Jeffrey Dean

According to our database, Jeffrey Dean authored at least 95 papers between 1992 and 2024.

Collaborative distances:

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2024

Scaling Instruction-Finetuned Language Models.

Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, 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

J. Mach. Learn. Res., 2024

Capabilities of Gemini Models in Medicine.

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

CoRR, 2024

2023

PaLM: Scaling Language Modeling with Pathways.

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

J. Mach. Learn. Res., 2023

Efficiently Scaling Transformer Inference.

Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Jonathan Heek, Kefan Xiao, Shivani Agrawal, Jeff Dean

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

Brainformers: Trading Simplicity for Efficiency.

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

Proceedings of the International Conference on Machine Learning, 2023

Exciting Directions for ML Models and the Implications for Computing Hardware.

Jeff Dean, Amin Vahdat

Proceedings of the 35th IEEE Hot Chips Symposium, 2023

2022

Emergent Abilities of Large Language Models.

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

Trans. Mach. Learn. Res., 2022

Interlocking Backpropagation: Improving depthwise model-parallelism.

Aidan N. Gomez, Oscar Key, Kuba Perlin, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal

J. Mach. Learn. Res., 2022

Efficiently Scaling Transformer Inference.

Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Anselm Levskaya, Jonathan Heek, Kefan Xiao, Shivani Agrawal, Jeff Dean

CoRR, 2022

Scaling Instruction-Finetuned Language Models.

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

CoRR, 2022

A Review of Sparse Expert Models in Deep Learning.

William Fedus, Jeff Dean, Barret Zoph

CoRR, 2022

An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems.

Andrea Gesmundo, Jeff Dean

CoRR, 2022

muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems.

Andrea Gesmundo, Jeff Dean

CoRR, 2022

Designing Effective Sparse Expert Models.

Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus

CoRR, 2022

The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink.

David A. Patterson, Joseph Gonzalez, Urs Hölzle, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean

Computer, 2022

Pathways: Asynchronous Distributed Dataflow for ML.

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

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

2021

Deep learning-enabled medical computer vision.

Andre Esteva, Katherine Chou, Serena Yeung, Nikhil Naik, Ali Madani, Ali Mottaghi, Yun Liu, Eric J. Topol, Jeff Dean, Richard Socher

npj Digit. Medicine, 2021

A graph placement methodology for fast chip design.

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

Nat., 2021

Carbon Emissions and Large Neural Network Training.

David A. Patterson, Joseph Gonzalez, Quoc V. Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David R. So, Maud Texier, Jeff Dean

CoRR, 2021

2020

Customization scenarios for de-identification of clinical notes.

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

BMC Medical Informatics Decis. Mak., 2020

Interlocking Backpropagation: Improving depthwise model-parallelism.

Aidan N. Gomez, Oscar Key, Stephen Gou, Nick Frosst, Jeff Dean, Yarin Gal

CoRR, 2020

Chip Placement with Deep Reinforcement Learning.

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

CoRR, 2020

1.1 The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design.

Jeffrey Dean

Proceedings of the 2020 IEEE International Solid- State Circuits Conference, 2020

2019

The Deep Learning Revolution and Its Implications for Computer Architecture and Chip Design.

Jeffrey Dean

CoRR, 2019

Accelerating Deep Learning by Focusing on the Biggest Losers.

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

CoRR, 2019

SysML: The New Frontier of Machine Learning Systems.

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

CoRR, 2019

Deep Learning for Solving Important Problems.

Jeff Dean

Proceedings of the World Wide Web Conference, 2019

2018

Scalable and accurate deep learning with electronic health records.

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

npj Digit. Medicine, 2018

Reply: metrics to assess machine learning models.

Alvin Rajkomar, Andrew M. Dai, Mimi Sun, Michaela Hardt, Kai Chen, Kathryn Rough, Jeffrey Dean

npj Digit. Medicine, 2018

A New Golden Age in Computer Architecture: Empowering the Machine-Learning Revolution.

