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09/01/2023
Randomized Polar Codes for Anytime Distributed Machine Learning
We present a novel distributed computing framework that is robust to slo...
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04/27/2023
Moccasin: Efficient Tensor Rematerialization for Neural Networks
The deployment and training of neural networks on edge computing devices...
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03/18/2022
Distributed Sketching for Randomized Optimization: Exact Characterization, Concentration and Lower Bounds
We consider distributed optimization methods for problems where forming ...
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07/12/2021
Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions
Generative Adversarial Networks (GANs) are commonly used for modeling co...
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05/04/2021
Training Quantized Neural Networks to Global Optimality via Semidefinite Programming
Neural networks (NNs) have been extremely successful across many tasks i...
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01/07/2021
Neural Spectrahedra and Semidefinite Lifts: Global Convex Optimization of Polynomial Activation Neural Networks in Fully Polynomial-Time
The training of two-layer neural networks with nonlinear activation func...
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07/02/2020
Debiasing Distributed Second Order Optimization with Surrogate Sketching and Scaled Regularization
In distributed second order optimization, a standard strategy is to aver...
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02/16/2020
Distributed Averaging Methods for Randomized Second Order Optimization
We consider distributed optimization problems where forming the Hessian ...
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02/16/2020
Distributed Sketching Methods for Privacy Preserving Regression
In this work, we study distributed sketching methods for large scale reg...
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07/13/2019
Distributed Black-Box Optimization via Error Correcting Codes
We introduce a novel distributed derivative-free optimization framework ...
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01/21/2019
Polar Coded Distributed Matrix Multiplication
We propose a polar coding mechanism for distributed matrix multiplicatio...
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12/31/2018
