The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks

9 March 2018

Papers citing "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks"

50 / 2,030 papers shown

Title
Finding trainable sparse networks through Neural Tangent Transfer Tianlin Liu Friedemann Zenke 67 35 0 15 Jun 2020
Neural gradients are near-lognormal: improved quantized and sparse training Brian Chmiel Liad Ben-Uri Moran Shkolnik Elad Hoffer Ron Banner Daniel Soudry MQ 65 5 0 15 Jun 2020
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient Ankit Pensia Shashank Rajput Alliot Nagle Harit Vishwakarma Dimitris Papailiopoulos 62 104 0 14 Jun 2020
High-contrast "gaudy" images improve the training of deep neural network models of visual cortex Benjamin R. Cowley Jonathan W. Pillow 41 10 0 13 Jun 2020
Dynamic Model Pruning with Feedback Tao R. Lin Sebastian U. Stich Luis Barba Daniil Dmitriev Martin Jaggi 163 204 0 12 Jun 2020
A Practical Sparse Approximation for Real Time Recurrent Learning Jacob Menick Erich Elsen Utku Evci Simon Osindero Karen Simonyan Alex Graves 89 32 0 12 Jun 2020
How many winning tickets are there in one DNN? Kathrin Grosse Michael Backes UQCV 36 2 0 12 Jun 2020
Neural Path Features and Neural Path Kernel : Understanding the role of gates in deep learning Chandrashekar Lakshminarayanan Amit Singh AI4CE 54 10 0 11 Jun 2020
Convolutional neural networks compression with low rank and sparse tensor decompositions Pavel Kaloshin 36 1 0 11 Jun 2020
Pruning neural networks without any data by iteratively conserving synaptic flow Hidenori Tanaka D. Kunin Daniel L. K. Yamins Surya Ganguli 198 650 0 09 Jun 2020
Towards More Practical Adversarial Attacks on Graph Neural Networks Jiaqi Ma Shuangrui Ding Qiaozhu Mei AAML 73 122 0 09 Jun 2020
A Framework for Neural Network Pruning Using Gibbs Distributions Alex Labach S. Valaee 33 5 0 08 Jun 2020
Differentiable Neural Input Search for Recommender Systems Weiyu Cheng Yanyan Shen Linpeng Huang 71 36 0 08 Jun 2020
Neural Sparse Representation for Image Restoration Yuchen Fan Jiahui Yu Yiqun Mei Yulun Zhang Y. Fu Ding Liu Thomas S. Huang 38 31 0 08 Jun 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation Deepan Das Haley Massa Abhimanyu Kulkarni Theodoros Rekatsinas 58 18 0 06 Jun 2020
Accelerating Natural Language Understanding in Task-Oriented Dialog Ojas Ahuja Shrey Desai VLM 20 1 0 05 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 143 99 0 05 Jun 2020
Shapley Value as Principled Metric for Structured Network Pruning Marco Ancona Cengiz Öztireli Markus Gross 60 9 0 02 Jun 2020
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization Mayumi Ohta Nathaniel Berger Artem Sokolov Stefan Riezler ODL 38 9 0 02 Jun 2020
Pruning via Iterative Ranking of Sensitivity Statistics Stijn Verdenius M. Stol Patrick Forré AAML 80 38 0 01 Jun 2020
Transferring Inductive Biases through Knowledge Distillation Samira Abnar Mostafa Dehghani Willem H. Zuidema 90 60 0 31 May 2020
Geometric algorithms for predicting resilience and recovering damage in neural networks G. Raghavan Jiayi Li Matt Thomson AAML 22 0 0 23 May 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 122 151 0 20 May 2020
Dynamic Sparsity Neural Networks for Automatic Speech Recognition Zhaofeng Wu Ding Zhao Qiao Liang Jiahui Yu Anmol Gulati Ruoming Pang 51 41 0 16 May 2020
