Stephen Tu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
24
Venues
12
Active years
2010–2026
Best venue rank
A*
Where they publish
Papers
24 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | COLT | On the Asymptotics of Self-Supervised Pre-training: Two-Stage M-Estimation and Representation Symmetry. | Mohammad Tinati, Stephen Tu |
| 2025 | ICLR | Shallow diffusion networks provably learn hidden low-dimensional structure. | Nicholas Matthew Boffi, Arthur Jacot, Stephen Tu, Ingvar M. Ziemann |
| 2024 | ICML | Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss. | Ingvar M. Ziemann, Stephen Tu, George J. Pappas, Nikolai Matni |
| 2023 | CoRL | Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners. | Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar |
| 2023 | ICML | Bootstrapped Representations in Reinforcement Learning. | Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc G. Bellemare, Will Dabney |
| 2023 | ICML | The Power of Learned Locally Linear Models for Nonlinear Policy Optimization. | Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu |
| 2023 | ICRA | Visual Backtracking Teleoperation: A Data Collection Protocol for Offline Image-Based Reinforcement Learning. | David Brandfonbrener, Stephen Tu, Avi Singh, Stefan Welker, Chad Boodoo, Nikolai Matni, Jake Varley |
| 2022 | AISTATS | The role of optimization geometry in single neuron learning. | Nicholas M. Boffi, Stephen Tu, Jean-Jacques E. Slotine |
| 2022 | AISTATS | On the Generalization of Representations in Reinforcement Learning. | Charline Le Lan, Stephen Tu, Adam Oberman, Rishabh Agarwal, Marc G. Bellemare |
| 2022 | CoRL | Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigation. | Xuesu Xiao, Tingnan Zhang, Krzysztof Marcin Choromanski, Tsang-Wei Edward Lee, Anthony G. Francis, Jake Varley, Stephen Tu, Sumeet Singh, Peng Xu, Fei Xia, Sven Mikael Persson, Dmitry Kalashnikov, Leila Takayama, Roy Frostig, Jie Tan, Carolina Parada, Vikas Sindhwani |
| 2020 | CoRL | Learning Stability Certificates from Data. | Nicholas M. Boffi, Stephen Tu, Nikolai Matni, Jean-Jacques E. Slotine, Vikas Sindhwani |
| 2020 | CoRL | Learning Hybrid Control Barrier Functions from Data. | Lars Lindemann, Haimin Hu, Alexander Robey, Hanwen Zhang, Dimos V. Dimarogonas, Stephen Tu, Nikolai Matni |
| 2020 | ICLR | Observational Overfitting in Reinforcement Learning. | Xingyou Song, Yiding Jiang, Stephen Tu, Yilun Du, Behnam Neyshabur |
| 2019 | COLT | The Gap Between Model-Based and Model-Free Methods on the Linear Quadratic Regulator: An Asymptotic Viewpoint. | Stephen Tu, Benjamin Recht |
| 2018 | COLT | Learning Without Mixing: Towards A Sharp Analysis of Linear System Identification. | Max Simchowitz, Horia Mania, Stephen Tu, Michael I. Jordan, Benjamin Recht |
| 2018 | ICML | Least-Squares Temporal Difference Learning for the Linear Quadratic Regulator. | Stephen Tu, Benjamin Recht |
| 2017 | ICML | Breaking Locality Accelerates Block Gauss-Seidel. | Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson, Alex Gittens, Michael I. Jordan, Benjamin Recht |
| 2016 | ICML | Low-rank Solutions of Linear Matrix Equations via Procrustes Flow. | Stephen Tu, Ross Boczar, Max Simchowitz, Mahdi Soltanolkotabi, Ben Recht |
| 2015 | NDSS | Machine Learning Classification over Encrypted Data. | Raphael Bost, Raluca Ada Popa, Stephen Tu, Shafi Goldwasser |
| 2014 | OSDI | Fast Databases with Fast Durability and Recovery Through Multicore Parallelism. | Wenting Zheng, Stephen Tu, Eddie Kohler, Barbara Liskov |
| 2013 | SOSP | Speedy transactions in multicore in-memory databases. | Stephen Tu, Wenting Zheng, Eddie Kohler, Barbara Liskov, Samuel Madden |
| 2012 | OOPSLA | The HipHop compiler for PHP. | Haiping Zhao, Iain Proctor, Minghui Yang, Xin Qi, Mark Williams, Qi Gao, Guilherme Ottoni, Andrew Paroski, Scott MacVicar, Jason Evans, Stephen Tu |
| 2010 | CLOUD | The case for PIQL: a performance insightful query language. | Michael Armbrust, Nick Lanham, Stephen Tu, Armando Fox, Michael J. Franklin, David A. Patterson |
| 2010 | SIGMOD | PIQL: a performance insightful query language. | Michael Armbrust, Stephen Tu, Armando Fox, Michael J. Franklin, David A. Patterson, Nick Lanham, Beth Trushkowsky, Jesse Trutna |