Alex Damian

21 papers A* 9Journal 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
Improved high-dimensional estimation with Langevin dynamics and stochastic weight averaging.
CoRR
Stanley Wei, Alex Damian, Jason D. Lee
2025 A* conf
Learning Compositional Functions with Transformers from Easy-to-Hard Data.
COLT
Zixuan Wang, Eshaan Nichani, Alberto Bietti, Alex Damian, Daniel Hsu, Jason D. Lee, Denny Wu
2025 J jnl
Learning Compositional Functions with Transformers from Easy-to-Hard Data.
CoRR
Zixuan Wang, Eshaan Nichani, Alberto Bietti, Alex Damian, Daniel Hsu, Jason D. Lee, Denny Wu
2025 J jnl
The Generative Leap: Sharp Sample Complexity for Efficiently Learning Gaussian Multi-Index Models.
CoRR
Alex Damian, Jason D. Lee, Joan Bruna
2025 A* conf
Understanding Optimization in Deep Learning with Central Flows.
ICLR
Jeremy Cohen, Alex Damian, Ameet Talwalkar, J. Zico Kolter, Jason D. Lee
2024 A* conf
Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract).
COLT
Alex Damian, Loucas Pillaud-Vivien, Jason D. Lee, Joan Bruna
2024 J jnl
Computational-Statistical Gaps in Gaussian Single-Index Models.
CoRR
Alex Damian, Loucas Pillaud-Vivien, Jason D. Lee, Joan Bruna
2024 A* conf
How Transformers Learn Causal Structure with Gradient Descent.
ICML
Eshaan Nichani, Alex Damian, Jason D. Lee
2024 J jnl
How Transformers Learn Causal Structure with Gradient Descent.
CoRR
Eshaan Nichani, Alex Damian, Jason D. Lee
2024 J jnl
Understanding Optimization in Deep Learning with Central Flows.
CoRR
Jeremy Cohen, Alex Damian, Ameet Talwalkar, Zico Kolter, Jason D. Lee
2023 A* conf
Fine-Tuning Language Models with Just Forward Passes.
NeurIPS
Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora
2023 J jnl
Fine-Tuning Language Models with Just Forward Passes.
CoRR
Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora
2023 A* conf
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks.
NeurIPS
Eshaan Nichani, Alex Damian, Jason D. Lee
2023 J jnl
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks.
CoRR
Eshaan Nichani, Alex Damian, Jason D. Lee
2023 A* conf
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability.
ICLR
Alex Damian, Eshaan Nichani, Jason D. Lee
2023 A* conf
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models.
NeurIPS
Alex Damian, Eshaan Nichani, Rong Ge, Jason D. Lee
2023 J jnl
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models.
CoRR
Alex Damian, Eshaan Nichani, Rong Ge, Jason D. Lee
2022 J jnl
Neural Networks can Learn Representations with Gradient Descent.
CoRR
Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi
2022 J jnl
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability.
CoRR
Alex Damian, Eshaan Nichani, Jason D. Lee
2021 A* conf
Label Noise SGD Provably Prefers Flat Global Minimizers.
NeurIPS
Alex Damian, Tengyu Ma, Jason D. Lee
2021 J jnl
Label Noise SGD Provably Prefers Flat Global Minimizers.
CoRR
Alex Damian, Tengyu Ma, Jason D. Lee