Khashayar Gatmiry
16 papers · 2020–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (5) π Cross-Pollinator (8) πΊοΈ Taxonomy Completionist (23) π§ Keyword Pioneer π Interdisciplinary Bridge
π
Conference Polyglot
(6)
ποΈ
Keyword Collector
(61)
β‘
Prolific Year
(6)
π
Century Club
(16)
β
The Questioner
(3)
Conferences
COLT (5)
NIPS (5)
ICLR (2)
ICML (2)
AISTATS (1)
JMLR (1)
Top co-authors
Keywords
regret bound
(2)
self-concordant barrier
(2)
generalization bound
(2)
online convex optimization
(2)
sample complexity
(1)
expectation maximization
(1)
online learning
(1)
theoretical analysis
(1)
parameter estimation
(1)
markov chain monte carlo
(1)
gradient descent
(1)
algorithmic stability
(1)
computational complexity
(1)
linear regression
(1)
mirror descent
(1)
distribution testing
(1)
riemannian manifold
(1)
determinantal point process
(1)
mixing time
(1)
distributed learning
(1)
Papers
Learning Mixtures of Gaussians Using Diffusion Models
COLT 2025
Rethinking Invariance in In-context Learning
ICLR 2025
Computing Optimal Regularizers for Online Linear Optimization
COLT 2025
EM for Mixture of Linear Regression with Clustered Data
AISTATS 2024
Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
ICML 2024
Sampling Polytopes with Riemannian HMC: Faster Mixing via the Lewis Weights Barrier
COLT 2024
Adversarial Online Learning with Temporal Feedback Graphs
COLT 2024
Simplicity Bias via Global Convergence of Sharpness Minimization
ICML 2024
What does guidance do? A fine-grained analysis in a simple setting
NIPS 2024
A Unified Approach to Controlling Implicit Regularization via Mirror Descent
JMLR 2023
Projection-Free Online Convex Optimization via Efficient Newton Iterations
NIPS 2023
What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models
NIPS 2023
Quasi-Newton Steps for Efficient Online Exp-Concave Optimization
COLT 2023
Optimization and Adaptive Generalization of Three layer Neural Networks
ICLR 2022
On the generalization of learning algorithms that do not converge
NIPS 2022
Testing Determinantal Point Processes
NIPS 2020