Predicting Parameters in Deep Learning

3 June 2013

Papers citing "Predicting Parameters in Deep Learning"

50 / 240 papers shown

Title
Learning Compressed Transforms with Low Displacement Rank Anna T. Thomas Albert Gu Tri Dao Atri Rudra Christopher Ré 27 40 0 04 Oct 2018
Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams Mahardhika Pratama Andri Ashfahani Yew-Soon Ong Savitha Ramasamy E. Lughofer 14 15 0 24 Sep 2018
2PFPCE: Two-Phase Filter Pruning Based on Conditional Entropy Chuhan Min Aosen Wang Yiran Chen Wenyao Xu Xin Chen 30 41 0 06 Sep 2018
A Survey on Methods and Theories of Quantized Neural Networks Yunhui Guo MQ 34 232 0 13 Aug 2018
LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks Dongqing Zhang Jiaolong Yang Dongqiangzi Ye G. Hua MQ 23 697 0 26 Jul 2018
Filter Distillation for Network Compression Xavier Suau Luca Zappella N. Apostoloff 24 38 0 20 Jul 2018
Automatic Rank Selection for High-Speed Convolutional Neural Network Hyeji Kim C. Kyung 27 5 0 28 Jun 2018
Scalable Neural Network Compression and Pruning Using Hard Clustering and L1 Regularization Yibo Yang Nicholas Ruozzi Vibhav Gogate 21 2 0 14 Jun 2018
EasyConvPooling: Random Pooling with Easy Convolution for Accelerating Training and Testing Jianzhong Sheng Chuanbo Chen Chenchen Fu Chun Jason Xue 24 4 0 05 Jun 2018
Grow and Prune Compact, Fast, and Accurate LSTMs Xiaoliang Dai Hongxu Yin N. Jha VLM SyDa 31 90 0 30 May 2018
Compact and Computationally Efficient Representation of Deep Neural Networks Simon Wiedemann K. Müller Wojciech Samek MQ 42 67 0 27 May 2018
Deploy Large-Scale Deep Neural Networks in Resource Constrained IoT Devices with Local Quantization Region Yi Yang A. Chen Xiaoming Chen Jiang Ji Zhenyang Chen Yan Dai MQ 18 11 0 24 May 2018
AutoPruner: An End-to-End Trainable Filter Pruning Method for Efficient Deep Model Inference Jian-Hao Luo Jianxin Wu 18 207 0 23 May 2018
Object detection at 200 Frames Per Second Rakesh Mehta Cemalettin Öztürk ObjD 37 61 0 16 May 2018
Measuring the Intrinsic Dimension of Objective Landscapes Chunyuan Li Heerad Farkhoor Rosanne Liu J. Yosinski 38 401 0 24 Apr 2018
Fast inference of deep neural networks in FPGAs for particle physics Javier Mauricio Duarte Song Han Philip C. Harris S. Jindariani E. Kreinar ... J. Ngadiuba M. Pierini R. Rivera N. Tran Zhenbin Wu AI4CE 88 389 0 16 Apr 2018
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds Cenk Baykal Lucas Liebenwein Igor Gilitschenski Dan Feldman Daniela Rus 25 79 0 15 Apr 2018
A Systematic DNN Weight Pruning Framework using Alternating Direction Method of Multipliers Tianyun Zhang Shaokai Ye Kaiqi Zhang Jian Tang Wujie Wen M. Fardad Yanzhi Wang 30 434 0 10 Apr 2018
The Loss Surface of XOR Artificial Neural Networks D. Mehta Xiaojun Zhao Edgar A. Bernal D. Wales 34 19 0 06 Apr 2018
Neural Network Quine Oscar Chang Hod Lipson 21 23 0 15 Mar 2018
Deep Neural Network Compression with Single and Multiple Level Quantization Yuhui Xu Yongzhuang Wang Aojun Zhou Weiyao Lin H. Xiong MQ 20 114 0 06 Mar 2018
Compressing Neural Networks using the Variational Information Bottleneck Bin Dai Chen Zhu David Wipf MLT 28 179 0 28 Feb 2018
Attention-Based Guided Structured Sparsity of Deep Neural Networks A. Torfi Rouzbeh A. Shirvani Sobhan Soleymani Nasser M. Nasrabadi 29 23 0 13 Feb 2018
VIBNN: Hardware Acceleration of Bayesian Neural Networks R. Cai Ao Ren Ning Liu Caiwen Ding Luhao Wang Xuehai Qian Massoud Pedram Yanzhi Wang BDL 49 87 0 02 Feb 2018
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks Deepak Mittal S. Bhardwaj Mitesh M. Khapra Balaraman Ravindran VLM 36 65 0 31 Jan 2018
