Spencer Frei
17 papers · 2019–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (21) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π£ Hot Topic Early Bird π¬ Deep Specialist (13)
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Keyword Collector
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Research topics
Machine Learning
(15)
Optimization & Theory Β· Machine Learning
(15)
Core Methods
(10)
Deep Learning
(8)
Architectures
(6)
Optimization & Theory Β· Deep Learning
(5)
Learning Types Β· Machine Learning
(4)
Artificial Intelligence
(3)
Learning Paradigms
(2)
Learning Types Β· Deep Learning
(2)
Core AI
(1)
Keywords
gradient descent
(7)
benign overfitting
(4)
relu network
(4)
feature learning
(3)
stochastic gradient descent
(3)
gradient flow
(3)
non-convex optimization
(2)
adversarial robustness
(2)
neural network
(2)
in-context learning
(2)
logistic loss
(2)
agnostic learning
(2)
covariate shift
(2)
label noise
(2)
linear regression
(2)
implicit bia
(2)
leaky relu
(2)
generalization bound
(2)
neural network optimization
(1)
adversarial training
(1)
Papers
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning
JMLR 2025
Trained Transformer Classifiers Generalize and Exhibit Benign Overfitting In-Context
ICLR 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
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
Random Feature Amplification: Feature Learning and Generalization in Neural Networks
JMLR 2023
The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
NeurIPS 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
Agnostic Learning of Halfspaces with Gradient Descent via Soft Margins
ICML 2021
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
NeurIPS 2021
Agnostic Learning of a Single Neuron with Gradient Descent
NeurIPS 2020
Algorithm-Dependent Generalization Bounds for Overparameterized Deep Residual Networks
NeurIPS 2019