Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds

15 April 2018

Daniela Rus

Papers citing "Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds"

20 / 20 papers shown

Title
Gradient-Free Structured Pruning with Unlabeled Data Azade Nova H. Dai Dale Schuurmans SyDa 37 20 0 07 Mar 2023
Pruning Deep Neural Networks from a Sparsity Perspective Enmao Diao G. Wang Jiawei Zhan Yuhong Yang Jie Ding Vahid Tarokh 27 30 0 11 Feb 2023
Getting Away with More Network Pruning: From Sparsity to Geometry and Linear Regions Junyang Cai Khai-Nguyen Nguyen Nishant Shrestha Aidan Good Ruisen Tu Xin Yu Shandian Zhe Thiago Serra MLT 40 7 0 19 Jan 2023
The Effect of Data Dimensionality on Neural Network Prunability Zachary Ankner Alex Renda Gintare Karolina Dziugaite Jonathan Frankle Tian Jin 28 5 0 01 Dec 2022
Efficient NTK using Dimensionality Reduction Nir Ailon Supratim Shit 28 0 0 10 Oct 2022
Dynamic Selection of Perception Models for Robotic Control Bineet Ghosh Masaad Khan Adithya S Ashok Sandeep Chinchali Parasara Sridhar Duggirala 37 1 0 13 Jul 2022
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm Aidan Good Jia-Huei Lin Hannah Sieg Mikey Ferguson Xin Yu Shandian Zhe J. Wieczorek Thiago Serra 37 11 0 07 Jun 2022
The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks Xin Yu Thiago Serra Srikumar Ramalingam Shandian Zhe 42 48 0 09 Mar 2022
Obstacle Aware Sampling for Path Planning M. Tukan Alaa Maalouf Dan Feldman Roi Poranne 31 8 0 08 Mar 2022
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning Soufiane Hayou Bo He Gintare Karolina Dziugaite 37 2 0 22 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong UQCV MLT 31 13 0 12 Oct 2021
Interpretable Trade-offs Between Robot Task Accuracy and Compute Efficiency Bineet Ghosh Sandeep Chinchali Parasara Sridhar Duggirala 26 3 0 03 Aug 2021
Adversarial Robustness of Streaming Algorithms through Importance Sampling Vladimir Braverman Avinatan Hassidim Yossi Matias Mariano Schain Sandeep Silwal Samson Zhou AAML OOD 24 38 0 28 Jun 2021
Sparse Flows: Pruning Continuous-depth Models Lucas Liebenwein Ramin Hasani Alexander Amini Daniela Rus 26 16 0 24 Jun 2021
Low-Regret Active learning Cenk Baykal Lucas Liebenwein Dan Feldman Daniela Rus UQCV 31 3 0 06 Apr 2021
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy Lucas Liebenwein Cenk Baykal Brandon Carter David K Gifford Daniela Rus AAML 40 71 0 04 Mar 2021
Introduction to Core-sets: an Updated Survey Dan Feldman 9 62 0 18 Nov 2020
On Coresets for Support Vector Machines M. Tukan Cenk Baykal Dan Feldman Daniela Rus 27 27 0 15 Feb 2020
Machine Unlearning Lucas Bourtoule Varun Chandrasekaran Christopher A. Choquette-Choo Hengrui Jia Adelin Travers Baiwu Zhang David Lie Nicolas Papernot MU 29 807 0 09 Dec 2019
Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights Aojun Zhou Anbang Yao Yiwen Guo Lin Xu Yurong Chen MQ 337 1,049 0 10 Feb 2017