N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning

18 September 2017

Papers citing "N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning"

23 / 23 papers shown

Title
Robust low-rank training via approximate orthonormal constraints Dayana Savostianova Emanuele Zangrando Gianluca Ceruti Francesco Tudisco 18 9 0 02 Jun 2023
Combining Multi-Objective Bayesian Optimization with Reinforcement Learning for TinyML M. Deutel G. Kontes Christopher Mutschler Jürgen Teich 39 0 0 23 May 2023
Automatic Attention Pruning: Improving and Automating Model Pruning using Attentions Kaiqi Zhao Animesh Jain Ming Zhao 19 9 0 14 Mar 2023
NAS-based Recursive Stage Partial Network (RSPNet) for Light-Weight Semantic Segmentation Yi-Chun Wang J. Hsieh Ming-Ching Chang 18 1 0 03 Oct 2022
Distributed Training for Deep Learning Models On An Edge Computing Network Using ShieldedReinforcement Learning Tanmoy Sen Haiying Shen OffRL 11 5 0 01 Jun 2022
DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices Xueyu Hou Yongjie Guan Tao Han Ning Zhang 9 41 0 03 Feb 2022
Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient Distillation Sumanth Chennupati Mohammad Mahdi Kamani Zhongwei Cheng Lin Chen 19 4 0 19 Oct 2021
Self-paced Resistance Learning against Overfitting on Noisy Labels Xiaoshuang Shi Zhenhua Guo Fuyong Xing Yun Liang Xiaofeng Zhu NoLa 19 20 0 07 May 2021
Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression Cody Blakeney Xiaomin Li Yan Yan Ziliang Zong 27 39 0 05 Dec 2020
Knowledge Distillation: A Survey Jianping Gou B. Yu Stephen J. Maybank Dacheng Tao VLM 19 2,835 0 09 Jun 2020
An Overview of Neural Network Compression James OÑeill AI4CE 40 98 0 05 Jun 2020
A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions Pengzhen Ren Yun Xiao Xiaojun Chang Po-Yao (Bernie) Huang Zhihui Li Xiaojiang Chen Xin Wang AI4CE 29 653 0 01 Jun 2020
Residual Knowledge Distillation Mengya Gao Yujun Shen Quanquan Li Chen Change Loy 6 28 0 21 Feb 2020
PoPS: Policy Pruning and Shrinking for Deep Reinforcement Learning Dor Livne Kobi Cohen 24 50 0 14 Jan 2020
Towards Oracle Knowledge Distillation with Neural Architecture Search Minsoo Kang Jonghwan Mun Bohyung Han FedML 20 43 0 29 Nov 2019
Distilled Siamese Networks for Visual Tracking Jianbing Shen Yuanpei Liu Xingping Dong Xiankai Lu F. Khan S. Hoi 11 101 0 24 Jul 2019
Similarity-Preserving Knowledge Distillation Frederick Tung Greg Mori 39 957 0 23 Jul 2019
OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks Jiashi Li Q. Qi Jingyu Wang Ce Ge Yujian Betterest Li Zhangzhang Yue Haifeng Sun BDL CML 13 53 0 28 May 2019
Auto Deep Compression by Reinforcement Learning Based Actor-Critic Structure Hamed Hakkak OffRL AI4CE 13 1 0 08 Jul 2018
Resource-Efficient Neural Architect Yanqi Zhou S. Ebrahimi Sercan Ö. Arik Haonan Yu Hairong Liu G. Diamos 9 64 0 12 Jun 2018
Path-Level Network Transformation for Efficient Architecture Search Han Cai Jiacheng Yang Weinan Zhang Song Han Yong Yu 19 210 0 07 Jun 2018
AMC: AutoML for Model Compression and Acceleration on Mobile Devices Yihui He Ji Lin Zhijian Liu Hanrui Wang Li-Jia Li Song Han 33 1,339 0 10 Feb 2018
Neural Architecture Search with Reinforcement Learning Barret Zoph Quoc V. Le 264 5,326 0 05 Nov 2016