Spencer Frei

According to our database, Spencer Frei authored at least 16 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data.

Zhiwei Xu, Yutong Wang, Spencer Frei, Gal Vardi, Wei Hu

CoRR, 2023

The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning.

Nikhil Ghosh, Spencer Frei, Wooseok Ha, Bin Yu

CoRR, 2023

Trained Transformers Learn Linear Models In-Context.

Ruiqi Zhang, Spencer Frei, Peter L. Bartlett

CoRR, 2023

The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks.

Spencer Frei, Gal Vardi, Peter L. Bartlett, Nati Srebro

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data.

Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro, Wei Hu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization.

Spencer Frei, Gal Vardi, Peter L. Bartlett, Nathan Srebro

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022

Random Feature Amplification: Feature Learning and Generalization in Neural Networks.

Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett

CoRR, 2022

Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data.

Spencer Frei, Niladri S. Chatterji, Peter L. Bartlett

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

Self-training Converts Weak Learners to Strong Learners in Mixture Models.

Spencer Frei, Difan Zou, Zixiang Chen, Quanquan Gu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Statistical Learning with Neural Networks Trained by Gradient Descent.

Spencer Frei

PhD thesis, 2021

Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent.

Spencer Frei, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Provable Robustness of Adversarial Training for Learning Halfspaces with Noise.

Difan Zou, Spencer Frei, Quanquan Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise.

Spencer Frei, Yuan Cao, Quanquan Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins.

Spencer Frei, Yuan Cao, Quanquan Gu

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Agnostic Learning of a Single Neuron with Gradient Descent.

Spencer Frei, Yuan Cao, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks.

Spencer Frei, Yuan Cao, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019