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ORCIDKhashayar Gatmiry
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2020 – today
- 2024
[c12]Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar:
EM for Mixture of Linear Regression with Clustered Data. AISTATS 2024: 2341-2349- [c11]Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier. COLT 2024: 1796-1881 - [c10]Khashayar Gatmiry, Jon Schneider:
Adversarial Online Learning with Temporal Feedback Graphs. COLT 2024: 4548-4572 - [c9]Khashayar Gatmiry, Zhiyuan Li, Sashank J. Reddi, Stefanie Jegelka:
Simplicity Bias via Global Convergence of Sharpness Minimization. ICML 2024 - [c8]Khashayar Gatmiry, Nikunj Saunshi, Sashank J. Reddi, Stefanie Jegelka, Sanjiv Kumar:
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? ICML 2024 - [c7]Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla
, Yifan Wang:
Bandit Algorithms for Prophet Inequality and Pandora's Box. SODA 2024: 462-500 - [i18]Khashayar Gatmiry, Jonathan A. Kelner, Holden Lee:
Learning Mixtures of Gaussians Using Diffusion Models. CoRR abs/2404.18869 (2024) - [i17]Khashayar Gatmiry, Jon Schneider:
Adversarial Online Learning with Temporal Feedback Graphs. CoRR abs/2407.00571 (2024) - [i16]Muthu Chidambaram, Khashayar Gatmiry, Sitan Chen, Holden Lee, Jianfeng Lu:
What does guidance do? A fine-grained analysis in a simple setting. CoRR abs/2409.13074 (2024) - 2023
- [j2]Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan:
A Unified Approach to Controlling Implicit Regularization via Mirror Descent. J. Mach. Learn. Res. 24: 393:1-393:58 (2023) - [c6]Zakaria Mhammedi, Khashayar Gatmiry:
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. COLT 2023: 4473-4503 - [c5]Khashayar Gatmiry, Zhiyuan Li, Tengyu Ma, Sashank J. Reddi, Stefanie Jegelka, Ching-Yao Chuang:
What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models. NeurIPS 2023 - [c4]Khashayar Gatmiry, Zakaria Mhammedi:
Projection-Free Online Convex Optimization via Efficient Newton Iterations. NeurIPS 2023 - [i15]Khashayar Gatmiry, Jonathan A. Kelner, Santosh S. Vempala:
Sampling with Barriers: Faster Mixing via Lewis Weights. CoRR abs/2303.00480 (2023) - [i14]Yuansi Chen, Khashayar Gatmiry:
A Simple Proof of the Mixing of Metropolis-Adjusted Langevin Algorithm under Smoothness and Isoperimetry. CoRR abs/2304.04095 (2023) - [i13]Yuansi Chen, Khashayar Gatmiry:
When does Metropolized Hamiltonian Monte Carlo provably outperform Metropolis-adjusted Langevin algorithm? CoRR abs/2304.04724 (2023) - [i12]Khashayar Gatmiry, Zakaria Mhammedi:
Projection-Free Online Convex Optimization via Efficient Newton Iterations. CoRR abs/2306.11121 (2023) - [i11]Khashayar Gatmiry, Zhiyuan Li, Ching-Yao Chuang, Sashank J. Reddi, Tengyu Ma, Stefanie Jegelka:
The Inductive Bias of Flatness Regularization for Deep Matrix Factorization. CoRR abs/2306.13239 (2023) - [i10]Haoyuan Sun, Khashayar Gatmiry, Kwangjun Ahn, Navid Azizan:
A Unified Approach to Controlling Implicit Regularization via Mirror Descent. CoRR abs/2306.13853 (2023) - [i9]Amirhossein Reisizadeh, Khashayar Gatmiry, Asuman E. Ozdaglar:
EM for Mixture of Linear Regression with Clustered Data. CoRR abs/2308.11518 (2023) - 2022
- [j1]Khashayar Gatmiry, Manuel Gomez-Rodriguez:
The Network Visibility Problem. ACM Trans. Inf. Syst. 40(2): 22:1-22:42 (2022) - [c3]Khashayar Gatmiry, Stefanie Jegelka, Jonathan A. Kelner:
Optimization and Adaptive Generalization of Three layer Neural Networks. ICLR 2022 - [c2]Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka:
On the generalization of learning algorithms that do not converge. NeurIPS 2022 - [i8]Khashayar Gatmiry, Santosh S. Vempala:
Convergence of the Riemannian Langevin Algorithm. CoRR abs/2204.10818 (2022) - [i7]Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka:
On the generalization of learning algorithms that do not converge. CoRR abs/2208.07951 (2022) - [i6]Zakaria Mhammedi, Khashayar Gatmiry:
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization. CoRR abs/2211.01357 (2022) - [i5]Khashayar Gatmiry, Thomas Kesselheim, Sahil Singla, Yifan Wang:
Bandit Algorithms for Prophet Inequality and Pandora's Box. CoRR abs/2211.08586 (2022) - [i4]Tasuku Soma, Khashayar Gatmiry, Stefanie Jegelka:
Optimal algorithms for group distributionally robust optimization and beyond. CoRR abs/2212.13669 (2022) - 2020
- [c1]Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka:
Testing Determinantal Point Processes. NeurIPS 2020 - [i3]Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka:
Testing Determinantal Point Processes. CoRR abs/2008.03650 (2020)
2010 – 2019
- 2018
- [i2]Khashayar Gatmiry, Seyed Abolfazl Motahari:
Information Theoretic Bounds on Optimal Worst-case Error in Binary Mixture Identification. CoRR abs/1811.07307 (2018) - [i1]Khashayar Gatmiry, Manuel Gomez-Rodriguez:
On the Network Visibility Problem. CoRR abs/1811.07863 (2018)
Coauthor Index
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last updated on 2024-10-18 20:31 CEST by the dblp team
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