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Jeff Dean
Person information
- affiliation: Google, Inc.
- award: ACM Prize in Computing, 2012
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Books and Theses
- 2006
[b2]Steven Pritchard, Bruno Gomes Pessanha, Nicolai Langfeldt, James Stanger, Jeffrey Dean:
LPI Linux certification - in a nutshell: a desktop quick reference: pass the LPIC-1 and LPIC-2 exams, 2nd Edition. O'Reilly 2006, ISBN 978-0-596-00528-3, pp. I-XVIII, 1-961- 2001
- [b1]Jeffrey Dean:
LPI Linux certification in a nutshell - a desktop quick reference: covers exams 101 102 for LPI level 1. O'Reilly 2001, ISBN 978-1-56592-748-3, pp. I-XVI, 1-551
Journal Articles
- 2023
- [j30]Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel:
PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 24: 240:1-240:113 (2023) - 2022
- [j29]David A. Patterson, Joseph Gonzalez
, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. Computer 55(7): 18-28 (2022) - [j28]Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal:
Interlocking Backpropagation: Improving depthwise model-parallelism. J. Mach. Learn. Res. 23: 171:1-171:28 (2022) - [j27]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022) - 2021
- [j26]Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe Wenjie Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean:
A graph placement methodology for fast chip design. Nat. 594(7862): 207-212 (2021) - [j25]Andre Esteva, Katherine Chou, Serena Yeung, Nikhil Naik, Ali Madani, Ali Mottaghi, Yun Liu, Eric J. Topol, Jeff Dean, Richard Socher:
Deep learning-enabled medical computer vision. npj Digit. Medicine 4 (2021) - 2020
- [j24]Tzvika Hartman, Michael D. Howell, Jeff Dean, Shlomo Hoory, Ronit Slyper, Itay Laish, Oren Gilon, Danny Vainstein, Greg Corrado, Katherine Chou, Ming Jack Po, Jutta Williams, Scott Ellis, Gavin Bee, Avinatan Hassidim, Rony Amira, Genady Beryozkin, Idan Szpektor, Yossi Matias:
Customization scenarios for de-identification of clinical notes. BMC Medical Informatics Decis. Mak. 20(1): 14 (2020) - 2018
- [j23]Jeff Dean, David A. Patterson, Cliff Young:
A New Golden Age in Computer Architecture: Empowering the Machine-Learning Revolution. IEEE Micro 38(2): 21-29 (2018) - [j22]Alvin Rajkomar, Andrew M. Dai, Mimi Sun, Michaela Hardt, Kai Chen, Kathryn Rough, Jeffrey Dean:
Reply: metrics to assess machine learning models. npj Digit. Medicine 1 (2018) - [j21]Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Michaela Hardt, Peter J. Liu, Xiaobing Liu, Jake Marcus, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Yi Zhang, Gerardo Flores, Gavin E. Duggan, Jamie Irvine, Quoc Le, Kurt Litsch, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Gregory S. Corrado, Jeffrey Dean:
Scalable and accurate deep learning with electronic health records. npj Digit. Medicine 1 (2018) - 2017
- [j20]Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda B. Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean:
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation. Trans. Assoc. Comput. Linguistics 5: 339-351 (2017) - 2016
- [j19]Daniel Abadi, Rakesh Agrawal, Anastasia Ailamaki, Magdalena Balazinska, Philip A. Bernstein, Michael J. Carey, Surajit Chaudhuri, Jeffrey Dean, AnHai Doan, Michael J. Franklin, Johannes Gehrke, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioannidis, H. V. Jagadish, Donald Kossmann, Samuel Madden, Sharad Mehrotra, Tova Milo, Jeffrey F. Naughton, Raghu Ramakrishnan, Volker Markl, Christopher Olston, Beng Chin Ooi, Christopher Ré, Dan Suciu, Michael Stonebraker, Todd Walter, Jennifer Widom:
