Predicting Parameters in Deep Learning

3 June 2013

Papers citing "Predicting Parameters in Deep Learning"

50 / 240 papers shown

Title
Backpropagation Neural Tree Varun Ojha Giuseppe Nicosia BDL 36 14 0 04 Feb 2022
Auto-Compressing Subset Pruning for Semantic Image Segmentation Konstantin Ditschuneit Johannes Otterbach 21 5 0 26 Jan 2022
Network Compression via Central Filter Y. Duan Xiaofang Hu Yue Zhou Qiang Liu Shukai Duan 3DPC 19 1 0 10 Dec 2021
A New Measure of Model Redundancy for Compressed Convolutional Neural Networks Feiqing Huang Yuefeng Si Yao Zheng Guodong Li 39 1 0 09 Dec 2021
Neural Network Quantization for Efficient Inference: A Survey Olivia Weng MQ 28 23 0 08 Dec 2021
Low-rank Tensor Decomposition for Compression of Convolutional Neural Networks Using Funnel Regularization Bo-Shiuan Chu Che-Rung Lee 26 11 0 07 Dec 2021
Gabor filter incorporated CNN for compression Akihiro Imamura N. Arizumi CVBM 28 2 0 29 Oct 2021
S-Cyc: A Learning Rate Schedule for Iterative Pruning of ReLU-based Networks Shiyu Liu Chong Min John Tan Mehul Motani CLL 29 4 0 17 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks Shuai Zhang Meng Wang Sijia Liu Pin-Yu Chen Jinjun Xiong UQCV MLT 31 13 0 12 Oct 2021
Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks Ghada Sokar Decebal Constantin Mocanu Mykola Pechenizkiy CLL 35 8 0 11 Oct 2021
Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values Zhenquan Lin K. Guo Xiaofen Xing Xiangmin Xu ODL 24 1 0 09 Oct 2021
Convolutional Neural Network Compression through Generalized Kronecker Product Decomposition Marawan Gamal Abdel Hameed Marzieh S. Tahaei A. Mosleh V. Nia 47 25 0 29 Sep 2021
Comfetch: Federated Learning of Large Networks on Constrained Clients via Sketching Tahseen Rabbani Brandon Yushan Feng Marco Bornstein Kyle Rui Sang Yifan Yang Arjun Rajkumar A. Varshney Furong Huang FedML 61 2 0 17 Sep 2021
$On the Compression of Neural Networks Using $\ell_0$-Norm Regularization and Weight Pruning$ On the Compression of Neural Networks Using $\ell_0$ -Norm Regularization and Weight Pruning F. Oliveira E. Batista R. Seara 20 9 0 10 Sep 2021
Learning the hypotheses space from data through a U-curve algorithm Diego Marcondes Adilson Simonis Junior Barrera 39 1 0 08 Sep 2021
Greenformers: Improving Computation and Memory Efficiency in Transformer Models via Low-Rank Approximation Samuel Cahyawijaya 31 12 0 24 Aug 2021
InsPose: Instance-Aware Networks for Single-Stage Multi-Person Pose Estimation Dahu Shi Xing Wei Xiaodong Yu Wenming Tan Ye Ren Shiliang Pu 3DH 43 30 0 19 Jul 2021
Training Compact CNNs for Image Classification using Dynamic-coded Filter Fusion Mingbao Lin Bohong Chen Rongrong Ji Rongrong Ji VLM 35 23 0 14 Jul 2021
Learning Gradual Argumentation Frameworks using Genetic Algorithms J. Spieler Nico Potyka Steffen Staab AI4CE 36 4 0 25 Jun 2021
Knowledge Distillation via Instance-level Sequence Learning Haoran Zhao Xin Sun Junyu Dong Zihe Dong Qiong Li 34 23 0 21 Jun 2021
Spectral Pruning for Recurrent Neural Networks Takashi Furuya Kazuma Suetake K. Taniguchi Hiroyuki Kusumoto Ryuji Saiin Tomohiro Daimon 27 4 0 23 May 2021
Initialization and Regularization of Factorized Neural Layers M. Khodak Neil A. Tenenholtz Lester W. Mackey Nicolò Fusi 65 56 0 03 May 2021
Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation Mengyao Zhai Lei Chen Jiawei He Megha Nawhal Frederick Tung Greg Mori CLL 38 28 0 24 Apr 2021
Compacting Deep Neural Networks for Internet of Things: Methods and Applications Ke Zhang Hanbo Ying Hongning Dai Lin Li Yuangyuang Peng Keyi Guo Hongfang Yu 21 38 0 20 Mar 2021
