Using Cooperative Game Theory to Prune Neural Networks

17 November 2023

Papers citing "Using Cooperative Game Theory to Prune Neural Networks"

7 / 7 papers shown

Title
Explaining Quantum Circuits with Shapley Values: Towards Explainable Quantum Machine Learning R. Heese Thore Gerlach Sascha Mucke Sabine Muller Matthias Jakobs Nico Piatkowski 24 18 0 22 Jan 2023
FastSHAP: Real-Time Shapley Value Estimation N. Jethani Mukund Sudarshan Ian Covert Su-In Lee Rajesh Ranganath TDI FAtt 67 127 0 15 Jul 2021
Negotiating Team Formation Using Deep Reinforcement Learning Yoram Bachrach Richard Everett Edward Hughes Angeliki Lazaridou Joel Z Leibo Marc Lanctot Michael Bradley Johanson Wojciech M. Czarnecki T. Graepel 45 35 0 20 Oct 2020
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Tianlong Chen Jonathan Frankle Shiyu Chang Sijia Liu Yang Zhang Zhangyang Wang Michael Carbin 156 377 0 23 Jul 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 191 1,032 0 06 Mar 2020
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 202 745 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,145 0 06 Jun 2015