The Beckman report on database research. Commun. ACM 59(2): 92-99 (2016) - 2014
- [j18]Daniel J. Abadi, Rakesh Agrawal, Anastasia Ailamaki, Magdalena Balazinska, Philip A. Bernstein, Michael J. Carey, Surajit Chaudhuri, Jeffrey Dean, AnHai Doan, Michael J. Franklin, Johannes Gehrke, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioannidis, H. V. Jagadish, Donald Kossmann, Samuel Madden, Sharad Mehrotra, Tova Milo, Jeffrey F. Naughton, Raghu Ramakrishnan, Volker Markl, Christopher Olston, Beng Chin Ooi, Christopher Ré, Dan Suciu, Michael Stonebraker, Todd Walter, Jennifer Widom:
The Beckman Report on Database Research. SIGMOD Rec. 43(3): 61-70 (2014) - 2013
- [j17]Jeffrey Dean, Luiz André Barroso:
The tail at scale. Commun. ACM 56(2): 74-80 (2013) - [j16]James C. Corbett, Jeffrey Dean, Michael Epstein, Andrew Fikes, Christopher Frost, J. J. Furman, Sanjay Ghemawat, Andrey Gubarev, Christopher Heiser, Peter Hochschild, Wilson C. Hsieh, Sebastian Kanthak, Eugene Kogan, Hongyi Li, Alexander Lloyd, Sergey Melnik, David Mwaura, David Nagle, Sean Quinlan, Rajesh Rao, Lindsay Rolig, Yasushi Saito, Michal Szymaniak, Christopher Taylor, Ruth Wang, Dale Woodford:
Spanner: Google's Globally Distributed Database. ACM Trans. Comput. Syst. 31(3): 8 (2013) - 2010
- [j15]Jeffrey Dean, Sanjay Ghemawat:
MapReduce: a flexible data processing tool. Commun. ACM 53(1): 72-77 (2010) - 2008
- [j14]Jeffrey Dean, Sanjay Ghemawat:
MapReduce: simplified data processing on large clusters. Commun. ACM 51(1): 107-113 (2008) - [j13]Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Michael Burrows, Tushar Chandra, Andrew Fikes, Robert E. Gruber:
Bigtable: A Distributed Storage System for Structured Data. ACM Trans. Comput. Syst. 26(2): 4:1-4:26 (2008) - 2003
- [j12]Luiz André Barroso, Jeffrey Dean, Urs Hölzle:
Web Search for a Planet: The Google Cluster Architecture. IEEE Micro 23(2): 22-28 (2003) - 2000
- [j11]Krishna Bharat, Andrei Z. Broder, Jeffrey Dean, Monika Rauch Henzinger:
A Comparison of Techniques to Find Mirrored Hosts on the WWW. IEEE Data Eng. Bull. 23(4): 21-26 (2000) - [j10]Krishna Bharat, Andrei Z. Broder, Jeffrey Dean, Monika Rauch Henzinger:
A comparison of techniques to find mirrored hosts on the WWW. J. Am. Soc. Inf. Sci. 51(12): 1114-1122 (2000) - 1999
- [j9]Jeffrey Dean, Thomas Kindermann, Josef Schmitz, Michael Schumm, Holk Cruse:
Control of Walking in the Stick Insect: From Behavior and Physiology to Modeling. Auton. Robots 7(3): 271-288 (1999) - [j8]Jeffrey Dean, Monika Rauch Henzinger:
Finding Related Pages in the World Wide Web. Comput. Networks 31(11-16): 1467-1479 (1999) - 1998
- [j7]Holk Cruse, Thomas Kindermann, Michael Schumm, Jeffrey Dean, Josef Schmitz:
Walknet--a biologically inspired network to control six-legged walking. Neural Networks 11(7-8): 1435-1447 (1998) - 1997
- [j6]Jennifer-Ann M. Anderson, Lance M. Berc, Jeffrey Dean, Sanjay Ghemawat, Monika Rauch Henzinger, Shun-Tak Leung, Richard L. Sites, Mark T. Vandevoorde, Carl A. Waldspurger, William E. Weihl:
Continuous Profiling: Where Have All the Cycles Gone? ACM Trans. Comput. Syst. 15(4): 357-390 (1997) - 1995
- [j5]Holk Cruse, Christian Bartling, M. Dreifert, Josef Schmitz, D. E. Brunn, Jeffrey Dean, Thomas Kindermann:
Walking: A Complex Behavior Controlled by Simple Networks. Adapt. Behav. 3(4): 385-418 (1995) - [j4]Holk Cruse, Christian Bartling, Gennady S. Cymbalyuk, Jeffrey Dean, M. Dreifert:
A modular artificial neural net for controlling a six-legged walking system. Biol. Cybern. 72(5): 421-430 (1995) - 1992
- [j3]Uwe Müller-Wilm, Holk Cruse, Jürgen Eltze, Jeffrey Dean, Hans-Jürgen Weidemann, Friedrich Pfeiffer:
Kinematic Model of a Stick Insect as an Example of a Six-Legged Walking System. Adapt. Behav. 1(2): 155-169 (1992) - [j2]Jeffrey Dean:
A model of leg coordination in the stick insect, Carausius morosus. Biol. Cybern. 66(4): 335-343 (1992) - [j1]Jeffrey Dean:
A model of leg coordination in the stick insect, Carausim morosus. Biol. Cybern. 66(4): 345-355 (1992)
Conference and Workshop Papers
- 2023
- [c47]Jeff Dean, Amin Vahdat:
Exciting Directions for ML Models and the Implications for Computing Hardware. HCS 2023: 1-87 - [c46]Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean:
Brainformers: Trading Simplicity for Efficiency. ICML 2023: 42531-42542 - [c45]Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Jonathan Heek, Kefan Xiao, Shivani Agrawal, Jeff Dean:
Efficiently Scaling Transformer Inference. MLSys 2023 - 2022
- [c44]Paul Barham, Aakanksha Chowdhery, Jeff Dean, Sanjay Ghemawat, Steven Hand, Dan Hurt, Michael Isard, Hyeontaek Lim, Ruoming Pang, Sudip Roy, Brennan Saeta, Parker Schuh, Ryan Sepassi, Laurent El Shafey, Chandramohan A. Thekkath, Yonghui Wu:
Pathways: Asynchronous Distributed Dataflow for ML. MLSys 2022 - 2020
- [c43]Jeffrey Dean:
1.1 The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design. ISSCC 2020: 8-14 - 2019
- [c42]Jeff Dean:
Deep Learning for Solving Important Problems. WWW 2019: 1 - 2018
- [c41]Yuan Yu, Martín Abadi, Paul Barham, Eugene Brevdo, Mike Burrows, Andy Davis, Jeff Dean, Sanjay Ghemawat, Tim Harley, Peter Hawkins, Michael Isard, Manjunath Kudlur, Rajat Monga, Derek Gordon Murray, Xiaoqiang Zheng:
Dynamic control flow in large-scale machine learning. EuroSys 2018: 18:1-18:15 - [c40]Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean:
A Hierarchical Model for Device Placement. ICLR (Poster) 2018 - [c39]Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean:
Faster Discovery of Neural Architectures by Searching for Paths in a Large Model. ICLR (Workshop) 2018 - [c38]Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean:
Efficient Neural Architecture Search via Parameter Sharing. ICML 2018: 4092-4101 - [c37]Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis:
The Case for Learned Index Structures. SIGMOD Conference 2018: 489-504 - 2017
- [c36]Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean:
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. ICLR (Poster) 2017 - [c35]Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean:
Device Placement Optimization with Reinforcement Learning. ICML 2017: 2430-2439 - [c34]Norman P. Jouppi, Cliff Young, Nishant Patil, David A. Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, Rick Boyle, Pierre-luc Cantin, Clifford Chao, Chris Clark, Jeremy Coriell, Mike Daley, Matt Dau, Jeffrey Dean, Ben Gelb, Tara Vazir Ghaemmaghami, Rajendra Gottipati, William Gulland, Robert Hagmann, C. Richard Ho, Doug Hogberg, John Hu, Robert Hundt, Dan Hurt, Julian Ibarz, Aaron Jaffey, Alek Jaworski, Alexander Kaplan, Harshit Khaitan, Daniel Killebrew, Andy Koch, Naveen Kumar, Steve Lacy, James Laudon, James Law, Diemthu Le, Chris Leary, Zhuyuan Liu, Kyle Lucke, Alan Lundin, Gordon MacKean, Adriana Maggiore, Maire Mahony, Kieran Miller, Rahul Nagarajan, Ravi Narayanaswami, Ray Ni, Kathy Nix, Thomas Norrie, Mark Omernick, Narayana Penukonda, Andy Phelps, Jonathan Ross, Matt Ross, Amir Salek, Emad Samadiani, Chris Severn, Gregory Sizikov, Matthew Snelham, Jed Souter, Dan Steinberg, Andy Swing, Mercedes Tan, Gregory Thorson, Bo Tian, Horia Toma, Erick Tuttle, Vijay Vasudevan, Richard Walter, Walter Wang, Eric Wilcox, Doe Hyun Yoon:
In-Datacenter Performance Analysis of a Tensor Processing Unit. ISCA 2017: 1-12 - 2016
- [c33]Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng:
TensorFlow: A System for Large-Scale Machine Learning. OSDI 2016: 265-283 - [c32]Jeff Dean:
Building Machine Learning Systems that Understand. SIGMOD Conference 2016: 1 - [c31]Jeffrey Dean:
Large-Scale Deep Learning For Building Intelligent Computer Systems. WSDM 2016: 1 - 2015
- [c30]Jeffrey Dean:
The rise of cloud computing systems. SOSP History Day 2015: 12:1-12:40 - 2014
- [c29]Mohammad Norouzi, Tomás Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean:
Zero-Shot Learning by Convex Combination of Semantic Embeddings. ICLR 2014 - 2013
- [c28]Matthew D. Zeiler, Marc'Aurelio Ranzato, Rajat Monga, Mark Z. Mao, K. Yang, Quoc Viet Le, Patrick Nguyen, Andrew W. Senior, Vincent Vanhoucke, Jeffrey Dean, Geoffrey E. Hinton:
On rectified linear units for speech processing. ICASSP 2013: 3517-3521 - [c27]Georg Heigold, Vincent Vanhoucke, Andrew W. Senior, Patrick Nguyen, Marc'Aurelio Ranzato, Matthieu Devin, Jeffrey Dean:
Multilingual acoustic models using distributed deep neural networks. ICASSP 2013: 8619-8623 - [c26]Andrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomás Mikolov:
DeViSE: A Deep Visual-Semantic Embedding Model. NIPS 2013: 2121-2129 - [c25]Tomás Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, Jeffrey Dean:
Distributed Representations of Words and Phrases and their Compositionality. NIPS 2013: 3111-3119 - [c24]Tomás Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean:
Efficient Estimation of Word Representations in Vector Space. ICLR (Workshop Poster) 2013 - 2012
- [c23]Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng:
Building high-level features using large scale unsupervised learning. ICML 2012 - [c22]Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc V. Le, Mark Z. Mao, Marc'Aurelio Ranzato, Andrew W. Senior, Paul A. Tucker, Ke Yang, Andrew Y. Ng:
Large Scale Distributed Deep Networks. NIPS 2012: 1232-1240 - [c21]James C. Corbett, Jeffrey Dean, Michael Epstein, Andrew Fikes, Christopher Frost, J. J. Furman, Sanjay Ghemawat, Andrey Gubarev, Christopher Heiser, Peter Hochschild, Wilson C. Hsieh, Sebastian Kanthak, Eugene Kogan, Hongyi Li, Alexander Lloyd, Sergey Melnik, David Mwaura, David Nagle, Sean Quinlan, Rajesh Rao, Lindsay Rolig, Yasushi Saito, Michal Szymaniak, Christopher Taylor, Ruth Wang, Dale Woodford:
Spanner: Google's Globally-Distributed Database. OSDI 2012: 251-264 - 2010
- [c20]Jeffrey Dean:
Evolution and future directions of large-scale storage and computation systems at Google. SoCC 2010: 1 - 2009
- [c19]Boulos Harb, Ciprian Chelba, Jeffrey Dean, Sanjay Ghemawat:
Back-off language model compression. INTERSPEECH 2009: 352-355 - [c18]Jeffrey Dean:
Challenges in building large-scale information retrieval systems: invited talk. WSDM 2009: 1 - 2007