Jeff Dean, David A. Patterson, Cliff Young

IEEE Micro, 2018

Microscope 2.0: An Augmented Reality Microscope with Real-time Artificial Intelligence Integration.

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

CoRR, 2018

Scalable and accurate deep learning for electronic health records.

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

CoRR, 2018

The Case for Learned Index Structures.

Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis

Proceedings of the 2018 International Conference on Management of Data, 2018

Efficient Neural Architecture Search via Parameter Sharing.

Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean

Proceedings of the 35th International Conference on Machine Learning, 2018

Faster Discovery of Neural Architectures by Searching for Paths in a Large Model.

Hieu Pham, Melody Y. Guan, Barret Zoph, Quoc V. Le, Jeff Dean

Proceedings of the 6th International Conference on Learning Representations, 2018

A Hierarchical Model for Device Placement.

Azalia Mirhoseini, Anna Goldie, Hieu Pham, Benoit Steiner, Quoc V. Le, Jeff Dean

Proceedings of the 6th International Conference on Learning Representations, 2018

Dynamic control flow in large-scale machine learning.

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

Proceedings of the Thirteenth EuroSys Conference, 2018

2017

Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation.

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

Trans. Assoc. Comput. Linguistics, 2017

In-Datacenter Performance Analysis of a Tensor Processing Unit.

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

CoRR, 2017

In-Datacenter Performance Analysis of a Tensor Processing Unit.

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

Proceedings of the 44th Annual International Symposium on Computer Architecture, 2017

Device Placement Optimization with Reinforcement Learning.

Azalia Mirhoseini, Hieu Pham, Quoc V. Le, Benoit Steiner, Rasmus Larsen, Yuefeng Zhou, Naveen Kumar, Mohammad Norouzi, Samy Bengio, Jeff Dean

Proceedings of the 34th International Conference on Machine Learning, 2017

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc V. Le, Geoffrey E. Hinton, Jeff Dean

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

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

CoRR, 2016

TensorFlow: A system for large-scale machine learning.

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

CoRR, 2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

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

CoRR, 2016

Large-Scale Deep Learning For Building Intelligent Computer Systems.

Jeffrey Dean

Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Building Machine Learning Systems that Understand.

Jeff Dean

Proceedings of the 2016 International Conference on Management of Data, 2016

TensorFlow: A System for Large-Scale Machine Learning.

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

Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation, 2016

2015

Distilling the Knowledge in a Neural Network.

Geoffrey E. Hinton, Oriol Vinyals, Jeffrey Dean

CoRR, 2015

The rise of cloud computing systems.

Jeffrey Dean

Proceedings of the SOSP History Day 2015, Monterey, California, USA, October 4, 2015, 2015

2014

The Beckman Report on Database Research.

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

SIGMOD Rec., 2014

Zero-Shot Learning by Convex Combination of Semantic Embeddings.

Mohammad Norouzi, Tomás Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea Frome, Greg Corrado, Jeffrey Dean

Proceedings of the 2nd International Conference on Learning Representations, 2014

2013

Spanner: Google's Globally Distributed Database.

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

ACM Trans. Comput. Syst., 2013

Efficient Estimation of Word Representations in Vector Space

Tomás Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean

Proceedings of the 1st International Conference on Learning Representations, 2013

Using Web Co-occurrence Statistics for Improving Image Categorization.

Samy Bengio, Jeffrey Dean, Dumitru Erhan, Eugene Ie, Quoc V. Le, Andrew Rabinovich, Jonathon Shlens, Yoram Singer

CoRR, 2013

The tail at scale.

Jeffrey Dean, Luiz André Barroso

Commun. ACM, 2013

Distributed Representations of Words and Phrases and their Compositionality.

Tomás Mikolov, Ilya Sutskever, Kai Chen, Gregory S. Corrado, Jeffrey Dean

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

DeViSE: A Deep Visual-Semantic Embedding Model.