Learning to Prune Filters in Convolutional Neural Networks Qiangui Huang S. Kevin Zhou Suya You Ulrich Neumann VLM 28 177 0 23 Jan 2018
Focus: Querying Large Video Datasets with Low Latency and Low Cost Kevin Hsieh Ganesh Ananthanarayanan P. Bodík P. Bahl Matthai Philipose Phillip B. Gibbons O. Mutlu 27 275 0 10 Jan 2018
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition Jinmian Ye Linnan Wang Guangxi Li Di Chen Shandian Zhe Xinqi Chu Zenglin Xu 29 132 0 14 Dec 2017
FFT-Based Deep Learning Deployment in Embedded Systems Sheng Lin Ning Liu M. Nazemi Hongjia Li Caiwen Ding Yanzhi Wang Massoud Pedram 41 52 0 13 Dec 2017
Automated Pruning for Deep Neural Network Compression Franco Manessi A. Rozza Simone Bianco Paolo Napoletano Raimondo Schettini 44 56 0 05 Dec 2017
Deep Expander Networks: Efficient Deep Networks from Graph Theory Ameya Prabhu G. Varma A. Namboodiri GNN 30 71 0 23 Nov 2017
NISP: Pruning Networks using Neuron Importance Score Propagation Ruichi Yu Ang Li Chun-Fu Chen Jui-Hsin Lai Vlad I. Morariu Xintong Han M. Gao Ching-Yung Lin L. Davis 44 795 0 16 Nov 2017
Compression-aware Training of Deep Networks J. Álvarez Mathieu Salzmann 21 172 0 07 Nov 2017
Moonshine: Distilling with Cheap Convolutions Elliot J. Crowley Gavia Gray Amos Storkey 33 120 0 07 Nov 2017
Wider and Deeper, Cheaper and Faster: Tensorized LSTMs for Sequence Learning Zhen He Shaobing Gao Liang Xiao Daxue Liu Hangen He David Barber AIMat 37 64 0 05 Nov 2017
Accelerating Training of Deep Neural Networks via Sparse Edge Processing Sourya Dey Yinan Shao K. Chugg P. Beerel 30 16 0 03 Nov 2017
Knowledge Projection for Deep Neural Networks Zhi Zhang G. Ning Zhihai He 38 15 0 26 Oct 2017
Trace norm regularization and faster inference for embedded speech recognition RNNs Markus Kliegl Siddharth Goyal Kexin Zhao Kavya Srinet M. Shoeybi 40 8 0 25 Oct 2017
A Survey of Model Compression and Acceleration for Deep Neural Networks Yu Cheng Duo Wang Pan Zhou Zhang Tao 40 1,087 0 23 Oct 2017
Learning Intrinsic Sparse Structures within Long Short-Term Memory W. Wen Yuxiong He Samyam Rajbhandari Minjia Zhang Wenhan Wang Fang Liu Bin Hu Yiran Chen H. Li MQ 35 140 0 15 Sep 2017
DeepFense: Online Accelerated Defense Against Adversarial Deep Learning B. Rouhani Mohammad Samragh Mojan Javaheripi T. Javidi F. Koushanfar AAML 12 15 0 08 Sep 2017
Neuron Pruning for Compressing Deep Networks using Maxout Architectures Fernando Moya Rueda René Grzeszick G. Fink CVBM 22 17 0 21 Jul 2017
Model compression as constrained optimization, with application to neural nets. Part II: quantization M. A. Carreira-Perpiñán Yerlan Idelbayev MQ 28 37 0 13 Jul 2017
Network Sketching: Exploiting Binary Structure in Deep CNNs Yiwen Guo Anbang Yao Hao Zhao Yurong Chen MQ 37 95 0 07 Jun 2017
IDK Cascades: Fast Deep Learning by Learning not to Overthink Xin Wang Yujia Luo D. Crankshaw Alexey Tumanov Fisher Yu Joseph E. Gonzalez 35 107 0 03 Jun 2017
Kronecker Recurrent Units C. Jose Moustapha Cissé François Fleuret ODL 24 45 0 29 May 2017
Bayesian Compression for Deep Learning Christos Louizos Karen Ullrich Max Welling UQCV BDL 23 479 0 24 May 2017
Compressing Recurrent Neural Network with Tensor Train Andros Tjandra S. Sakti Satoshi Nakamura 31 109 0 23 May 2017
Towards thinner convolutional neural networks through Gradually Global Pruning Z. Wang Ce Zhu Zhiqiang Xia Qi Guo Yipeng Liu CVBM 22 4 0 29 Mar 2017
Soft Weight-Sharing for Neural Network Compression Karen Ullrich Edward Meeds Max Welling 37 412 0 13 Feb 2017