- [c17]Thorsten Brants, Ashok C. Popat, Peng Xu, Franz Josef Och, Jeffrey Dean:
Large Language Models in Machine Translation. EMNLP-CoNLL 2007: 858-867 - [c16]Jeffrey Dean:
MapReduce and Other Building Blocks for Large-Scale Distributed Systems at Google. USENIX ATC 2007 - 2006
- [c15]Jeffrey Dean:
Experiences with MapReduce, an abstraction for large-scale computation. PACT 2006: 1 - [c14]Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Michael Burrows, Tushar Chandra, Andrew Fikes, Robert Gruber:
Bigtable: A Distributed Storage System for Structured Data (Awarded Best Paper!). OSDI 2006: 205-218 - 2004
- [c13]Jeffrey Dean, Sanjay Ghemawat:
MapReduce: Simplified Data Processing on Large Clusters. OSDI 2004: 137-150 - 1999
- [c12]Krishna Bharat, Andrei Z. Broder, Jeffrey Dean, Monika Rauch Henzinger:
A Comparison of Techniques to Find Mirrored Hosts on the WWW. WOWS 1999: 2-12 - 1997
- [c11]Jeffrey Dean, James E. Hicks, Carl A. Waldspurger, William E. Weihl, George Z. Chrysos:
ProfileMe: Hardware Support for Instruction-Level Profiling on Out-of-Order Processors. MICRO 1997: 292-302 - [c10]David Grove, Greg DeFouw, Jeffrey Dean, Craig Chambers:
Call Graph Construction in Object-Oriented Languages. OOPSLA 1997: 108-124 - [c9]Jennifer-Ann M. Anderson, Lance M. Berc, Jeffrey Dean, Sanjay Ghemawat, Monika Rauch Henzinger, Shun-Tak Leung, Richard L. Sites, Mark T. Vandevoorde, Carl A. Waldspurger, William E. Weihl:
Continuous Profiling: Where Have All the Cycles Gone? SOSP 1997: 1-14 - 1996
- [c8]Holk Cruse, Christian Bartling, Jeffrey Dean, Thomas Kindermann, Josef Schmitz, Michael Schumm, Hendrik Wagner:
Simplifying Neural Networks for Controlling Walking by Exploiting Physical Properties. ICANN 1996: 433-438 - [c7]Jeffrey Dean, Greg DeFouw, David Grove, Vassily Litvinov, Craig Chambers:
Vortex: An Optimizing Compiler for Object-Oriented Languages. OOPSLA 1996: 83-100 - 1995
- [c6]Jeffrey Dean, David Grove, Craig Chambers:
Optimization of Object-Oriented Programs Using Static Class Hierarchy Analysis. ECOOP 1995: 77-101 - [c5]Craig Chambers, Jeffrey Dean, David Grove:
A Framework for Selective Recompilation in the Presence of Complex Intermodule Dependencies. ICSE 1995: 221-230 - [c4]David Grove, Jeffrey Dean, Charles Garrett, Craig Chambers:
Profile-Guided Receiver Class Prediction. OOPSLA 1995: 108-123 - [c3]Jeffrey Dean, Craig Chambers, David Grove:
Selective Specialization for Object-Oriented Languages. PLDI 1995: 93-102 - 1994
- [c2]Jeffrey Dean, Craig Chambers:
Towards Better Inlining Decisions Using Inlining Trials. LISP and Functional Programming 1994: 273-282 - [c1]Jeffrey Dean, Craig Chambers, David Grove:
Identifying Profitable Specialization in Object-Oriented Languages. PEPM 1994: 85-96
Informal and Other Publications
- 2024
- [i34]Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan:
Capabilities of Gemini Models in Medicine. CoRR abs/2404.18416 (2024) - 2023
- [i33]Yanqi Zhou, Nan Du, Yanping Huang, Daiyi Peng, Chang Lan, Da Huang, Siamak Shakeri, David R. So, Andrew M. Dai, Yifeng Lu, Zhifeng Chen, Quoc V. Le, Claire Cui, James Laudon, Jeff Dean:
Brainformers: Trading Simplicity for Efficiency. CoRR abs/2306.00008 (2023) - 2022
- [i32]Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus:
