Alon Brutzkus
11 papers · 2017–2024 · 5 venues · across top CS/AI venues
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Venues
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Research topics
Machine Learning
(11)
Optimization & Theory Β· Machine Learning
(9)
Deep Learning
(7)
Architectures
(6)
Core Methods
(4)
Learning Types
(4)
Artificial Intelligence
(2)
Mathematics & Optimization
(2)
Learning Paradigms
(2)
Optimization
(2)
Optimization & Theory Β· Deep Learning
(2)
Computer Vision
(1)
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(1)
Domain-Specific
(1)
Keywords
convolutional neural network
(4)
transfer learning
(2)
inductive bia
(2)
stochastic gradient descent
(2)
feature learning
(2)
gradient descent
(2)
neural network
(2)
generalization bound
(2)
sample complexity
(2)
polynomial time
(2)
linear regression
(1)
vc dimension
(1)
theoretical analysis
(1)
minimum norm
(1)
computational complexity
(1)
non-convex optimization
(1)
gaussian distribution
(1)
neural network optimization
(1)
generalization
(1)
deep learning
(1)
Papers
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
ICML 2024
Efficient Learning of CNNs using Patch Based Features
ICML 2022
On the inductive bias of neural networks for learning read-once DNFs
UAI 2022
An optimization and generalization analysis for max-pooling networks
UAI 2021
A Theoretical Analysis of Fine-tuning with Linear Teachers
NeurIPS 2021
Towards Understanding Learning in Neural Networks with Linear Teachers
ICML 2021
ID3 Learns Juntas for Smoothed Product Distributions
COLT 2020
Low Latency Privacy Preserving Inference
ICML 2019
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem
ICML 2019
SGD Learns Over-parameterized Networks that Provably Generalize on Linearly Separable Data
ICLR 2018
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
ICML 2017