Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

15 August 2013

Aaron Courville

Papers citing "Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation"

50 / 1,874 papers shown

Title
$Gradient $\ell_1$ Regularization for Quantization Robustness$ Gradient $\ell_1$ Regularization for Quantization Robustness Milad Alizadeh Arash Behboodi M. V. Baalen Christos Louizos Tijmen Blankevoort Max Welling MQ 17 8 0 18 Feb 2020
Controlling Computation versus Quality for Neural Sequence Models Ankur Bapna N. Arivazhagan Orhan Firat 27 30 0 17 Feb 2020
BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations Hyungjun Kim Kyungsu Kim Jinseok Kim Jae-Joon Kim MQ 27 47 0 16 Feb 2020
Estimating Gradients for Discrete Random Variables by Sampling without Replacement W. Kool H. V. Hoof Max Welling BDL 31 49 0 14 Feb 2020
Improving Efficiency in Neural Network Accelerator Using Operands Hamming Distance optimization Meng Li Yilei Li P. Chuang Liangzhen Lai Vikas Chandra 16 3 0 13 Feb 2020
BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization Milovs Nikolić G. B. Hacene Ciaran Bannon Alberto Delmas Lascorz Matthieu Courbariaux Yoshua Bengio Vincent Gripon Andreas Moshovos MQ 22 24 0 08 Feb 2020
Switchable Precision Neural Networks Luis Guerra Bohan Zhuang Ian Reid Tom Drummond MQ 30 20 0 07 Feb 2020
Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow Didrik Nielsen Ole Winther MQ 201 13 0 06 Feb 2020
Deep Learning-based Image Compression with Trellis Coded Quantization Binglin Li Mohammad Akbari Jie Liang Yang Wang MQ 18 8 0 26 Jan 2020
Latency-Aware Differentiable Neural Architecture Search Yuhui Xu Lingxi Xie Xiaopeng Zhang Xin Chen Bowen Shi Qi Tian H. Xiong OOD 35 33 0 17 Jan 2020
MeliusNet: Can Binary Neural Networks Achieve MobileNet-level Accuracy? Joseph Bethge Christian Bartz Haojin Yang Ying-Cong Chen Christoph Meinel MQ 25 91 0 16 Jan 2020
Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation Chuteng Zhou Prad Kadambi Matthew Mattina P. Whatmough 21 35 0 14 Jan 2020
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search Daoyuan Chen Yaliang Li Minghui Qiu Zhen Wang Bofang Li Bolin Ding Hongbo Deng Jun Huang Wei Lin Jingren Zhou MQ 24 104 0 13 Jan 2020
Least squares binary quantization of neural networks Hadi Pouransari Zhucheng Tu Oncel Tuzel MQ 17 32 0 09 Jan 2020
Resource-Efficient Neural Networks for Embedded Systems Wolfgang Roth Günther Schindler Lukas Pfeifenberger Robert Peharz Sebastian Tschiatschek Holger Fröning Franz Pernkopf Zoubin Ghahramani 34 47 0 07 Jan 2020
Attention over Parameters for Dialogue Systems Andrea Madotto Zhaojiang Lin Chien-Sheng Wu Jamin Shin Pascale Fung 30 20 0 07 Jan 2020
Generalizing Emergent Communication Thomas A. Unger Elia Bruni 20 1 0 06 Jan 2020
Learning Accurate Integer Transformer Machine-Translation Models Ephrem Wu 19 4 0 03 Jan 2020
Mixed-Precision Quantized Neural Network with Progressively Decreasing Bitwidth For Image Classification and Object Detection Tianshu Chu Qin Luo Jie Yang Xiaolin Huang MQ 24 6 0 29 Dec 2019
Towards Efficient Training for Neural Network Quantization Qing Jin Linjie Yang Zhenyu A. Liao MQ 19 42 0 21 Dec 2019
Triple Generative Adversarial Networks Chongxuan Li Kun Xu Jiashuo Liu Jun Zhu Bo Zhang GAN 36 41 0 20 Dec 2019
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax Andres Potapczynski G. Loaiza-Ganem John P. Cunningham 32 29 0 19 Dec 2019
Meta Decision Trees for Explainable Recommendation Systems Eyal Shulman Lior Wolf 23 18 0 19 Dec 2019
Learned Variable-Rate Image Compression with Residual Divisive Normalization Mohammad Akbari Jie Liang Jingning Han Chengjie Tu 22 25 0 11 Dec 2019