Designing Effective Sparse Expert Models. CoRR abs/2202.08906 (2022) - [i31]Paul Barham, Aakanksha Chowdhery, Jeff Dean, Sanjay Ghemawat, Steven Hand, Dan Hurt, Michael Isard, Hyeontaek Lim, Ruoming Pang, Sudip Roy, Brennan Saeta, Parker Schuh, Ryan Sepassi, Laurent El Shafey, Chandramohan A. Thekkath, Yonghui Wu:
Pathways: Asynchronous Distributed Dataflow for ML. CoRR abs/2203.12533 (2022) - [i30]Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel:
PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022) - [i29]David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. CoRR abs/2204.05149 (2022) - [i28]Andrea Gesmundo, Jeff Dean:
muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems. CoRR abs/2205.10937 (2022) - [i27]Andrea Gesmundo, Jeff Dean:
An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems. CoRR abs/2205.12755 (2022) - [i26]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. CoRR abs/2206.07682 (2022) - [i25]William Fedus, Jeff Dean, Barret Zoph:
A Review of Sparse Expert Models in Deep Learning. CoRR abs/2209.01667 (2022) - [i24]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. CoRR abs/2210.11416 (2022) - [i23]Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Anselm Levskaya, Jonathan Heek, Kefan Xiao, Shivani Agrawal, Jeff Dean:
Efficiently Scaling Transformer Inference. CoRR abs/2211.05102 (2022) - 2021
- [i22]David A. Patterson, Joseph Gonzalez, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean:
Carbon Emissions and Large Neural Network Training. CoRR abs/2104.10350 (2021) - 2020
- [i21]Azalia Mirhoseini, Anna Goldie, Mustafa Yazgan, Joe W. J. Jiang, Ebrahim M. Songhori, Shen Wang, Young-Joon Lee, Eric Johnson, Omkar Pathak, Sungmin Bae, Azade Nazi, Jiwoo Pak, Andy Tong, Kavya Srinivasa, William Hang, Emre Tuncer, Anand Babu, Quoc V. Le, James Laudon, Richard Ho, Roger Carpenter, Jeff Dean:
Chip Placement with Deep Reinforcement Learning. CoRR abs/2004.10746 (2020) - [i20]Aidan N. Gomez, Oscar Key, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal:
Interlocking Backpropagation: Improving depthwise model-parallelism. CoRR abs/2010.04116 (2020) - 2019
- [i19]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i18]Angela H. Jiang, Daniel L.-K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminsky, Michael Kozuch, Zachary C. Lipton, Padmanabhan Pillai:
Accelerating Deep Learning by Focusing on the Biggest Losers. CoRR abs/1910.00762 (2019) - [i17]Jeffrey Dean:
The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design. CoRR abs/1911.05289 (2019) - 2018
- [i16]Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai, Nissan Hajaj, Peter J. Liu, Xiaobing Liu, Mimi Sun, Patrik Sundberg, Hector Yee, Kun Zhang, Gavin E. Duggan, Gerardo Flores, Michaela Hardt, Jamie Irvine, Quoc V. Le, Kurt Litsch, Jake Marcus, Alexander Mossin, Justin Tansuwan, De Wang, James Wexler, Jimbo Wilson, Dana Ludwig, Samuel L. Volchenboum, Katherine Chou, Michael Pearson, Srinivasan Madabushi, Nigam H. Shah, Atul J. Butte, Michael D. Howell, Claire Cui, Greg Corrado, Jeff Dean:
Scalable and accurate deep learning for electronic health records. CoRR abs/1801.07860 (2018) - [i15]Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean:
Efficient Neural Architecture Search via Parameter Sharing. CoRR abs/1802.03268 (2018) - [i14]Yuan Yu, Martín Abadi, Paul Barham, Eugene Brevdo, Mike Burrows, Andy Davis, Jeff Dean, Sanjay Ghemawat, Tim Harley, Peter Hawkins, Michael Isard, Manjunath Kudlur, Rajat Monga, Derek Gordon Murray, Xiaoqiang Zheng:
Dynamic Control Flow in Large-Scale Machine Learning. CoRR abs/1805.01772 (2018) - [i13]Po-Hsuan Cameron Chen, Krishna Gadepalli, Robert MacDonald, Yun Liu, Kunal Nagpal, Timo Kohlberger, Jeffrey Dean, Gregory S. Corrado, Jason D. Hipp, Martin C. Stumpe:
Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration. CoRR abs/1812.00825 (2018) - 2017
- [i12]Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean:
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. CoRR abs/1701.06538 (2017) - [i11]Norman P. Jouppi, Cliff Young, Nishant Patil, David A. Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Al Borchers, Rick Boyle, Pierre-luc Cantin, Clifford Chao, Chris Clark, Jeremy Coriell, Mike Daley, Matt Dau, Jeffrey Dean, Ben Gelb, Tara Vazir Ghaemmaghami, Rajendra Gottipati, William Gulland, Robert Hagmann, C. Richard Ho, Doug Hogberg, John Hu, Robert Hundt, Dan Hurt, Julian Ibarz, Aaron Jaffey, Alek Jaworski, Alexander Kaplan, Harshit Khaitan, Andy Koch, Naveen Kumar, Steve Lacy, James Laudon, James Law, Diemthu Le, Chris Leary, Zhuyuan Liu, Kyle Lucke, Alan Lundin, Gordon MacKean, Adriana Maggiore, Maire Mahony, Kieran Miller, Rahul Nagarajan, Ravi Narayanaswami, Ray Ni, Kathy Nix, Thomas Norrie, Mark Omernick, Narayana Penukonda, Andy Phelps, Jonathan Ross, Amir Salek, Emad Samadiani, Chris Severn, Gregory Sizikov, Matthew Snelham, Jed Souter, Dan Steinberg, Andy Swing, Mercedes Tan, Gregory Thorson, Bo Tian, Horia Toma, Erick Tuttle, Vijay Vasudevan, Richard Walter, Walter Wang, Eric Wilcox, Doe Hyun Yoon:
In-Datacenter Performance Analysis of a Tensor Processing Unit. CoRR abs/1704.04760 (2017) - [i10]Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean:
Device Placement Optimization with Reinforcement Learning. CoRR abs/1706.04972 (2017) - [i9]Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis:
The Case for Learned Index Structures. CoRR abs/1712.01208 (2017) - 2016
- [i8]Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng:
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. CoRR abs/1603.04467 (2016) - [i7]Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek Gordon Murray, Benoit Steiner, Paul A. Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zhang:
TensorFlow: A system for large-scale machine learning. CoRR abs/1605.08695 (2016) - [i6]Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Lukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean:
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. CoRR abs/1609.08144 (2016) - [i5]Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda B. Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, Jeffrey Dean:
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation. CoRR abs/1611.04558 (2016) - 2015
- [i4]Geoffrey E. Hinton, Oriol Vinyals, Jeffrey Dean:
Distilling the Knowledge in a Neural Network. CoRR abs/1503.02531 (2015) - 2013
- [i3]Tomás Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean:
Distributed Representations of Words and Phrases and their Compositionality. CoRR abs/1310.4546 (2013) - [i2]Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer:
Using Web Co-occurrence Statistics for Improving Image Categorization. CoRR abs/1312.5697 (2013) - 2011
- [i1]Quoc V. Le, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Marc'Aurelio Ranzato, Jeffrey Dean, Andrew Y. Ng:
Building high-level features using large scale unsupervised learning. CoRR abs/1112.6209 (2011)
Coauthor Index
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