Andrea Frome, Gregory S. Corrado, Jonathon Shlens, Samy Bengio, Jeffrey Dean, Marc'Aurelio Ranzato, Tomás Mikolov

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

On rectified linear units for speech processing.

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

Proceedings of the IEEE International Conference on Acoustics, 2013

Multilingual acoustic models using distributed deep neural networks.

Georg Heigold, Vincent Vanhoucke, Andrew W. Senior, Patrick Nguyen, Marc'Aurelio Ranzato, Matthieu Devin, Jeffrey Dean

Proceedings of the IEEE International Conference on Acoustics, 2013

2012

Large Scale Distributed Deep Networks.

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

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Building high-level features using large scale unsupervised learning.

Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Greg Corrado, Kai Chen, Jeffrey Dean, Andrew Y. Ng

Proceedings of the 29th International Conference on Machine Learning, 2012

2010

MapReduce: a flexible data processing tool.

Jeffrey Dean, Sanjay Ghemawat

Commun. ACM, 2010

Evolution and future directions of large-scale storage and computation systems at Google.

Jeffrey Dean

Proceedings of the 1st ACM Symposium on Cloud Computing, 2010

2009

Challenges in building large-scale information retrieval systems: invited talk.

Jeffrey Dean

Proceedings of the Second International Conference on Web Search and Web Data Mining, 2009

Back-off language model compression.

Boulos Harb, Ciprian Chelba, Jeffrey Dean, Sanjay Ghemawat

Proceedings of the 10th Annual Conference of the International Speech Communication Association, 2009

2008

Bigtable: A Distributed Storage System for Structured Data.

Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Michael Burrows, Tushar Chandra, Andrew Fikes, Robert E. Gruber

ACM Trans. Comput. Syst., 2008

MapReduce: simplified data processing on large clusters.

Jeffrey Dean, Sanjay Ghemawat

Commun. ACM, 2008

2007

MapReduce and Other Building Blocks for Large-Scale Distributed Systems at Google.

Jeffrey Dean

Proceedings of the 2007 USENIX Annual Technical Conference, 2007

Large Language Models in Machine Translation.

Thorsten Brants, Ashok C. Popat, Peng Xu, Franz Josef Och, Jeffrey Dean

Proceedings of the EMNLP-CoNLL 2007, 2007

2006

Bigtable: A Distributed Storage System for Structured Data (Awarded Best Paper!).

Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Michael Burrows, Tushar Chandra, Andrew Fikes, Robert Gruber

Proceedings of the 7th Symposium on Operating Systems Design and Implementation (OSDI '06), 2006

Experiences with MapReduce, an abstraction for large-scale computation.

Jeffrey Dean

Proceedings of the 15th International Conference on Parallel Architectures and Compilation Techniques (PACT 2006), 2006

LPI Linux certification - in a nutshell: a desktop quick reference: pass the LPIC-1 and LPIC-2 exams, 2nd Edition.

Steven Pritchard, Bruno Gomes Pessanha, Nicolai Langfeldt, James Stanger, Jeffrey Dean

O'Reilly, ISBN: 978-0-596-00528-3, 2006

2003

Web Search for a Planet: The Google Cluster Architecture.

Luiz André Barroso, Jeffrey Dean, Urs Hölzle

IEEE Micro, 2003

2001

LPI Linux certification in a nutshell - a desktop quick reference: covers exams 101 102 for LPI level 1.

Jeffrey Dean

O'Reilly, ISBN: 978-1-56592-748-3, 2001

2000

A Comparison of Techniques to Find Mirrored Hosts on the WWW.

Krishna Bharat, Andrei Z. Broder, Jeffrey Dean, Monika Rauch Henzinger

IEEE Data Eng. Bull., 2000

1999

Finding Related Pages in the World Wide Web.

Jeffrey Dean, Monika Rauch Henzinger

Comput. Networks, 1999

Control of Walking in the Stick Insect: From Behavior and Physiology to Modeling.

