Spencer Frei
17 papers · 2019–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (21) π§ Keyword Pioneer π Academic Marathon (6) π Conference Polyglot (6)
π
Cross-Pollinator
(10)
ποΈ
Keyword Collector
(52)
π
Century Club
(17)
π₯
Unstoppable
(7)
Conferences
ICML (4)
NIPS (4)
ICLR (3)
JMLR (3)
COLT (2)
AISTATS (1)
Top co-authors
Keywords
gradient descent
(5)
relu network
(3)
stochastic gradient descent
(3)
adversarial robustness
(2)
gradient flow
(2)
label noise
(2)
generalization bound
(2)
benign overfitting
(2)
neural network
(2)
feature learning
(2)
agnostic learning
(2)
neural network optimization
(1)
adversarial training
(1)
covariate shift
(1)
robust classification
(1)
nonconvex optimization
(1)
in-context learning
(1)
soft margin
(1)
sparse representation
(1)
margin maximization
(1)
Papers
Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context
ICLR 2025
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning
JMLR 2025
Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data
ICLR 2024
Minimum-Norm Interpolation Under Covariate Shift
ICML 2024
Trained Transformers Learn Linear Models In-Context
JMLR 2024
Random Feature Amplification: Feature Learning and Generalization in Neural Networks
JMLR 2023
Benign Overfitting in Linear Classifiers and Leaky ReLU Networks from KKT Conditions for Margin Maximization
COLT 2023
Implicit Bias in Leaky ReLU Networks Trained on High-Dimensional Data
ICLR 2023
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
NIPS 2023
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data
COLT 2022
Self-training Converts Weak Learners to Strong Learners in Mixture Models
AISTATS 2022
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
ICML 2021
Provable Robustness of Adversarial Training for Learning Halfspaces with Noise
ICML 2021
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent
NIPS 2021
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
ICML 2021
Agnostic Learning of a Single Neuron with Gradient Descent
NIPS 2020
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks
NIPS 2019