Khashayar Gatmiry

According to our database1, Khashayar Gatmiry authored at least 22 papers between 2018 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Learning Mixtures of Gaussians Using Diffusion Models.
CoRR, 2024

Bandit Algorithms for Prophet Inequality and Pandora's Box.
Proceedings of the 2024 ACM-SIAM Symposium on Discrete Algorithms, 2024

Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Simplicity Bias via Global Convergence of Sharpness Minimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Adversarial Online Learning with Temporal Feedback Graphs.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier.
Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

EM for Mixture of Linear Regression with Clustered Data.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
A Unified Approach to Controlling Implicit Regularization via Mirror Descent.
J. Mach. Learn. Res., 2023

The Inductive Bias of Flatness Regularization for Deep Matrix Factorization.
CoRR, 2023

When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm?
CoRR, 2023

A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry.
CoRR, 2023

Sampling with Barriers: Faster Mixing via Lewis Weights.
CoRR, 2023

Projection-Free Online Convex Optimization via Efficient Newton Iterations.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Quasi-Newton Steps for Efficient Online Exp-Concave Optimization.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
The Network Visibility Problem.
ACM Trans. Inf. Syst., 2022

Optimal algorithms for group distributionally robust optimization and beyond.
CoRR, 2022

Convergence of the Riemannian Langevin Algorithm.
CoRR, 2022

On the generalization of learning algorithms that do not converge.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Optimization and Adaptive Generalization of Three layer Neural Networks.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2020
Testing Determinantal Point Processes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018
Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification.
CoRR, 2018


  Loading...