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Author Information
Beidi Chen (Stanford University)
I'm a third year Ph.D. Student at Rice University and working with Dr. Anshumali Shrivastava. My research topic is hashing in large-scale learning. I work closely with Dr. Rebecca Steorts on Record Linkage. I had my undergrad in Berkeley and my Advisor was Randy Katz. My topic was data mining.
Tri Dao (Stanford University)
Eric Winsor (Stanford University)
Zhao Song (Adobe Systems)
Atri Rudra (University at Buffalo, SUNY)
Christopher Ré (Stanford)

Christopher (Chris) Re is an associate professor in the Department of Computer Science at Stanford University. He is in the Stanford AI Lab and is affiliated with the Machine Learning Group and the Center for Research on Foundation Models. His recent work is to understand how software and hardware systems will change because of machine learning along with a continuing, petulant drive to work on math problems. Research from his group has been incorporated into scientific and humanitarian efforts, such as the fight against human trafficking, along with products from technology and companies including Apple, Google, YouTube, and more. He has also cofounded companies, including Snorkel, SambaNova, and Together, and a venture firm, called Factory. His family still brags that he received the MacArthur Foundation Fellowship, but his closest friends are confident that it was a mistake. His research contributions have spanned database theory, database systems, and machine learning, and his work has won best paper at a premier venue in each area, respectively, at PODS 2012, SIGMOD 2014, and ICML 2016. Due to great collaborators, he received the NeurIPS 2020 test-of-time award and the PODS 2022 test-of-time award. Due to great students, he received best paper at MIDL 2022, best paper runner up at ICLR22 and ICML22, and best student-paper runner up at UAI22.
More from the Same Authors
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2021 : Correct-N-Contrast: A Contrastive Approach for Improving Robustness to Spurious Correlations »
Michael Zhang · Nimit Sohoni · Hongyang Zhang · Chelsea Finn · Christopher Ré -
2021 : Combining Recurrent, Convolutional, and Continuous-Time Models with Structured Learnable Linear State-Space Layers »
Isys Johnson · Albert Gu · Karan Goel · Khaled Saab · Tri Dao · Atri Rudra · Christopher Ré -
2023 Poster: Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture »
Dan Fu · Jessica R Grogan · Isys Johnson · Simran Arora · Evan Sabri Eyuboglu · Armin Thomas · Benjamin Spector · Michael Poli · Atri Rudra · Christopher Ré -
2023 Poster: Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions »
Stefano Massaroli · Michael Poli · Dan Fu · Hermann Kumbong · David Romero · Rom Parnichkun · Aman Timalsina · Quinn McIntyre · Beidi Chen · Atri Rudra · Ce Zhang · Christopher Ré · Stefano Ermon · Yoshua Bengio -
2023 Oral: Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture »
Dan Fu · Jessica R Grogan · Isys Johnson · Simran Arora · Evan Sabri Eyuboglu · Armin Thomas · Benjamin Spector · Michael Poli · Atri Rudra · Christopher Ré -
2023 Invited Talk: Chris Re »
Christopher Ré -
2022 Poster: FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness »
Tri Dao · Dan Fu · Stefano Ermon · Atri Rudra · Christopher Ré -
2022 Poster: Decentralized Training of Foundation Models in Heterogeneous Environments »
Binhang Yuan · Yongjun He · Jared Davis · Tianyi Zhang · Tri Dao · Beidi Chen · Percy Liang · Christopher Ré · Ce Zhang -
2022 Poster: Transform Once: Efficient Operator Learning in Frequency Domain »
Michael Poli · Stefano Massaroli · Federico Berto · Jinkyoo Park · Tri Dao · Christopher Ré · Stefano Ermon -
2022 Poster: S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces »
