Generalization Bounds for Data-Driven Numerical Linear Algebra
Peter Bartlett, Piotr Indyk, Tal Wagner
May 2022
July 2, 2022 –
July 5, 2022
Microsoft at COLT 2022
Location: London, UK
Publications
Publications
Publications by Year
-
Improved Analysis for a Proximal Algorithm for Sampling
Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono
COLT 2022 | May 2022
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation
Dylan Foster, Akshay Krishnamurthy, David Simchi-Levi, Yunzong Xu
2022 Conference on Learning Theory | May 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information
Yonathan Efroni, Dylan Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford
2022 Conference on Learning Theory | May 2022
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo
Krishnakumar Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Matthew Zhang
COLT 2022 | May 2022
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
-
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Meena Jagadeesan, Ilya P. Razenshteyn, Suriya Gunasekar
COLT 2022 | September 2021
The Price of Tolerance in Distribution Testing
Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li
COLT 2022 | June 2021
Toward Instance-Optimal State Certification With Incoherent Measurements
Sitan Chen, Jerry Li, Ryan O’Donnell
COLT 2022 | February 2021
Publications by Research Area
-
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo
Krishnakumar Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Matthew Zhang
COLT 2022 | May 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information
Yonathan Efroni, Dylan Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford
2022 Conference on Learning Theory | May 2022
Improved Analysis for a Proximal Algorithm for Sampling
Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono
COLT 2022 | May 2022
Generalization Bounds for Data-Driven Numerical Linear Algebra
Peter Bartlett, Piotr Indyk, Tal Wagner
May 2022
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation
Dylan Foster, Akshay Krishnamurthy, David Simchi-Levi, Yunzong Xu
2022 Conference on Learning Theory | May 2022
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Meena Jagadeesan, Ilya P. Razenshteyn, Suriya Gunasekar
COLT 2022 | September 2021
The Price of Tolerance in Distribution Testing
Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li
COLT 2022 | June 2021
Toward Instance-Optimal State Certification With Incoherent Measurements
Sitan Chen, Jerry Li, Ryan O’Donnell
COLT 2022 | February 2021
-
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo
Krishnakumar Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Matthew Zhang
COLT 2022 | May 2022
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
-
Generalization Bounds for Data-Driven Numerical Linear Algebra
Peter Bartlett, Piotr Indyk, Tal Wagner
May 2022
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
-
Toward Instance-Optimal State Certification With Incoherent Measurements
Sitan Chen, Jerry Li, Ryan O’Donnell
COLT 2022 | February 2021
-
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
Publications by Type
-
Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo
Krishnakumar Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Matthew Zhang
COLT 2022 | May 2022
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information
Yonathan Efroni, Dylan Foster, Dipendra Misra, Akshay Krishnamurthy, John Langford
2022 Conference on Learning Theory | May 2022
Improved Analysis for a Proximal Algorithm for Sampling
Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono
COLT 2022 | May 2022
Offline Reinforcement Learning: Fundamental Barriers for Value Function Approximation
Dylan Foster, Akshay Krishnamurthy, David Simchi-Levi, Yunzong Xu
2022 Conference on Learning Theory | May 2022
Private Convex Optimization via Exponential Mechanism
Sivakanth Gopi, Yin Tat Lee, Daogao Liu
COLT 2022 | March 2022
Inductive Bias of Multi-Channel Linear Convolutional Networks with Bounded Weight Norm
Meena Jagadeesan, Ilya P. Razenshteyn, Suriya Gunasekar
COLT 2022 | September 2021
The Price of Tolerance in Distribution Testing
Clément L. Canonne, Ayush Jain, Gautam Kamath, Jerry Li
COLT 2022 | June 2021
Toward Instance-Optimal State Certification With Incoherent Measurements
Sitan Chen, Jerry Li, Ryan O’Donnell
COLT 2022 | February 2021
-
Generalization Bounds for Data-Driven Numerical Linear Algebra
Peter Bartlett, Piotr Indyk, Tal Wagner
May 2022