Learning to Request Guidance in Emergent Communication Benjamin Kolb Leon Lang H. Bartsch Arwin Gansekoele Raymond Koopmanschap Leonardo Romor David Speck Mathijs Mul Elia Bruni 27 0 0 11 Dec 2019
Neural-Symbolic Descriptive Action Model from Images: The Search for STRIPS Masataro Asai 9 3 0 11 Dec 2019
Winning the Lottery with Continuous Sparsification Pedro H. P. Savarese Hugo Silva Michael Maire 8 133 0 10 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 28 9 0 09 Dec 2019
Exploring the Back Alleys: Analysing The Robustness of Alternative Neural Network Architectures against Adversarial Attacks Y. Tan Yuval Elovici Alexander Binder AAML 11 3 0 08 Dec 2019
Dynamic Convolutions: Exploiting Spatial Sparsity for Faster Inference Thomas Verelst Tinne Tuytelaars 11 149 0 06 Dec 2019
Sampling-Free Learning of Bayesian Quantized Neural Networks Jiahao Su Milan Cvitkovic Furong Huang BDL MQ UQCV 13 7 0 06 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 67 1,635 0 05 Dec 2019
Deep Model Compression Via Two-Stage Deep Reinforcement Learning Huixin Zhan Wei-Ming Lin Yongcan Cao 18 12 0 04 Dec 2019
RTN: Reparameterized Ternary Network Yuhang Li Xin Dong Shanghang Zhang Haoli Bai Yuanpeng Chen Wei Wang MQ 21 28 0 04 Dec 2019
Binarized Canonical Polyadic Decomposition for Knowledge Graph Completion Koki Kishimoto Katsuhiko Hayashi Genki Akai Masashi Shimbo 14 1 0 04 Dec 2019
Dream to Control: Learning Behaviors by Latent Imagination Danijar Hafner Timothy Lillicrap Jimmy Ba Mohammad Norouzi VLM 39 1,313 0 03 Dec 2019
The Knowledge Within: Methods for Data-Free Model Compression Matan Haroush Itay Hubara Elad Hoffer Daniel Soudry 20 105 0 03 Dec 2019
A binary-activation, multi-level weight RNN and training algorithm for ADC-/DAC-free and noise-resilient processing-in-memory inference with eNVM Siming Ma David Brooks Gu-Yeon Wei MQ 11 2 0 30 Nov 2019
What's Hidden in a Randomly Weighted Neural Network? Vivek Ramanujan Mitchell Wortsman Aniruddha Kembhavi Ali Farhadi Mohammad Rastegari 14 351 0 29 Nov 2019
Semi-Relaxed Quantization with DropBits: Training Low-Bit Neural Networks via Bit-wise Regularization J. H. Lee Jihun Yun Sung Ju Hwang Eunho Yang MQ 20 0 0 29 Nov 2019
QKD: Quantization-aware Knowledge Distillation Jangho Kim Yash Bhalgat Jinwon Lee Chirag I. Patel Nojun Kwak MQ 26 64 0 28 Nov 2019
AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning Ximeng Sun Yikang Shen Rogerio Feris Kate Saenko 31 261 0 27 Nov 2019
Technical report: supervised training of convolutional spiking neural networks with PyTorch Romain Zimmer Thomas Pellegrini S. Singh T. Masquelier 28 32 0 22 Nov 2019
Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech David Harwath Wei-Ning Hsu James R. Glass 28 84 0 21 Nov 2019
Few Shot Network Compression via Cross Distillation Haoli Bai Jiaxiang Wu Irwin King Michael Lyu FedML 28 60 0 21 Nov 2019
Fast and Flexible Image Blind Denoising via Competition of Experts S. Maeda 35 6 0 20 Nov 2019
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition Jibin Wu Emre Yilmaz Malu Zhang Haizhou Li Kay Chen Tan 33 104 0 19 Nov 2019
AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers Julian Faraone M. Kumm M. Hardieck P. Zipf Xueyuan Liu David Boland Philip H. W. Leong MQ 14 45 0 19 Nov 2019
Any-Precision Deep Neural Networks Haichao Yu Haoxiang Li Humphrey Shi Thomas S. Huang G. Hua MQ 23 63 0 17 Nov 2019
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation Ryuichiro Hataya Jan Zdenek Kazuki Yoshizoe Hideki Nakayama 27 203 0 16 Nov 2019