She was 19 years old and looking forward to the start of classes and reuniting with her college pals. Before joining Stanford in Fall 2016, I was an NSF post-doctoral fellow at Carnegie Mellon University ; I received a Ph.D. in mathematics from the University of Michigan in 2014, and a B.A. In Symposium on Discrete Algorithms (SODA 2018) (arXiv), Variance Reduced Value Iteration and Faster Algorithms for Solving Markov Decision Processes, Efficient (n/) Spectral Sketches for the Laplacian and its Pseudoinverse, Stability of the Lanczos Method for Matrix Function Approximation. [last name]@stanford.edu where [last name]=sidford. aaron sidford cvis sea bass a bony fish to eat. This site uses cookies from Google to deliver its services and to analyze traffic. I was fortunate to work with Prof. Zhongzhi Zhang. We organize regular talks and if you are interested and are Stanford affiliated, feel free to reach out (from a Stanford email). Oral Presentation for Misspecification in Prediction Problems and Robustness via Improper Learning. Some I am still actively improving and all of them I am happy to continue polishing. We organize regular talks and if you are interested and are Stanford affiliated, feel free to reach out (from a Stanford email). Allen Liu. Instructor: Aaron Sidford Winter 2018 Time: Tuesdays and Thursdays, 10:30 AM - 11:50 AM Room: Education Building, Room 128 Here is the course syllabus. This is the academic homepage of Yang Liu (I publish under Yang P. Liu). Prateek Jain, Sham M. Kakade, Rahul Kidambi, Praneeth Netrapalli, Aaron Sidford; 18(223):142, 2018. Unlike previous ADFOCS, this year the event will take place over the span of three weeks. with Yair Carmon, Aaron Sidford and Kevin Tian Aaron Sidford. Lower bounds for finding stationary points II: first-order methods. I am a fifth year Ph.D. student in Computer Science at Stanford University co-advised by Gregory Valiant and John Duchi. Outdated CV [as of Dec'19] Students I am very lucky to advise the following Ph.D. students: Siddartha Devic (co-advised with Aleksandra Korolova . Interior Point Methods for Nearly Linear Time Algorithms | ISL ", "A general continuous optimization framework for better dynamic (decremental) matching algorithms. Conference on Learning Theory (COLT), 2015. [pdf] [poster] International Colloquium on Automata, Languages, and Programming (ICALP), 2022, Sharper Rates for Separable Minimax and Finite Sum Optimization via Primal-Dual Extragradient Methods with Hilal Asi, Yair Carmon, Arun Jambulapati and Aaron Sidford My research focuses on AI and machine learning, with an emphasis on robotics applications.
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