Khashayar Gatmiry

42 papers A* 15A 1Journal 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	High-accuracy and dimension-free sampling with diffusions. CoRR Khashayar Gatmiry, Sitan Chen, Adil Salim
2025	A*	`conf`	Computing Optimal Regularizers for Online Linear Optimization. COLT Khashayar Gatmiry, Jon Schneider, Stefanie Jegelka
2025	A*	`conf`	Learning Mixtures of Gaussians Using Diffusion Models. COLT Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee
2025	A*	`conf`	Rethinking Invariance in In-context Learning. ICLR Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang
2025	J	`jnl`	Rethinking Invariance in In-context Learning. CoRR Lizhe Fang, Yifei Wang, Khashayar Gatmiry, Lei Fang, Yisen Wang
2024	A*	`conf`	Adversarial Online Learning with Temporal Feedback Graphs. COLT Khashayar Gatmiry, Jon Schneider
2024	J	`jnl`	Adversarial Online Learning with Temporal Feedback Graphs. CoRR Khashayar Gatmiry, Jon Schneider
2024	A*	`conf`	Bandit Algorithms for Prophet Inequality and Pandora's Box. SODA Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla, Yifan Wang
2024	A*	`conf`	Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? ICML Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar
2024	J	`jnl`	Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? CoRR Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar
2024	J	`jnl`	Computing Optimal Regularizers for Online Linear Optimization. CoRR Khashayar Gatmiry, Jon Schneider, Stefanie Jegelka
2024	A	`conf`	EM for Mixture of Linear Regression with Clustered Data. AISTATS Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar
2024	J	`jnl`	Learning Mixtures of Gaussians Using Diffusion Models. CoRR Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee
2024	J	`jnl`	On the Role of Depth and Looping for In-Context Learning with Task Diversity. CoRR Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar
2024	A*	`conf`	Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala
2024	A*	`conf`	Simplicity Bias via Global Convergence of Sharpness Minimization. ICML Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka
2024	J	`jnl`	Simplicity Bias via Global Convergence of Sharpness Minimization. CoRR Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka
2024	A*	`conf`	What does guidance do? A fine-grained analysis in a simple setting. NeurIPS Muthu Chidambaram, Khashayar Gatmiry, Sitan Chen, Holden Lee, Jianfeng Lu
2024	J	`jnl`	What does guidance do? A fine-grained analysis in a simple setting. CoRR Muthu Chidambaram, Khashayar Gatmiry, Sitan Chen, Holden Lee, Jianfeng Lu
2023	J	`jnl`	A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry. CoRR Yuansi Chen, Khashayar Gatmiry
2023	J	`jnl`	A Unified Approach to Controlling Implicit Regularization via Mirror Descent. CoRR Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan
2023	J	`jnl`	A Unified Approach to Controlling Implicit Regularization via Mirror Descent. J. Mach. Learn. Res. Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan
2023	J	`jnl`	EM for Mixture of Linear Regression with Clustered Data. CoRR Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar
2023	A*	`conf`	Projection-Free Online Convex Optimization via Efficient Newton Iterations. NeurIPS Khashayar Gatmiry, Zakaria Mhammedi
2023	J	`jnl`	Projection-Free Online Convex Optimization via Efficient Newton Iterations. CoRR Khashayar Gatmiry, Zakaria Mhammedi
2023	A*	`conf`	Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. COLT Zakaria Mhammedi, Khashayar Gatmiry
2023	J	`jnl`	Sampling with Barriers: Faster Mixing via Lewis Weights. CoRR Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala
2023	J	`jnl`	The Inductive Bias of Flatness Regularization for Deep Matrix Factorization. CoRR Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank J. Reddi, Tengyu Ma, Stefanie Jegelka
2023	A*	`conf`	What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models. NeurIPS Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank J. Reddi, Stefanie Jegelka, Ching-Yao Chuang
2023	J	`jnl`	When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? CoRR Yuansi Chen, Khashayar Gatmiry
2022	J	`jnl`	Bandit Algorithms for Prophet Inequality and Pandora's Box. CoRR Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla, Yifan Wang
2022	J	`jnl`	Convergence of the Riemannian Langevin Algorithm. CoRR Khashayar Gatmiry, Santosh S. Vempala
2022	A*	`conf`	On the generalization of learning algorithms that do not converge. NeurIPS Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
2022	J	`jnl`	On the generalization of learning algorithms that do not converge. CoRR Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka
2022	J	`jnl`	Optimal algorithms for group distributionally robust optimization and beyond. CoRR Tasuku Soma, Khashayar Gatmiry, Stefanie Jegelka
2022	A*	`conf`	Optimization and Adaptive Generalization of Three layer Neural Networks. ICLR Khashayar Gatmiry, Stefanie Jegelka, Jonathan A. Kelner
2022	J	`jnl`	Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. CoRR Zakaria Mhammedi, Khashayar Gatmiry
2022	J	`jnl`	The Network Visibility Problem. ACM Trans. Inf. Syst. Khashayar Gatmiry, Manuel Gomez-Rodriguez
2020	A*	`conf`	Testing Determinantal Point Processes. NeurIPS Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka
2020	J	`jnl`	Testing Determinantal Point Processes. CoRR Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka
2018	J	`jnl`	Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification. CoRR Khashayar Gatmiry, Seyed Abolfazl Motahari
2018	J	`jnl`	On the Network Visibility Problem. CoRR Khashayar Gatmiry, Manuel Gomez-Rodriguez