Khashayar Gatmiry

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 28

Top Topics

Top Venues

Publications

Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla, Yifan Wang
Bandit Algorithms for Prophet Inequality and Pandora's Box. SODA (2024)
Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar
EM for Mixture of Linear Regression with Clustered Data. AISTATS (2024)
Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT (2024)
Khashayar Gatmiry, Jon Schneider
Adversarial Online Learning with Temporal Feedback Graphs. COLT (2024)
Khashayar Gatmiry, Jon Schneider
Adversarial Online Learning with Temporal Feedback Graphs. CoRR (2024)
Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee
Learning Mixtures of Gaussians Using Diffusion Models. CoRR (2024)
Khashayar Gatmiry, Zakaria Mhammedi
Projection-Free Online Convex Optimization via Efficient Newton Iterations. CoRR (2023)
Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank Reddi, Stefanie Jegelka, Ching-Yao Chuang
What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models. NeurIPS (2023)
Yuansi Chen, Khashayar Gatmiry
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry. CoRR (2023)
Zakaria Mhammedi, Khashayar Gatmiry
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. COLT (2023)
Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar
EM for Mixture of Linear Regression with Clustered Data. CoRR (2023)
Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala
Sampling with Barriers: Faster Mixing via Lewis Weights. CoRR (2023)
Yuansi Chen, Khashayar Gatmiry
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? CoRR (2023)
Khashayar Gatmiry, Zakariak Mhammedi
Projection-Free Online Convex Optimization via Efficient Newton Iterations. NeurIPS (2023)
Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank Reddi, Tengyu Ma, Stefanie Jegelka
The Inductive Bias of Flatness Regularization for Deep Matrix Factorization. CoRR (2023)
Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan
A Unified Approach to Controlling Implicit Regularization via Mirror Descent. CoRR (2023)
Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla, Yifan Wang
Bandit Algorithms for Prophet Inequality and Pandora's Box. CoRR (2022)
Khashayar Gatmiry, Manuel Gomez-Rodriguez
The Network Visibility Problem. ACM Trans. Inf. Syst. 40 (2) (2022)
Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
On the generalization of learning algorithms that do not converge. CoRR (2022)
Khashayar Gatmiry, Santosh S. Vempala
Convergence of the Riemannian Langevin Algorithm. CoRR (2022)
Zakaria Mhammedi, Khashayar Gatmiry
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. CoRR (2022)
Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
On the generalization of learning algorithms that do not converge. NeurIPS (2022)
Khashayar Gatmiry, Stefanie Jegelka, Jonathan A. Kelner
Optimization and Adaptive Generalization of Three layer Neural Networks. ICLR (2022)
Tasuku Soma, Khashayar Gatmiry, Stefanie Jegelka
Optimal algorithms for group distributionally robust optimization and beyond. CoRR (2022)
Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka
Testing Determinantal Point Processes. CoRR (2020)
Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka
Testing Determinantal Point Processes. NeurIPS (2020)
Khashayar Gatmiry, Manuel Gomez-Rodriguez
On the Network Visibility Problem. CoRR (2018)
Khashayar Gatmiry, Seyed Abolfazl Motahari
Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification. CoRR (2018)