization ...
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09/30/2022
SoK: On the Impossible Security of Very Large Foundation Models
Large machine learning models, or so-called foundation models, aim to se...
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09/22/2022
Making Byzantine Decentralized Learning Efficient
Decentralized-SGD (D-SGD) distributes heavy learning tasks across multip...
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05/24/2022
Byzantine Machine Learning Made Easy by Resilient Averaging of Momentums
Byzantine resilience emerged as a prominent topic within the distributed...
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10/21/2021
Utilizing Redundancy in Cost Functions for Resilience in Distributed Optimization and Learning
This paper considers the problem of resilient distributed optimization a...
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10/08/2021
Combining Differential Privacy and Byzantine Resilience in Distributed SGD
Privacy and Byzantine resilience (BR) are two crucial requirements of mo...
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08/26/2021
Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy
We consider the problem of Byzantine fault-tolerance in federated machin...
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08/19/2021
On Accelerating Distributed Convex Optimizations
This paper studies a distributed multi-agent convex optimization problem...
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06/07/2021
Asynchronous Distributed Optimization with Redundancy in Cost Functions
This paper considers the problem of asynchronous distributed multi-agent...
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02/16/2021
Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?
This paper addresses the problem of combining Byzantine resilience with ...
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01/28/2021
Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent
We consider the problem of Byzantine fault-tolerance in the peer-to-peer...
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01/26/2021
Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem
This paper considers the problem of multi-agent distributed linear regre...
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01/22/2021
Approximate Byzantine Fault-Tolerance in Distributed Optimization
We consider the problem of Byzantine fault-tolerance in distributed mult...
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11/15/2020
Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning
This paper considers the multi-agent distributed linear least-squares pr...
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09/30/2020
Byzantine Fault-Tolerance in Decentralized Optimization under Minimal Redundancy
This paper considers the problem of Byzantine fault-tolerance in multi-a...
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08/11/2020
Byzantine Fault-Tolerant Distributed Machine Learning Using Stochastic Gradient Descent (SGD) and Norm-Based Comparative Gradient Elimination (CGE)
This report considers the problem of Byzantine fault-tolerance in homoge...
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08/06/2020
Iterative Pre-Conditioning for Expediting the Gradient-Descent Method: The Distributed Linear Least-Squares Problem
This paper considers the multi-agent linear least-squares problem in a s...
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04/03/2020
Preserving Statistical Privacy in Distributed Optimization
We propose a distributed optimization algorithm that, additionally, pres...
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03/21/2020
Resilience in Collaborative Optimization: Redundant and Independent Cost Functions
This report considers the problem of Byzantine fault-tolerance in multi-...
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03/13/2020
Iterative Pre-Conditioning to Expedite the Gradient-Descent Method
Gradient-descent method is one of the most widely used and perhaps the m...
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12/19/2019
Randomized Reactive Redundancy for Byzantine Fault-Tolerance in Parallelized Learning
This report considers the problem of Byzantine fault-tolerance in synchr...
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03/20/2019
Statistical Privacy in Distributed Average Consensus on Bounded Real Inputs
This paper proposes a privacy protocol for distributed average consensus...
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03/20/2019