Publication

Adaptation and Learning Over Networks Under Subspace Constraints-Part I: Stability Analysis

Publications associées (32)

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Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

PLMR2023

Results on Sparse Integer Programming and Geometric Independent Sets

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An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

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Universal and adaptive methods for robust stochastic optimization

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In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

2023

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The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in ...

2023

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Distributed systems designers typically strive to improve performance and preserve availability despite failures or attacks; but, when strong consistency is also needed, they encounter fundamental limitations. The bottleneck is in replica coordination, whi ...

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Hypergraph-Based Fast Distributed AC Power Flow Optimization

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IEEE2023

Adaptation and Learning Over Networks Under Subspace Constraints-Part I: Stability Analysis

Robust Collaborative Learning with Linear Gradient Overhead

Results on Sparse Integer Programming and Geometric Independent Sets

Universal and adaptive methods for robust stochastic optimization

Fairness and Explainability in Clustering Problems

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Stochastic adaptive resampling for the estimation of discrete choice models

Bayesian reconstruction of memories stored in neural networks from their connectivity

Building Strongly-Consistent Systems Resilient to Failures, Partitions, and Slowdowns

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Graph Chatbot

Robust Collaborative Learning with Linear Gradient Overhead

Results on Sparse Integer Programming and Geometric Independent Sets

Universal and adaptive methods for robust stochastic optimization

Fairness and Explainability in Clustering Problems

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Stochastic adaptive resampling for the estimation of discrete choice models

Bayesian reconstruction of memories stored in neural networks from their connectivity

Building Strongly-Consistent Systems Resilient to Failures, Partitions, and Slowdowns

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Hypergraph-Based Fast Distributed AC Power Flow Optimization

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search