Alex Damian
9 papers · 2021–2025 · 4 venues · across top CS/AI venues
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Achievements
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Conference Polyglot · Bronze
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Interdisciplinary Bridge · Bronze
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Taxonomy Completionist
(15)
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Hot Topic Early Bird
Venues
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Research topics
Machine Learning
(9)
Optimization & Theory · Machine Learning
(9)
Deep Learning
(4)
Artificial Intelligence
(3)
Core Methods
(3)
Architectures
(2)
Core AI
(2)
Optimization & Theory · Deep Learning
(2)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Learning Paradigms
(1)
Resources & Methods
(1)
Statistics
(1)
Keywords
gradient descent
(4)
sample complexity
(4)
stochastic gradient descent
(2)
single-index model
(2)
neural network
(2)
transformer
(2)
optimization dynamics
(2)
learning rate
(2)
label noise
(1)
statistical query
(1)
in-context learning
(1)
mutual information
(1)
computational complexity
(1)
loss landscape
(1)
curriculum learning
(1)
computational-statistical gaps
(1)
neural network optimization
(1)
high-dimensional regression
(1)
hessian eigenvalue
(1)
causal structure
(1)
Papers
Learning Compositional Functions with Transformers from Easy-to-Hard Data
COLT 2025
Understanding Optimization in Deep Learning with Central Flows
ICLR 2025
Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract)
COLT 2024
How Transformers Learn Causal Structure with Gradient Descent
ICML 2024
Fine-Tuning Language Models with Just Forward Passes
NeurIPS 2023
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks
NeurIPS 2023
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
ICLR 2023
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models
NeurIPS 2023
Label Noise SGD Provably Prefers Flat Global Minimizers
NeurIPS 2021