Joint Progressive Knowledge Distillation and Unsupervised Domain Adaptation Le Thanh Nguyen-Meidine Eric Granger M. Kiran Jose Dolz Louis-Antoine Blais-Morin 78 23 0 16 May 2020
Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers Junjie Liu Zhe Xu Runbin Shi R. Cheung Hayden Kwok-Hay So 62 121 0 14 May 2020
RSO: A Gradient Free Sampling Based Approach For Training Deep Neural Networks Rohun Tripathi Bharat Singh 38 6 0 12 May 2020
On the Transferability of Winning Tickets in Non-Natural Image Datasets M. Sabatelli M. Kestemont Pierre Geurts 62 15 0 11 May 2020
Data-Free Network Quantization With Adversarial Knowledge Distillation Yoojin Choi Jihwan P. Choi Mostafa El-Khamy Jungwon Lee MQ 76 121 0 08 May 2020
Efficient Exact Verification of Binarized Neural Networks Kai Jia Martin Rinard AAML MQ 46 59 0 07 May 2020
Sources of Transfer in Multilingual Named Entity Recognition David Mueller Nicholas Andrews Mark Dredze 50 21 0 02 May 2020
When BERT Plays the Lottery, All Tickets Are Winning Sai Prasanna Anna Rogers Anna Rumshisky MILM 86 187 0 01 May 2020
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima Enzo Tartaglione Andrea Bragagnolo Marco Grangetto 66 12 0 30 Apr 2020
Out-of-the-box channel pruned networks Ragav Venkatesan Gurumurthy Swaminathan Xiong Zhou Anna Luo 29 0 0 30 Apr 2020
Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation Nithin Holla Pushkar Mishra H. Yannakoudakis Ekaterina Shutova 88 28 0 29 Apr 2020
WoodFisher: Efficient Second-Order Approximation for Neural Network Compression Sidak Pal Singh Dan Alistarh 57 28 0 29 Apr 2020
Masking as an Efficient Alternative to Finetuning for Pretrained Language Models Mengjie Zhao Tao R. Lin Fei Mi Martin Jaggi Hinrich Schütze 75 120 0 26 Apr 2020
How fine can fine-tuning be? Learning efficient language models Evani Radiya-Dixit Xin Wang 53 66 0 24 Apr 2020
Convolution-Weight-Distribution Assumption: Rethinking the Criteria of Channel Pruning Zhongzhan Huang Wenqi Shao Xinjiang Wang Liang Lin Ping Luo 75 55 0 24 Apr 2020
SIPA: A Simple Framework for Efficient Networks Gihun Lee Sangmin Bae Jaehoon Oh Seyoung Yun 19 1 0 24 Apr 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 124 176 0 23 Apr 2020
Lottery Hypothesis based Unsupervised Pre-training for Model Compression in Federated Learning Sohei Itahara Takayuki Nishio M. Morikura Koji Yamamoto 49 12 0 21 Apr 2020
Neural Status Registers Lukas Faber Roger Wattenhofer 35 9 0 15 Apr 2020
Prune2Edge: A Multi-Phase Pruning Pipelines to Deep Ensemble Learning in IIoT Besher Alhalabi M. Gaber S. Basurra 18 1 0 09 Apr 2020
LadaBERT: Lightweight Adaptation of BERT through Hybrid Model Compression Yihuan Mao Yujing Wang Chufan Wu Chen Zhang Yang-Feng Wang Yaming Yang Quanlu Zhang Yunhai Tong Jing Bai 58 74 0 08 Apr 2020
Network Adjustment: Channel Search Guided by FLOPs Utilization Ratio Zhengsu Chen J. Niu Lingxi Xie Xuefeng Liu Longhui Wei Qi Tian 54 12 0 06 Apr 2020
Composition of Saliency Metrics for Channel Pruning with a Myopic Oracle Kaveena Persand Andrew Anderson David Gregg 26 2 0 03 Apr 2020
Learning Sparse & Ternary Neural Networks with Entropy-Constrained Trained Ternarization (EC2T) Arturo Marbán Daniel Becking Simon Wiedemann Wojciech Samek MQ 51 12 0 02 Apr 2020
Nonconvex sparse regularization for deep neural networks and its optimality Ilsang Ohn Yongdai Kim 61 19 0 26 Mar 2020
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context Wenyu Zhang Skyler Seto Devesh K. Jha 71 5 0 26 Mar 2020