Carbon Emissions and Large Neural Network Training

21 April 2021

Papers citing "Carbon Emissions and Large Neural Network Training"

26 / 126 papers shown

Title
Automated Deep Learning: Neural Architecture Search Is Not the End Xuanyi Dong D. Kedziora Katarzyna Musial Bogdan Gabrys 25 26 0 16 Dec 2021
Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention Yichong Xu Chenguang Zhu Shuohang Wang Siqi Sun Hao Cheng Xiaodong Liu Jianfeng Gao Pengcheng He Michael Zeng Xuedong Huang LRM 254 55 0 06 Dec 2021
Incremental Learning in Semantic Segmentation from Image Labels Fabio Cermelli Dario Fontanel A. Tavera Marco Ciccone Barbara Caputo VLM CLL 35 47 0 03 Dec 2021
Many Heads but One Brain: Fusion Brain -- a Competition and a Single Multimodal Multitask Architecture Daria Bakshandaeva Denis Dimitrov V.Ya. Arkhipkin Alex Shonenkov M. Potanin ... Mikhail Martynov Anton Voronov Vera Davydova E. Tutubalina Aleksandr Petiushko 33 0 0 22 Nov 2021
The Efficiency Misnomer Daoyuan Chen Liuyi Yao Dawei Gao Ashish Vaswani Yaliang Li 34 99 0 25 Oct 2021
Unraveling the Hidden Environmental Impacts of AI Solutions for Environment Anne-Laure Ligozat J. Lefèvre Aurélie Bugeau Jacques Combaz 24 94 0 22 Oct 2021
A Loss Curvature Perspective on Training Instability in Deep Learning Justin Gilmer Behrooz Ghorbani Ankush Garg Sneha Kudugunta Behnam Neyshabur David E. Cardoze George E. Dahl Zachary Nado Orhan Firat ODL 36 35 0 08 Oct 2021
Exploring Heterogeneous Characteristics of Layers in ASR Models for More Efficient Training Lillian Zhou Dhruv Guliani Andreas Kabel Giovanni Motta F. Beaufays 23 1 0 08 Oct 2021
Towards Continual Knowledge Learning of Language Models Joel Jang Seonghyeon Ye Sohee Yang Joongbo Shin Janghoon Han Gyeonghun Kim Stanley Jungkyu Choi Minjoon Seo CLL KELM 230 151 0 07 Oct 2021
Exploring the Limits of Large Scale Pre-training Samira Abnar Mostafa Dehghani Behnam Neyshabur Hanie Sedghi AI4CE 60 114 0 05 Oct 2021
Perhaps PTLMs Should Go to School -- A Task to Assess Open Book and Closed Book QA Manuel R. Ciosici Joe Cecil Alex Hedges Dong-Ho Lee Marjorie Freedman R. Weischedel 25 9 0 04 Oct 2021
Prune Your Model Before Distill It Jinhyuk Park Albert No VLM 46 27 0 30 Sep 2021
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 206 110 0 22 Sep 2021
Primer: Searching for Efficient Transformers for Language Modeling David R. So Wojciech Mañke Hanxiao Liu Zihang Dai Noam M. Shazeer Quoc V. Le VLM 88 152 0 17 Sep 2021
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers Boseop Kim Hyoungseok Kim Sang-Woo Lee Gichang Lee Donghyun Kwak ... Jaewook Kang Inho Kang Jung-Woo Ha W. Park Nako Sung VLM 249 121 0 10 Sep 2021
Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision Bo-wen Li Xinyang Jiang Donglin Bai Yuge Zhang Ningxin Zheng Xuanyi Dong Lu Liu Yuqing Yang Dongsheng Li 14 10 0 30 Aug 2021
Dynamic Neural Network Architectural and Topological Adaptation and Related Methods -- A Survey Lorenz Kummer AI4CE 40 0 0 28 Jul 2021
Deduplicating Training Data Makes Language Models Better Katherine Lee Daphne Ippolito A. Nystrom Chiyuan Zhang Douglas Eck Chris Callison-Burch Nicholas Carlini SyDa 242 593 0 14 Jul 2021
The MultiBERTs: BERT Reproductions for Robustness Analysis Thibault Sellam Steve Yadlowsky Jason W. Wei Naomi Saphra Alexander DÁmour ... Iulia Turc Jacob Eisenstein Dipanjan Das Ian Tenney Ellie Pavlick 24 93 0 30 Jun 2021
Sparse Training via Boosting Pruning Plasticity with Neuroregeneration Shiwei Liu Tianlong Chen Xiaohan Chen Zahra Atashgahi Lu Yin Huanyu Kou Li Shen Mykola Pechenizkiy Zhangyang Wang D. Mocanu 34 111 0 19 Jun 2021
BoolNet: Minimizing The Energy Consumption of Binary Neural Networks Nianhui Guo Joseph Bethge Haojin Yang Kai Zhong Xuefei Ning Christoph Meinel Yu Wang MQ 24 11 0 13 Jun 2021
Scaling Vision with Sparse Mixture of Experts C. Riquelme J. Puigcerver Basil Mustafa Maxim Neumann Rodolphe Jenatton André Susano Pinto Daniel Keysers N. Houlsby MoE 17 575 0 10 Jun 2021
Mind the Gap: Assessing Temporal Generalization in Neural Language Models Angeliki Lazaridou A. Kuncoro E. Gribovskaya Devang Agrawal Adam Liska ... Sebastian Ruder Dani Yogatama Kris Cao Susannah Young Phil Blunsom VLM 41 207 0 03 Feb 2021
Measuring the Algorithmic Efficiency of Neural Networks Danny Hernandez Tom B. Brown 241 94 0 08 May 2020
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 261 4,489 0 23 Jan 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,212 0 23 Aug 2019