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i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery

Dec 07, 2021
Cameron R. Wolfe, Anastasios Kyrillidis

* 27 pages, 4 figures 

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On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons

Dec 05, 2021
Fangshuo Liao, Anastasios Kyrillidis

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Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum

Dec 03, 2021
Junhyung Lyle Kim, Panos Toulis, Anastasios Kyrillidis

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Federated Multiple Label Hashing (FedMLH): Communication Efficient Federated Learning on Extreme Classification Tasks

Oct 23, 2021
Zhenwei Dai, Chen Dun, Yuxin Tang, Anastasios Kyrillidis, Anshumali Shrivastava

* 10 pages, 5 figures 

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Provably Efficient Lottery Ticket Discovery

Jul 31, 2021
Cameron R. Wolfe, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis

* 27 pages, 6 figures 

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REX: Revisiting Budgeted Training with an Improved Schedule

Jul 09, 2021
John Chen, Cameron Wolfe, Anastasios Kyrillidis

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Momentum-inspired Low-Rank Coordinate Descent for Diagonally Constrained SDPs

Jul 03, 2021
Junhyung Lyle Kim, Jose Antonio Lara Benitez, Mohammad Taha Toghani, Cameron Wolfe, Zhiwei Zhang, Anastasios Kyrillidis

* 10 pages, 8 figures, preprint under review 

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ResIST: Layer-Wise Decomposition of ResNets for Distributed Training

Jul 02, 2021
Chen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis

* 11 pages 

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Mitigating deep double descent by concatenating inputs

Jul 02, 2021
John Chen, Qihan Wang, Anastasios Kyrillidis

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Fast quantum state reconstruction via accelerated non-convex programming

Apr 30, 2021
Junhyung Lyle Kim, George Kollias, Amir Kalev, Ken X. Wei, Anastasios Kyrillidis

* 46 pages 

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GIST: Distributed Training for Large-Scale Graph Convolutional Networks

Feb 20, 2021
Cameron R. Wolfe, Jingkang Yang, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis

* 17 pages, 5 figures, pre-print under review 

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Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets

Dec 17, 2020
T. Mitchell Roddenberry, Santiago Segarra, Anastasios Kyrillidis

* 22 pages, 3 figures 

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On Continuous Local BDD-Based Search for Hybrid SAT Solving

Dec 14, 2020
Anastasios Kyrillidis, Moshe Y. Vardi, Zhiwei Zhang

* AAAI 21 

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On Generalization of Adaptive Methods for Over-parameterized Linear Regression

Nov 28, 2020
Vatsal Shah, Soumya Basu, Anastasios Kyrillidis, Sujay Sanghavi

* arXiv admin note: substantial text overlap with arXiv:1811.07055 

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ImCLR: Implicit Contrastive Learning for Image Classification

Nov 25, 2020
John Chen, Samarth Sinha, Anastasios Kyrillidis

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Bayesian Coresets: An Optimization Perspective

Jul 01, 2020
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo

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FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints

Dec 02, 2019
Anastasios Kyrillidis, Anshumali Shrivastava, Moshe Y. Vardi, Zhiwei Zhang

* The paper was accepted by Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020) 

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Optimal Mini-Batch Size Selection for Fast Gradient Descent

Nov 15, 2019
Michael P. Perrone, Haidar Khan, Changhoan Kim, Anastasios Kyrillidis, Jerry Quinn, Valentina Salapura

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Negative sampling in semi-supervised learning

Nov 12, 2019
John Chen, Vatsal Shah, Anastasios Kyrillidis

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Learning Sparse Distributions using Iterative Hard Thresholding

Nov 07, 2019
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo

* NeurIPS 2019 

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Decaying momentum helps neural network training

Oct 11, 2019
John Chen, Anastasios Kyrillidis

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Distributed Learning of Deep Neural Networks using Independent Subnet Training

Oct 04, 2019
Binhang Yuan, Anastasios Kyrillidis, Christopher M. Jermaine

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SysML: The New Frontier of Machine Learning Systems

May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar

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Compressing Gradient Optimizers via Count-Sketches

Feb 26, 2019
Ryan Spring, Anastasios Kyrillidis, Vijai Mohan, Anshumali Shrivastava

* Initially submitted to WWW 2019 (November 2018) 

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Minimum norm solutions do not always generalize well for over-parameterized problems

Nov 16, 2018
Vatsal Shah, Anastasios Kyrillidis, Sujay Sanghavi

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