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Conference and Workshop Papers
- 2024
[c8]Zihao Wang, Eshaan Nichani, Jason D. Lee:
Learning Hierarchical Polynomials with Three-Layer Neural Networks. ICLR 2024- [c7]Eshaan Nichani, Alex Damian, Jason D. Lee:
How Transformers Learn Causal Structure with Gradient Descent. ICML 2024 - 2023
- [c6]Alex Damian, Eshaan Nichani, Jason D. Lee:
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability. ICLR 2023 - [c5]Alex Damian, Eshaan Nichani, Rong Ge, Jason D. Lee:
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models. NeurIPS 2023 - [c4]Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora:
Fine-Tuning Language Models with Just Forward Passes. NeurIPS 2023 - [c3]Eshaan Nichani, Alex Damian, Jason D. Lee:
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks. NeurIPS 2023 - 2022
- [c2]Chandler Squires, Annie Yun, Eshaan Nichani, Raj Agrawal, Caroline Uhler:
Causal Structure Discovery between Clusters of Nodes Induced by Latent Factors. CLeaR 2022: 669-687 - [c1]Eshaan Nichani, Yu Bai, Jason D. Lee:
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials. NeurIPS 2022
Informal and Other Publications
- 2024
- [i9]Eshaan Nichani, Alex Damian, Jason D. Lee:
How Transformers Learn Causal Structure with Gradient Descent. CoRR abs/2402.14735 (2024) - 2023
- [i8]Eshaan Nichani, Alex Damian, Jason D. Lee:
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks. CoRR abs/2305.06986 (2023) - [i7]Alex Damian, Eshaan Nichani, Rong Ge, Jason D. Lee:
Smoothing the Landscape Boosts the Signal for SGD: Optimal Sample Complexity for Learning Single Index Models. CoRR abs/2305.10633 (2023) - [i6]Sadhika Malladi, Tianyu Gao, Eshaan Nichani, Alex Damian, Jason D. Lee, Danqi Chen, Sanjeev Arora:
Fine-Tuning Language Models with Just Forward Passes. CoRR abs/2305.17333 (2023) - [i5]Zihao Wang, Eshaan Nichani, Jason D. Lee:
Learning Hierarchical Polynomials with Three-Layer Neural Networks. CoRR abs/2311.13774 (2023) - 2022
- [i4]Eshaan Nichani, Yu Bai, Jason D. Lee:
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials. CoRR abs/2206.03688 (2022) - [i3]Alex Damian, Eshaan Nichani, Jason D. Lee:
Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability. CoRR abs/2209.15594 (2022) - 2020
- [i2]Adityanarayanan Radhakrishnan, Eshaan Nichani, Daniel Irving Bernstein, Caroline Uhler:
Balancedness and Alignment are Unlikely in Linear Neural Networks. CoRR abs/2003.06340 (2020) - [i1]Eshaan Nichani, Adityanarayanan Radhakrishnan, Caroline Uhler:
Do Deeper Convolutional Networks Perform Better? CoRR abs/2010.09610 (2020)
Coauthor Index
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