Jelena Diakonikolas
29 papers · 2018–2026 · 6 venues · across top CS/AI venues
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🗺️ Taxonomy Completionist (33) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
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Keyword Champion
(3)
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Keyword Pioneer
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Topic Evolution
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Triple Crown
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(18)
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Century Club · Bronze
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Prolific Year · Productive
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Unstoppable · Bronze
Top co-authors
Research topics
Keywords
convex optimization
(9)
variance reduction
(8)
sample complexity
(4)
primal-dual algorithm
(3)
monotone inclusion
(3)
robust learning
(3)
adversarial label noise
(3)
halpern iteration
(3)
distributionally robust optimization
(2)
nonsmooth optimization
(2)
conditional gradient
(2)
non-convex optimization
(2)
projection-free optimization
(2)
convergence analysis
(2)
oracle complexity
(2)
strong convexity
(2)
learning theory
(2)
composite optimization
(2)
stochastic optimization
(2)
robust optimization
(2)
Papers
Linear Regression under Missing or Corrupted Coordinates
COLT 2026
Last Iterate Convergence of Incremental Methods as a Model of Forgetting
ICLR 2025
Robustly Learning Monotone Generalized Linear Models via Data Augmentation
COLT 2025
Drago: Primal-Dual Coupled Variance Reduction for Faster Distributionally Robust Optimization
NeurIPS 2024
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
NeurIPS 2024
Robustly Learning Single-Index Models via Alignment Sharpness
ICML 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
NeurIPS 2024
Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective
NeurIPS 2024
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
ICLR 2024
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
ICML 2023
Block-Coordinate Methods and Restarting for Solving Extensive-Form Games
NeurIPS 2023
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
ICML 2023
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise
COLT 2023
Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
NeurIPS 2023
Robustly Learning a Single Neuron via Sharpness
ICML 2023
Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing
NeurIPS 2023
A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data
NeurIPS 2022
Coordinate Linear Variance Reduction for Generalized Linear Programming
NeurIPS 2022
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions
NeurIPS 2022
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
AISTATS 2021
Parameter-free Locally Accelerated Conditional Gradients
ICML 2021
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
ICML 2021
Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities
COLT 2020
Langevin Monte Carlo without smoothness
AISTATS 2020
Locally Accelerated Conditional Gradients
AISTATS 2020
Lower Bounds for Parallel and Randomized Convex Optimization
JMLR 2020
Lower Bounds for Parallel and Randomized Convex Optimization
COLT 2019
Alternating Randomized Block Coordinate Descent
ICML 2018
On Acceleration with Noise-Corrupted Gradients
ICML 2018