Eric Nguyen · Karan Goel · Albert Gu · Gordon Downs · Preey Shah · Tri Dao · Stephen Baccus · Christopher Ré -
2022 Poster: Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees »
Jue WANG · Binhang Yuan · Luka Rimanic · Yongjun He · Tri Dao · Beidi Chen · Christopher Ré · Ce Zhang -
2021 : Alex Ratner and Chris Re - The Future of Data Centric AI »
Christopher Ré -
2021 Oral: Evaluating Gradient Inversion Attacks and Defenses in Federated Learning »
Yangsibo Huang · Samyak Gupta · Zhao Song · Kai Li · Sanjeev Arora -
2021 Poster: Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers »
Albert Gu · Isys Johnson · Karan Goel · Khaled Saab · Tri Dao · Atri Rudra · Christopher Ré -
2021 Poster: Locality Sensitive Teaching »
Zhaozhuo Xu · Beidi Chen · Chaojian Li · Weiyang Liu · Le Song · Yingyan Lin · Anshumali Shrivastava -
2021 Poster: Evaluating Gradient Inversion Attacks and Defenses in Federated Learning »
Yangsibo Huang · Samyak Gupta · Zhao Song · Kai Li · Sanjeev Arora -
2021 Poster: Does Preprocessing Help Training Over-parameterized Neural Networks? »
Zhao Song · Shuo Yang · Ruizhe Zhang -
2021 Poster: Rethinking Neural Operations for Diverse Tasks »
Nicholas Roberts · Mikhail Khodak · Tri Dao · Liam Li · Christopher Ré · Ameet Talwalkar -
2020 : Tree Covers: An Alternative to Metric Embeddings »
Roshni Sahoo · Ines Chami · Christopher Ré -
2020 Poster: HiPPO: Recurrent Memory with Optimal Polynomial Projections »
Albert Gu · Tri Dao · Stefano Ermon · Atri Rudra · Christopher Ré -
2020 Spotlight: HiPPO: Recurrent Memory with Optimal Polynomial Projections »
Albert Gu · Tri Dao · Stefano Ermon · Atri Rudra · Christopher Ré -
2020 Poster: No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems »
Nimit Sohoni · Jared Dunnmon · Geoffrey Angus · Albert Gu · Christopher Ré -
2019 : Posters and Coffee »
Sameer Kumar · Tomasz Kornuta · Oleg Bakhteev · Hui Guan · Xiaomeng Dong · Minsik Cho · Sören Laue · Theodoros Vasiloudis · Andreea Anghel · Erik Wijmans · Zeyuan Shang · Oleksii Kuchaiev · Ji Lin · Susan Zhang · Ligeng Zhu · Beidi Chen · Vinu Joseph · Jialin Ding · Jonathan Raiman · Ahnjae Shin · Vithursan Thangarasa · Anush Sankaran · Akhil Mathur · Martino Dazzi · Markus Löning · Darryl Ho · Emanuel Zgraggen · Supun Nakandala · Tomasz Kornuta · Rita Kuznetsova -
2019 Poster: Fast and Accurate Stochastic Gradient Estimation »
Beidi Chen · Yingchen Xu · Anshumali Shrivastava -
2018 Poster: Learning Compressed Transforms with Low Displacement Rank »
Anna Thomas · Albert Gu · Tri Dao · Atri Rudra · Christopher Ré -
2017 : Poster Session (encompasses coffee break) »
Beidi Chen · Borja Balle · Daniel Lee · iuri frosio · Jitendra Malik · Jan Kautz · Ke Li · Masashi Sugiyama · Miguel A. Carreira-Perpinan · Ramin Raziperchikolaei · Theja Tulabandhula · Yung-Kyun Noh · Adams Wei Yu -
2017 : Contributed talk: Unique Entity Estimation with Application to the Syrian Conflict »
Beidi Chen -
2017 Poster: Gaussian Quadrature for Kernel Features »
Tri Dao · Christopher M De Sa · Christopher Ré -
2017 Spotlight: Gaussian Quadrature for Kernel Features »
Tri Dao · Christopher M De Sa · Christopher Ré -
2016 Poster: Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much »
Bryan He · Christopher M De Sa · Ioannis Mitliagkas · Christopher Ré -
2016 Poster: Data Programming: Creating Large Training Sets, Quickly »
Alexander Ratner · Christopher M De Sa · Sen Wu · Daniel Selsam · Christopher Ré -
2015 : Hardware Trends for High Performance Analytics »
Christopher Ré -
2015 : Taking it Easy »
Christopher Ré -
2015 Spotlight: Rapidly Mixing Gibbs Sampling for a Class of Factor Graphs Using Hierarchy Width »
Christopher M De Sa · Ce Zhang · Kunle Olukotun · Christopher Ré · Christopher Ré -
2015 Poster: Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms »
Christopher M De Sa · Ce Zhang · Kunle Olukotun · Christopher Ré · Christopher Ré