Jeffrey Dean, Thomas Kindermann, Josef Schmitz, Michael Schumm, Holk Cruse

Auton. Robots, 1999

1998

Walknet--a biologically inspired network to control six-legged walking.

Holk Cruse, Thomas Kindermann, Michael Schumm, Jeffrey Dean, Josef Schmitz

Neural Networks, 1998

1997

Continuous Profiling: Where Have All the Cycles Gone?

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

ACM Trans. Comput. Syst., 1997

Call Graph Construction in Object-Oriented Languages.

David Grove, Greg DeFouw, Jeffrey Dean, Craig Chambers

Proceedings of the 1997 ACM SIGPLAN Conference on Object-Oriented Programming Systems, 1997

<i>ProfileMe</i>: Hardware Support for Instruction-Level Profiling on Out-of-Order Processors.

Jeffrey Dean, James E. Hicks, Carl A. Waldspurger, William E. Weihl, George Z. Chrysos

Proceedings of the Thirtieth Annual IEEE/ACM International Symposium on Microarchitecture, 1997

1996

Vortex: An Optimizing Compiler for Object-Oriented Languages.

Jeffrey Dean, Greg DeFouw, David Grove, Vassily Litvinov, Craig Chambers

Proceedings of the 1996 ACM SIGPLAN Conference on Object-Oriented Programming Systems, 1996

Simplifying Neural Networks for Controlling Walking by Exploiting Physical Properties.

Holk Cruse, Christian Bartling, Jeffrey Dean, Thomas Kindermann, Josef Schmitz, Michael Schumm, Hendrik Wagner

Proceedings of the Artificial Neural Networks, 1996

1995

A modular artificial neural net for controlling a six-legged walking system.

Holk Cruse, Christian Bartling, Gennady S. Cymbalyuk, Jeffrey Dean, M. Dreifert

Biol. Cybern., 1995

Walking: A Complex Behavior Controlled by Simple Networks.

Holk Cruse, Christian Bartling, M. Dreifert, Josef Schmitz, D. E. Brunn, Jeffrey Dean, Thomas Kindermann

Adapt. Behav., 1995

Selective Specialization for Object-Oriented Languages.

Jeffrey Dean, Craig Chambers, David Grove

Proceedings of the ACM SIGPLAN'95 Conference on Programming Language Design and Implementation (PLDI), 1995

Profile-Guided Receiver Class Prediction.

David Grove, Jeffrey Dean, Charles Garrett, Craig Chambers

Proceedings of the Tenth Annual Conference on Object-Oriented Programming Systems, 1995

A Framework for Selective Recompilation in the Presence of Complex Intermodule Dependencies.

Craig Chambers, Jeffrey Dean, David Grove

Proceedings of the 17th International Conference on Software Engineering, 1995

Optimization of Object-Oriented Programs Using Static Class Hierarchy Analysis.

Jeffrey Dean, David Grove, Craig Chambers

Proceedings of the ECOOP'95, 1995

1994

Identifying Profitable Specialization in Object-Oriented Languages.

Jeffrey Dean, Craig Chambers, David Grove

Proceedings of the PEPM'94, 1994

Towards Better Inlining Decisions Using Inlining Trials.

Jeffrey Dean, Craig Chambers

Proceedings of the 1994 ACM Conference on LISP and Functional Programming, 1994

1992

A model of leg coordination in the stick insect, <i>Carausim morosus</i>.

Jeffrey Dean

Biol. Cybern., 1992

A model of leg coordination in the stick insect, <i>Carausius morosus</i>.

Jeffrey Dean

Biol. Cybern., 1992

Kinematic Model of a Stick Insect as an Example of a Six-Legged Walking System.

Uwe Müller-Wilm, Holk Cruse, Jürgen Eltze, Jeffrey Dean, Hans-Jürgen Weidemann, Friedrich Pfeiffer

Adapt. Behav., 1992