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Author Information
Weihao Kong (University of Washington)
Raghav Somani (University of Washington)
I am broadly interested in the aspects of Large-Scale Optimization and Probability theory that arise in fundamental Machine Learning.
Zhao Song (UT-Austin & University of Washington)
Sham Kakade (University of Washington)
Sham Kakade is a Gordon McKay Professor of Computer Science and Statistics at Harvard University and a co-director of the recently announced Kempner Institute. He works on the mathematical foundations of machine learning and AI. Sham's thesis helped in laying the statistical foundations of reinforcement learning. With his collaborators, his additional contributions include: one of the first provably efficient policy search methods, Conservative Policy Iteration, for reinforcement learning; developing the mathematical foundations for the widely used linear bandit models and the Gaussian process bandit models; the tensor and spectral methodologies for provable estimation of latent variable models; the first sharp analysis of the perturbed gradient descent algorithm, along with the design and analysis of numerous other convex and non-convex algorithms. He is the recipient of the ICML Test of Time Award (2020), the IBM Pat Goldberg best paper award (in 2007), INFORMS Revenue Management and Pricing Prize (2014). He has been program chair for COLT 2011. Sham was an undergraduate at Caltech, where he studied physics and worked under the guidance of John Preskill in quantum computing. He then completed his Ph.D. in computational neuroscience at the Gatsby Unit at University College London, under the supervision of Peter Dayan. He was a postdoc at the Dept. of Computer Science, University of Pennsylvania , where he broadened his studies to include computational game theory and economics from the guidance of Michael Kearns. Sham has been a Principal Research Scientist at Microsoft Research, New England, an associate professor at the Department of Statistics, Wharton, UPenn, and an assistant professor at the Toyota Technological Institute at Chicago.
Sewoong Oh (University of Washington)
More from the Same Authors
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2021 : Estimating Optimal Policy Value in Linear Contextual Bandits beyond Gaussianity »
Jonathan Lee · Weihao Kong · Aldo Pacchiano · Vidya Muthukumar · Emma Brunskill -
2021 : A Short Note on the Relationship of Information Gain and Eluder Dimension »
Kaixuan Huang · Sham Kakade · Jason Lee · Qi Lei -
2021 : Sparsity in the Partially Controllable LQR »
Yonathan Efroni · Sham Kakade · Akshay Krishnamurthy · Cyril Zhang -
2023 Poster: Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time »
Zichang Liu · Jue Wang · Tri Dao · Tianyi Zhou · Binhang Yuan · Zhao Song · Anshumali Shrivastava · Ce Zhang · Yuandong Tian · Christopher Re · Beidi Chen -
2023 Poster: Efficient List-Decodable Regression using Batches »
Abhimanyu Das · Ayush Jain · Weihao Kong · Rajat Sen -
2023 Poster: Federated Adversarial Learning: A Framework with Convergence Analysis »
Xiaoxiao Li · Zhao Song · Jiaming Yang -
2023 Poster: Sketching for First Order Method: Efficient Algorithm for Low-Bandwidth Channel and Vulnerability »
Zhao Song · Yitan Wang · Zheng Yu · Lichen Zhang -
2023 Poster: Sketching Meets Differential Privacy: Fast Algorithm for Dynamic Kronecker Projection Maintenance »
Zhao Song · Xin Yang · Yuanyuan Yang · Lichen Zhang -
2023 Poster: A Nearly-Optimal Bound for Fast Regression with $\ell_\infty$ Guarantee »
Zhao Song · Mingquan Ye · Junze Yin · Lichen Zhang -
2023 Oral: Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time »
Zichang Liu · Jue Wang · Tri Dao · Tianyi Zhou · Binhang Yuan · Zhao Song · Anshumali Shrivastava · Ce Zhang · Yuandong Tian · Christopher Re · Beidi Chen -
2022 Poster: MAML and ANIL Provably Learn Representations »
Liam Collins · Aryan Mokhtari · Sewoong Oh · Sanjay Shakkottai -
2022 Spotlight: MAML and ANIL Provably Learn Representations »
Liam Collins · Aryan Mokhtari · Sewoong Oh · Sanjay Shakkottai -
2022 Poster: De novo mass spectrometry peptide sequencing with a transformer model »
Melih Yilmaz · William Fondrie · Wout Bittremieux · Sewoong Oh · William Noble -
2022 Spotlight: De novo mass spectrometry peptide sequencing with a transformer model »
Melih Yilmaz · William Fondrie · Wout Bittremieux · Sewoong Oh · William Noble -
2021 : Sparsity in the Partially Controllable LQR »
Yonathan Efroni · Sham Kakade · Akshay Krishnamurthy · Cyril Zhang -
2021 Poster: Fast Sketching of Polynomial Kernels of Polynomial Degree »
Zhao Song · David Woodruff · Zheng Yu · Lichen Zhang -
2021 Spotlight: Fast Sketching of Polynomial Kernels of Polynomial Degree »
Zhao Song · David Woodruff · Zheng Yu · Lichen Zhang -
2021 Poster: Defense against backdoor attacks via robust covariance estimation »
Jonathan Hayase · Weihao Kong · Raghav Somani · Sewoong Oh -
2021 Spotlight: Defense against backdoor attacks via robust covariance estimation »
Jonathan Hayase · Weihao Kong · Raghav Somani · Sewoong Oh -
