Do Deep Nets Really Need to be Deep?

21 December 2013

Lei Jimmy Ba

Papers citing "Do Deep Nets Really Need to be Deep?"

49 / 399 papers shown

Title
Knowledge distillation using unlabeled mismatched images Mandar M. Kulkarni Kalpesh Patil Shirish S. Karande 48 16 0 21 Mar 2017
NoScope: Optimizing Neural Network Queries over Video at Scale Daniel Kang John Emmons Firas Abuzaid Peter Bailis Matei A. Zaharia 29 205 0 07 Mar 2017
Chain-NN: An Energy-Efficient 1D Chain Architecture for Accelerating Deep Convolutional Neural Networks Shihao Wang Dajiang Zhou Xushen Han T. Yoshimura 3DV 11 51 0 04 Mar 2017
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World S. Garg Irina Rish Guillermo Cecchi A. Lozano OffRL CLL 33 6 0 22 Jan 2017
Learning From Noisy Large-Scale Datasets With Minimal Supervision Andreas Veit N. Alldrin Gal Chechik Ivan Krasin Abhinav Gupta Serge J. Belongie 34 476 0 06 Jan 2017
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer Sergey Zagoruyko N. Komodakis 37 2,553 0 12 Dec 2016
In Teacher We Trust: Learning Compressed Models for Pedestrian Detection Jonathan Shen Noranart Vesdapunt Vishnu Boddeti Kris Kitani 19 29 0 01 Dec 2016
Patient-Driven Privacy Control through Generalized Distillation Z. Berkay Celik David Lopez-Paz Patrick McDaniel 24 18 0 26 Nov 2016
Training Sparse Neural Networks Suraj Srinivas Akshayvarun Subramanya R. Venkatesh Babu 27 204 0 21 Nov 2016
Fast Video Classification via Adaptive Cascading of Deep Models Haichen Shen Seungyeop Han Matthai Philipose Arvind Krishnamurthy 34 78 0 20 Nov 2016
Deep Model Compression: Distilling Knowledge from Noisy Teachers Bharat Bhusan Sau V. Balasubramanian 23 181 0 30 Oct 2016
Small-footprint Highway Deep Neural Networks for Speech Recognition Liang Lu Steve Renals 38 15 0 18 Oct 2016
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser A. Kuncoro Miguel Ballesteros Lingpeng Kong Chris Dyer Noah A. Smith MoE 31 77 0 24 Sep 2016
Why does deep and cheap learning work so well? Henry W. Lin Max Tegmark David Rolnick 40 603 0 29 Aug 2016
Lets keep it simple, Using simple architectures to outperform deeper and more complex architectures S. H. HasanPour Mohammad Rouhani Mohsen Fayyaz Mohammad Sabokrou 23 119 0 22 Aug 2016
Knowledge Distillation for Small-footprint Highway Networks Liang Lu Michelle Guo Steve Renals 26 73 0 02 Aug 2016
Supervised learning based on temporal coding in spiking neural networks Hesham Mostafa 31 350 0 27 Jun 2016
Sequence-Level Knowledge Distillation Yoon Kim Alexander M. Rush 47 1,101 0 25 Jun 2016
Active Long Term Memory Networks Tommaso Furlanello Jiaping Zhao Andrew M. Saxe Laurent Itti B. Tjan KELM CLL 32 41 0 07 Jun 2016
The Implementation of Low-cost Urban Acoustic Monitoring Devices C. Mydlarz Justin Salamon J. P. Bello 22 140 0 26 May 2016
FractalNet: Ultra-Deep Neural Networks without Residuals Gustav Larsson Michael Maire Gregory Shakhnarovich 45 933 0 24 May 2016
A topological insight into restricted Boltzmann machines Decebal Constantin Mocanu Elena Mocanu Phuong H. Nguyen M. Gibescu A. Liotta BDL 8 97 0 20 Apr 2016
Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation G. Ros Simon Stent P. Alcantarilla Tomoki Watanabe 21 55 0 06 Apr 2016
Do Deep Convolutional Nets Really Need to be Deep and Convolutional? G. Urban Krzysztof J. Geras Samira Ebrahimi Kahou Ozlem Aslan Shengjie Wang R. Caruana Abdel-rahman Mohamed Matthai Philipose Matthew Richardson 20 47 0 17 Mar 2016
XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks Mohammad Rastegari Vicente Ordonez Joseph Redmon Ali Farhadi MQ 57 4,332 0 16 Mar 2016
Network Morphism Tao Wei Changhu Wang Y. Rui Chen Chen 21 176 0 05 Mar 2016
Decision Forests, Convolutional Networks and the Models in-Between Yani Andrew Ioannou D. Robertson Darko Zikic Peter Kontschieder Jamie Shotton Matthew Brown A. Criminisi 26 88 0 03 Mar 2016
Efficient Representation of Low-Dimensional Manifolds using Deep Networks Ronen Basri David Jacobs 3DPC 22 44 0 15 Feb 2016
A Taxonomy of Deep Convolutional Neural Nets for Computer Vision Suraj Srinivas Ravi Kiran Sarvadevabhatla Konda Reddy Mopuri N. Prabhu S. Kruthiventi R. Venkatesh Babu OOD 35 215 0 25 Jan 2016
Distilling Knowledge from Deep Networks with Applications to Healthcare Domain Zhengping Che S. Purushotham R. Khemani Yan Liu 19 139 0 11 Dec 2015
Sparsifying Neural Network Connections for Face Recognition Yi Sun Xiaogang Wang Xiaoou Tang 3DH CVBM 32 141 0 07 Dec 2015
Actor-Mimic: Deep Multitask and Transfer Reinforcement Learning Emilio Parisotto Jimmy Lei Ba Ruslan Salakhutdinov OffRL 30 591 0 19 Nov 2015
Policy Distillation Andrei A. Rusu Sergio Gomez Colmenarejo Çağlar Gülçehre Guillaume Desjardins J. Kirkpatrick Razvan Pascanu Volodymyr Mnih Koray Kavukcuoglu R. Hadsell 22 681 0 19 Nov 2015
Representational Distance Learning for Deep Neural Networks Patrick McClure N. Kriegeskorte 27 48 0 12 Nov 2015
How far can we go without convolution: Improving fully-connected networks Zhouhan Lin Roland Memisevic K. Konda 35 50 0 09 Nov 2015
Symmetry-invariant optimization in deep networks Vijay Badrinarayanan Bamdev Mishra R. Cipolla ODL 19 31 0 05 Nov 2015
Distilling Model Knowledge George Papamakarios BDL 32 17 0 08 Oct 2015
Simultaneous Deep Transfer Across Domains and Tasks Eric Tzeng Judy Hoffman Trevor Darrell Kate Saenko OOD 24 1,364 0 08 Oct 2015
Tensorizing Neural Networks Alexander Novikov D. Podoprikhin A. Osokin Dmitry Vetrov 47 875 0 22 Sep 2015
Giraffe: Using Deep Reinforcement Learning to Play Chess Matthew Lai 11 108 0 04 Sep 2015
Compressing Convolutional Neural Networks Wenlin Chen James T. Wilson Stephen Tyree Kilian Q. Weinberger Yixin Chen 26 139 0 14 Jun 2015
A Scale Mixture Perspective of Multiplicative Noise in Neural Networks Eric T. Nalisnick Anima Anandkumar Padhraic Smyth 27 19 0 10 Jun 2015
Fast ConvNets Using Group-wise Brain Damage V. Lebedev Victor Lempitsky AAML 44 447 0 08 Jun 2015
Recurrent Neural Network Training with Dark Knowledge Transfer Zhiyuan Tang Dong Wang Zhiyong Zhang 29 109 0 18 May 2015
In Defense of the Direct Perception of Affordances David Fouhey Xinyu Wang Abhinav Gupta 26 21 0 05 May 2015
Compressing Neural Networks with the Hashing Trick Wenlin Chen James T. Wilson Stephen Tyree Kilian Q. Weinberger Yixin Chen 35 1,190 0 19 Apr 2015
Hybrid Orthogonal Projection and Estimation (HOPE): A New Framework to Probe and Learn Neural Networks Shiliang Zhang Hui Jiang 3DV 36 9 0 03 Feb 2015
Crypto-Nets: Neural Networks over Encrypted Data P. Xie Mikhail Bilenko Tom Finley Ran Gilad-Bachrach Kristin E. Lauter M. Naehrig FedML 39 150 0 18 Dec 2014
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,640 0 03 Jul 2012