Reframing Neural Networks: Deep Structure in Overcomplete Representations Calvin Murdock George Cazenavette Simon Lucey BDL 41 4 0 10 Mar 2021
Consistent Sparse Deep Learning: Theory and Computation Y. Sun Qifan Song F. Liang BDL 48 27 0 25 Feb 2021
Cross-Layer Distillation with Semantic Calibration Defang Chen Jian-Ping Mei Yuan Zhang Can Wang Yan Feng Chun-Yen Chen FedML 45 288 0 06 Dec 2020
Bringing AI To Edge: From Deep Learning's Perspective Di Liu Hao Kong Xiangzhong Luo Weichen Liu Ravi Subramaniam 52 116 0 25 Nov 2020
Deep learning insights into cosmological structure formation Luisa Lucie-Smith H. Peiris A. Pontzen Brian D. Nord Jeyan Thiyagalingam 24 6 0 20 Nov 2020
Improving Neural Network Training in Low Dimensional Random Bases Frithjof Gressmann Zach Eaton-Rosen Carlo Luschi 30 28 0 09 Nov 2020
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks Julieta Martinez Jashan Shewakramani Ting Liu Ioan Andrei Bârsan Wenyuan Zeng R. Urtasun MQ 26 30 0 29 Oct 2020
Anti-Distillation: Improving reproducibility of deep networks G. Shamir Lorenzo Coviello 46 20 0 19 Oct 2020
Computing Systems for Autonomous Driving: State-of-the-Art and Challenges Liangkai Liu Sidi Lu Ren Zhong Baofu Wu Yongtao Yao Qingyan Zhang Weisong Shi 27 268 0 30 Sep 2020
A Partial Regularization Method for Network Compression E. Zhenqian Weiguo Gao 18 0 0 03 Sep 2020
Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network Anh-Huy Phan Konstantin Sobolev Konstantin Sozykin Dmitry Ermilov Julia Gusak P. Tichavský Valeriy Glukhov Ivan Oseledets A. Cichocki BDL 27 129 0 12 Aug 2020
Compression of Deep Learning Models for Text: A Survey Manish Gupta Puneet Agrawal VLM MedIm AI4CE 22 115 0 12 Aug 2020
Sparse Linear Networks with a Fixed Butterfly Structure: Theory and Practice Nir Ailon Omer Leibovitch Vineet Nair 15 14 0 17 Jul 2020
T-Basis: a Compact Representation for Neural Networks Anton Obukhov M. Rakhuba Stamatios Georgoulis Menelaos Kanakis Dengxin Dai Luc Van Gool 41 27 0 13 Jul 2020
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights Shail Dave Riyadh Baghdadi Tony Nowatzki Sasikanth Avancha Aviral Shrivastava Baoxin Li 64 82 0 02 Jul 2020
Principal Component Networks: Parameter Reduction Early in Training R. Waleffe Theodoros Rekatsinas 3DPC 19 9 0 23 Jun 2020
Deep Polynomial Neural Networks Grigorios G. Chrysos Stylianos Moschoglou Giorgos Bouritsas Jiankang Deng Yannis Panagakis S. Zafeiriou 29 92 0 20 Jun 2020
Infinite Feature Selection: A Graph-based Feature Filtering Approach Giorgio Roffo Simone Melzi U. Castellani Alessandro Vinciarelli Marco Cristani 35 107 0 15 Jun 2020
A Framework for Neural Network Pruning Using Gibbs Distributions Alex Labach S. Valaee 9 5 0 08 Jun 2020
Premium Access to Convolutional Neural Networks Julien Bringer H. Chabanne Linda Guiga HAI 6 0 0 22 May 2020
ZynqNet: An FPGA-Accelerated Embedded Convolutional Neural Network David Gschwend 35 64 0 14 May 2020
Pruning Algorithms to Accelerate Convolutional Neural Networks for Edge Applications: A Survey Jiayi Liu S. Tripathi Unmesh Kurup Mohak Shah 3DPC MedIm 30 52 0 08 May 2020
A Generic Network Compression Framework for Sequential Recommender Systems Yang Sun Fajie Yuan Ming Yang Guoao Wei Zhou Zhao Duo Liu 26 54 0 21 Apr 2020
GANSpace: Discovering Interpretable GAN Controls Erik Härkönen Aaron Hertzmann J. Lehtinen Sylvain Paris 75 900 0 06 Apr 2020
Dataless Model Selection with the Deep Frame Potential Calvin Murdock Simon Lucey 41 6 0 30 Mar 2020
Rethinking Depthwise Separable Convolutions: How Intra-Kernel Correlations Lead to Improved MobileNets D. Haase Manuel Amthor 20 132 0 30 Mar 2020