2021 Poster: KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning »
Ashok Vardhan Makkuva · Xiyang Liu · Mohammad Vahid Jamali · Hessam Mahdavifar · Sewoong Oh · Pramod Viswanath -
2021 Poster: How Important is the Train-Validation Split in Meta-Learning? »
Yu Bai · Minshuo Chen · Pan Zhou · Tuo Zhao · Jason Lee · Sham Kakade · Huan Wang · Caiming Xiong -
2021 Poster: FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis »
Baihe Huang · Xiaoxiao Li · Zhao Song · Xin Yang -
2021 Spotlight: KO codes: inventing nonlinear encoding and decoding for reliable wireless communication via deep-learning »
Ashok Vardhan Makkuva · Xiyang Liu · Mohammad Vahid Jamali · Hessam Mahdavifar · Sewoong Oh · Pramod Viswanath -
2021 Spotlight: How Important is the Train-Validation Split in Meta-Learning? »
Yu Bai · Minshuo Chen · Pan Zhou · Tuo Zhao · Jason Lee · Sham Kakade · Huan Wang · Caiming Xiong -
2021 Spotlight: FL-NTK: A Neural Tangent Kernel-based Framework for Federated Learning Analysis »
Baihe Huang · Xiaoxiao Li · Zhao Song · Xin Yang -
2021 Poster: Bilinear Classes: A Structural Framework for Provable Generalization in RL »
Simon Du · Sham Kakade · Jason Lee · Shachar Lovett · Gaurav Mahajan · Wen Sun · Ruosong Wang -
2021 Poster: Instabilities of Offline RL with Pre-Trained Neural Representation »
Ruosong Wang · Yifan Wu · Ruslan Salakhutdinov · Sham Kakade -
2021 Spotlight: Instabilities of Offline RL with Pre-Trained Neural Representation »
Ruosong Wang · Yifan Wu · Ruslan Salakhutdinov · Sham Kakade -
2021 Oral: Bilinear Classes: A Structural Framework for Provable Generalization in RL »
Simon Du · Sham Kakade · Jason Lee · Shachar Lovett · Gaurav Mahajan · Wen Sun · Ruosong Wang -
2021 Poster: Oblivious Sketching-based Central Path Method for Linear Programming »
Zhao Song · Zheng Yu -
2021 Spotlight: Oblivious Sketching-based Central Path Method for Linear Programming »
Zhao Song · Zheng Yu -
2020 : QA for invited talk 8 Kakade »
Sham Kakade -
2020 : Invited talk 8 Kakade »
Sham Kakade -
2020 : Speaker Panel »
Csaba Szepesvari · Martha White · Sham Kakade · Gergely Neu · Shipra Agrawal · Akshay Krishnamurthy -
2020 : Exploration, Policy Gradient Methods, and the Deadly Triad - Sham Kakade »
Sham Kakade -
2020 Poster: Soft Threshold Weight Reparameterization for Learnable Sparsity »
Aditya Kusupati · Vivek Ramanujan · Raghav Somani · Mitchell Wortsman · Prateek Jain · Sham Kakade · Ali Farhadi -
2020 Poster: Calibration, Entropy Rates, and Memory in Language Models »
Mark Braverman · Xinyi Chen · Sham Kakade · Karthik Narasimhan · Cyril Zhang · Yi Zhang -
2020 Poster: The Implicit and Explicit Regularization Effects of Dropout »
Colin Wei · Sham Kakade · Tengyu Ma -
2020 Poster: Provable Representation Learning for Imitation Learning via Bi-level Optimization »
Sanjeev Arora · Simon Du · Sham Kakade · Yuping Luo · Nikunj Umesh Saunshi -
2020 Poster: Optimal transport mapping via input convex neural networks »
Ashok Vardhan Makkuva · Amirhossein Taghvaei · Sewoong Oh · Jason Lee -
2020 Poster: InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs »
Zinan Lin · Kiran Thekumparampil · Giulia Fanti · Sewoong Oh -
2020 Test Of Time: Test of Time: Gaussian Process Optimization in the Bandit Settings: No Regret and Experimental Design »
Niranjan Srinivas · Andreas Krause · Sham Kakade · Matthias Seeger -
2019 : Keynote by Sham Kakade: Prediction, Learning, and Memory »
Sham Kakade -
2019 Poster: Online Control with Adversarial Disturbances »
Naman Agarwal · Brian Bullins · Elad Hazan · Sham Kakade · Karan Singh -
2019 Oral: Online Control with Adversarial Disturbances »
Naman Agarwal · Brian Bullins · Elad Hazan · Sham Kakade · Karan Singh -
2019 Poster: Provably Efficient Maximum Entropy Exploration »
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest -
2019 Oral: Provably Efficient Maximum Entropy Exploration »
Elad Hazan · Sham Kakade · Karan Singh · Abby Van Soest -
2019 Poster: Online Meta-Learning »
Chelsea Finn · Aravind Rajeswaran · Sham Kakade · Sergey Levine -
2019 Poster: Maximum Likelihood Estimation for Learning Populations of Parameters »
Ramya Korlakai Vinayak · Weihao Kong · Gregory Valiant · Sham Kakade -
2019 Oral: Maximum Likelihood Estimation for Learning Populations of Parameters »
Ramya Korlakai Vinayak · Weihao Kong · Gregory Valiant · Sham Kakade -
2019 Oral: Online Meta-Learning »
Chelsea Finn · Aravind Rajeswaran · Sham Kakade · Sergey Levine -
2018 Poster: Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator »
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi -
2018 Oral: Global Convergence of Policy Gradient Methods for the Linear Quadratic Regulator »
Maryam Fazel · Rong Ge · Sham Kakade · Mehran Mesbahi -
2017 Workshop: Principled Approaches to Deep Learning »
Andrzej Pronobis · Robert Gens · Sham Kakade · Pedro Domingos -
2017 Poster: How to Escape Saddle Points Efficiently »
Chi Jin · Rong Ge · Praneeth Netrapalli · Sham Kakade · Michael Jordan -
2017 Talk: How to Escape Saddle Points Efficiently »
Chi Jin · Rong Ge · Praneeth Netrapalli · Sham Kakade · Michael Jordan