Mikhail Isaev

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All published works

Action	Title	Year	Authors
+	Integer Quantization for Deep Learning Inference: Principles and Empirical Evaluation	2020	Hao Wu Patrick Judd Xiaojie Zhang Mikhail Isaev Paulius Micikevicius

Common Coauthors

Coauthor	Papers Together
Paulius Micikevicius	1
Patrick Judd	1
Xiaojie Zhang	1
Hao Wu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Low precision storage for deep learning	2014	Matthieu Courbariaux Yoshua Bengio Jean‐Pierre David	1
+	cuDNN: Efficient Primitives for Deep Learning	2014	Sharan Chetlur Cliff Woolley Philippe Vandermersch Jonathan Cohen John Tran Bryan Catanzaro Evan Shelhamer	1
+	Training deep neural networks with low precision multiplications	2014	Matthieu Courbariaux Yoshua Bengio Jean‐Pierre David	1
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	1
+ PDF Chat	Rethinking the Inception Architecture for Computer Vision	2016	Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jon Shlens Zbigniew Wojna	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+	Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation	2013	Yoshua Bengio Nicholas Léonard Aaron Courville	1
+ PDF Chat	XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks	2016	Mohammad Rastegari Vicente Ordóñez Joseph Redmon Ali Farhadi	1
+	Bridging Nonlinearities and Stochastic Regularizers with Gaussian Error Linear Units	2016	Dan Hendrycks Kevin Gimpel	1
+	DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients	2016	Shuchang Zhou Yuxin Wu Zekun Ni Xinyu Zhou He Wen Yuheng Zou	1
+	Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation	2016	Yonghui Wu Mike Schuster Zhifeng Chen Quoc V. Le Mohammad Norouzi Wolfgang Macherey Maxim Krikun Yuan Cao Qin Gao Klaus Macherey	1
+ PDF Chat	Aggregated Residual Transformations for Deep Neural Networks	2017	Saining Xie Ross Girshick Piotr Dollár Zhuowen Tu Kaiming He	1
+	Trained Ternary Quantization	2016	Chenzhuo Zhu Song Han Huizi Mao William J. Dally	1
+	In-Datacenter Performance Analysis of a Tensor Processing Unit	2017	Norman P. Jouppi Cliff Young Nishant Patil David A. Patterson Gaurav Agrawal Raminder Bajwa S. C. Bates Suresh Bhatia Nan Boden Al Borchers	1
+	Ternary Neural Networks with Fine-Grained Quantization	2017	Naveen Mellempudi Abhisek Kundu Dheevatsa Mudigere Dipankar Das Bharat Kaul Pradeep Dubey	1
+	MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications	2017	Andrew Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam	1
+	Mixed Precision Training	2017	Paulius Micikevicius Sharan Narang Jonah Alben Gregory Diamos Erich Elsen David García Boris Ginsburg Michael Houston Oleksii Kuchaiev Ganesh Venkatesh	1
+	Searching for Activation Functions	2017	Prajit Ramachandran Barret Zoph Quoc V. Le	1
+	Three Factors Influencing Minima in SGD	2017	Stanisław Jastrzȩbski Zachary Kenton Devansh Arpit Nicolas Ballas Asja Fischer Yoshua Bengio Amos Storkey	1
+	Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy	2017	Asit K. Mishra Debbie Marr	1
+	PACT: Parameterized Clipping Activation for Quantized Neural Networks	2018	Jungwook Choi Zhuo Wang Swagath Venkataramani Pierce Chuang Vijayalakshmi Srinivasan Kailash Gopalakrishnan	1
+	Model compression via distillation and quantization	2018	Antonio Polino Razvan Pascanu Dan Alistarh	1
+	Marian: Cost-effective High-Quality Neural Machine Translation in C++	2018	Marcin Junczys-Dowmunt Kenneth Heafield Hieu Hoang Roman Grundkiewicz Anthony Aue	1
+	Retraining-Based Iterative Weight Quantization for Deep Neural Networks	2018	Dongsoo Lee Byeongwook Kim	1
+	Quantizing deep convolutional networks for efficient inference: A whitepaper	2018	Raghuraman Krishnamoorthi	1
+	Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Embedded Inference	2018	Jeffrey L. McKinstry Steven K. Esser Rathinakumar Appuswamy Deepika Bablani John V. Arthur Izzet B. Yildiz Dharmendra S. Modha	1
+	Gaussian Error Linear Units (GELUs)	2016	Dan Hendrycks Kevin Gimpel	1
+	Image Classification at Supercomputer Scale	2018	Chris Ying Sameer Kumar Dehao Chen Tao Wang Youlong Cheng	1
+	Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks	2019	Boris Ginsburg Patrice Castonguay Oleksii Hrinchuk Oleksii Kuchaiev Vitaly Lavrukhin R. Bret Leary Jason Li Huyen Nguyen Jonathan Cohen	1
+	EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks	2019	Mingxing Tan Quoc V. Le	1
+	Efficient 8-Bit Quantization of Transformer Neural Machine Language Translation Model.	2019	Aishwarya Bhandare Vamsi Sripathi Deepthi Karkada Vivek Menon Sun Choi Kushal Datta Vikram A. Saletore	1
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	1
+	Extremely Low Bit Neural Network: Squeeze the Last Bit Out with ADMM	2017	Cong Leng Hao Li Shenghuo Zhu Rong Jin	1
+ PDF Chat	MobileNetV2: Inverted Residuals and Linear Bottlenecks	2018	Mark Sandler Andrew Howard Menglong Zhu Andrey Zhmoginov Liang-Chieh Chen	1
+ PDF Chat	Focal Loss for Dense Object Detection	2017	Tsung-Yi Lin Priya Goyal Ross Girshick Kaiming He Piotr Dollár	1
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	1
+ PDF Chat	Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning	2017	Christian Szegedy Sergey Ioffe Vincent Vanhoucke Alexander A. Alemi	1
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	1
+	Trained Quantization Thresholds for Accurate and Efficient Fixed-Point Inference of Deep Neural Networks	2019	Sambhav R. Jain Albert Gural Michael Wu Chris Dick	1
+	Q8BERT: Quantized 8Bit BERT	2019	Ofir Zafrir Guy Boudoukh Peter Izsak Moshe Wasserblat	1
+ PDF Chat	Data-Free Quantization Through Weight Equalization and Bias Correction	2019	Markus Nagel Mart van Baalen Tijmen Blankevoort Max Welling	1
+	Neural Network Distiller: A Python Package For DNN Compression Research	2019	Neta Zmora Guy Jacob Lev Zlotnik Bar Elharar Gal Novik	1
+ PDF Chat	Neural Network Compression Framework for Fast Model Inference	2021	Alexander Kozlov Ivan Lazarevich Vasily Shamporov Nikolay Lyalyushkin Yury Gorbachev	1
+ PDF Chat	UNIQ	2019	Chaim Baskin Natan Liss Eli Schwartz Evgenii Zheltonozhskii Raja Giryes Alex Bronstein Avi Mendelson	1