Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model

Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model

24 May 2022

Sosuke Kobayashi

Papers citing "Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model"

9 / 9 papers shown

Title
Sharpness-diversity tradeoff: improving flat ensembles with SharpBalance Haiquan Lu Xiaotian Liu Yefan Zhou Qunli Li Kurt Keutzer Michael W. Mahoney Yujun Yan Huanrui Yang Yaoqing Yang 38 1 0 17 Jul 2024
Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging Max Zimmer Christoph Spiegel S. Pokutta MoMe 41 14 0 29 Jun 2023
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction Jiefeng Chen Jinsung Yoon Sayna Ebrahimi Sercan Ö. Arik S. Jha Tomas Pfister 28 1 0 07 Apr 2023
Clip-Tuning: Towards Derivative-free Prompt Learning with a Mixture of Rewards Yekun Chai Shuohuan Wang Yu Sun Hao Tian Hua-Hong Wu Haifeng Wang VLM 24 17 0 21 Oct 2022
Multi-CLS BERT: An Efficient Alternative to Traditional Ensembling Haw-Shiuan Chang Ruei-Yao Sun Kathryn Ricci Andrew McCallum 41 14 0 10 Oct 2022
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers Yi Tay Mostafa Dehghani J. Rao W. Fedus Samira Abnar Hyung Won Chung Sharan Narang Dani Yogatama Ashish Vaswani Donald Metzler 198 110 0 22 Sep 2021
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Tianlong Chen Jonathan Frankle Shiyu Chang Sijia Liu Yang Zhang Zhangyang Wang Michael Carbin 150 345 0 23 Jul 2020
What is the State of Neural Network Pruning? Davis W. Blalock Jose Javier Gonzalez Ortiz Jonathan Frankle John Guttag 185 1,027 0 06 Mar 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015