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Spencer Frei
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Books and Theses
- 2021
- [b1]Spencer Frei:
Statistical Learning with Neural Networks Trained by Gradient Descent. University of California, Los Angeles, USA, 2021
Journal Articles
- 2024
- [j2]Ruiqi Zhang, Spencer Frei, Peter L. Bartlett:
Trained Transformers Learn Linear Models In-Context. J. Mach. Learn. Res. 25: 49:1-49:55 (2024) - 2023
- [j1]Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett:
Random Feature Amplification: Feature Learning and Generalization in Neural Networks. J. Mach. Learn. Res. 24: 303:1-303:49 (2023)
Conference and Workshop Papers
- 2024
- [c13]Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu:
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. ICLR 2024 - [c12]Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu:
Minimum-Norm Interpolation Under Covariate Shift. ICML 2024 - 2023
- [c11]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. COLT 2023: 3173-3228 - [c10]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu:
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. ICLR 2023 - [c9]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro:
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. NeurIPS 2023 - 2022
- [c8]Spencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu:
Self-training Converts Weak Learners to Strong Learners in Mixture Models. AISTATS 2022: 8003-8021 - [c7]Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett:
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. COLT 2022: 2668-2703 - 2021
- [c6]Spencer Frei, Yuan Cao, Quanquan Gu:
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins. ICML 2021: 3417-3426 - [c5]Spencer Frei, Yuan Cao, Quanquan Gu:
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise. ICML 2021: 3427-3438 - [c4]Difan Zou, Spencer Frei, Quanquan Gu:
Provable Robustness of Adversarial Training for Learning Halfspaces with Noise. ICML 2021: 13002-13011 - [c3]Spencer Frei, Quanquan Gu:
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent. NeurIPS 2021: 7937-7949 - 2020
- [c2]Spencer Frei, Yuan Cao, Quanquan Gu:
Agnostic Learning of a Single Neuron with Gradient Descent. NeurIPS 2020 - 2019
- [c1]Spencer Frei, Yuan Cao, Quanquan Gu:
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks. NeurIPS 2019: 14769-14779
Informal and Other Publications
- 2024
- [i18]Neil Mallinar, Austin Zane, Spencer Frei, Bin Yu:
Minimum-Norm Interpolation Under Covariate Shift. CoRR abs/2404.00522 (2024) - [i17]Spencer Frei, Gal Vardi:
Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context. CoRR abs/2410.01774 (2024) - [i16]Roey Magen, Shuning Shang, Zhiwei Xu, Spencer Frei, Wei Hu, Gal Vardi:
Benign Overfitting in Single-Head Attention. CoRR abs/2410.07746 (2024) - 2023
- [i15]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks. CoRR abs/2303.01456 (2023) - [i14]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro:
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization. CoRR abs/2303.01462 (2023) - [i13]Ruiqi Zhang, Spencer Frei, Peter L. Bartlett:
Trained Transformers Learn Linear Models In-Context. CoRR abs/2306.09927 (2023) - [i12]Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu:
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning. CoRR abs/2308.03215 (2023) - [i11]Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu:
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data. CoRR abs/2310.02541 (2023) - 2022
- [i10]Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett:
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data. CoRR abs/2202.05928 (2022) - [i9]Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett:
Random Feature Amplification: Feature Learning and Generalization in Neural Networks. CoRR abs/2202.07626 (2022) - [i8]Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu:
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data. CoRR abs/2210.07082 (2022) - 2021
- [i7]Spencer Frei, Yuan Cao, Quanquan Gu:
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise. CoRR abs/2101.01152 (2021) - [i6]Difan Zou, Spencer Frei, Quanquan Gu:
Provable Robustness of Adversarial Training for Learning Halfspaces with Noise. CoRR abs/2104.09437 (2021) - [i5]Spencer Frei, Quanquan Gu:
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent. CoRR abs/2106.13792 (2021) - [i4]Spencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu:
Self-training Converts Weak Learners to Strong Learners in Mixture Models. CoRR abs/2106.13805 (2021) - 2020
- [i3]Spencer Frei, Yuan Cao, Quanquan Gu:
Agnostic Learning of a Single Neuron with Gradient Descent. CoRR abs/2005.14426 (2020) - [i2]Spencer Frei, Yuan Cao, Quanquan Gu:
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins. CoRR abs/2010.00539 (2020) - 2019
- [i1]Spencer Frei, Yuan Cao, Quanquan Gu:
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks. CoRR abs/1910.02934 (2019)
Coauthor Index
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