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 18 17 0 22 Jan 2023
FastSHAP: Real-Time Shapley Value Estimation N. Jethani Mukund Sudarshan Ian Covert Su-In Lee Rajesh Ranganath TDI FAtt 56 120 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 30 33 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 148 345 0 23 Jul 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 172 1,018 0 06 Mar 2020
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference Y. Gal Zoubin Ghahramani UQCV BDL 197 741 0 06 Jun 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015