Damian, Alex

12 publications

COLT 2025 Learning Compositional Functions with Transformers from Easy-to-Hard Data Zixuan Wang, Eshaan Nichani, Alberto Bietti, Alex Damian, Daniel Hsu, Jason D Lee, Denny Wu

NeurIPS 2025 The Generative Leap: Tight Sample Complexity for Efficiently Learning Gaussian Multi-Index Models Alex Damian, Jason D. Lee, Joan Bruna

ICLR 2025 Understanding Optimization in Deep Learning with Central Flows Jeremy Cohen, Alex Damian, Ameet Talwalkar, J Zico Kolter, Jason D. Lee

COLT 2024 Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract) Alex Damian, Loucas Pillaud-Vivien, Jason Lee, Joan Bruna

ICML 2024 How Transformers Learn Causal Structure with Gradient Descent Eshaan Nichani, Alex Damian, Jason D. Lee

NeurIPS 2023 Fine-Tuning Language Models with Just Forward Passes Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason Lee, Danqi Chen, Sanjeev Arora

ICMLW 2023 Fine-Tuning Language Models with Just Forward Passes Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora

NeurIPS 2023 Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks Eshaan Nichani, Alex Damian, Jason Lee

ICLR 2023 Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability Alex Damian, Eshaan Nichani, Jason D. Lee

NeurIPS 2023 Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models Alex Damian, Eshaan Nichani, Rong Ge, Jason Lee

NeurIPSW 2022 Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability Alex Damian, Eshaan Nichani, Jason D. Lee

NeurIPS 2021 Label Noise SGD Provably Prefers Flat Global Minimizers Alex Damian, Tengyu Ma, Jason Lee