Elvis DOHMATOB
22 papers · 2016–2025 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+10 more ↓ Show less ↑
π Academic Marathon (9) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (5) π Cross-Pollinator (15)
π
Cross-Pollinator
(15)
π
Renaissance Researcher
(9)
πΊοΈ
Taxonomy Completionist
(33)
π
Triple Crown
π
Grand Slam
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(62)
π
Trend Setter
π
Century Club
(22)
π₯
Unstoppable
(7)
Conferences
ICLR (8)
ICML (7)
NIPS (4)
AISTATS (2)
AAAI (1)
Top co-authors
Keywords
rejection sampling
(2)
kernel matrix
(2)
determinantal point process
(2)
adversarial robustness
(2)
sparse coding
(1)
sparse representation
(1)
causal inference
(1)
theoretical analysis
(1)
convergence analysis
(1)
markov chain monte carlo
(1)
brain imaging
(1)
value iteration
(1)
gradient descent
(1)
kullback-leibler divergence
(1)
high-dimensional regression
(1)
generalization error
(1)
perturbation analysis
(1)
machine learning
(1)
information retrieval
(1)
learning theory
(1)
Papers
Improving the Scaling Laws of Synthetic Data with Deliberate Practice
ICML 2025
The Pitfalls of Memorization: When Memorization Hurts Generalization
ICLR 2025
An Effective Theory of Bias Amplification
ICLR 2025
Strong Model Collapse
ICLR 2025
Beyond Model Collapse: Scaling Up with Synthesized Data Requires Verification
ICLR 2025
Scaling Laws for Associative Memories
ICLR 2024
Consistent Adversarially Robust Linear Classification: Non-Parametric Setting
ICML 2024
A Tale of Tails: Model Collapse as a Change of Scaling Laws
ICML 2024
Precise Accuracy / Robustness Tradeoffs in Regression: Case of General Norms
ICML 2024
Model Collapse Demystified: The Case of Regression
NIPS 2024
Origins of Low-Dimensional Adversarial Perturbations
AISTATS 2023
Robust Linear Regression: Gradient-descent, Early-stopping, and Beyond
AISTATS 2023
Contextual bandits with concave rewards, and an application to fair ranking
ICLR 2023
Scalable Sampling for Nonsymmetric Determinantal Point Processes
ICLR 2022
Scalable MCMC Sampling for Nonsymmetric Determinantal Point Processes
ICML 2022
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
ICLR 2021
On the Convergence of Smooth Regularized Approximate Value Iteration Schemes
NIPS 2020
Distributionally Robust Counterfactual Risk Minimization
AAAI 2020
Learning disconnected manifolds: a no GANβs land
ICML 2020
Learning Nonsymmetric Determinantal Point Processes
NIPS 2019
Generalized No Free Lunch Theorem for Adversarial Robustness
ICML 2019
Learning brain regions via large-scale online structured sparse dictionary learning
NIPS 2016