Theodor Misiakiewicz
12 papers · 2017–2025 · 2 venues · across top CS/AI venues
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Research topics
Machine Learning
(11)
Optimization & Theory Β· Machine Learning
(11)
Core Methods
(5)
Deep Learning
(3)
Mathematics & Optimization
(3)
Architectures
(3)
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(3)
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(1)
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Keywords
stochastic gradient descent
(5)
neural network
(4)
kernel methods
(3)
generalization error
(3)
neural tangent kernel
(3)
sparse function
(2)
learning theory
(2)
kernel ridge regression
(2)
random feature
(2)
two-layer neural network
(2)
feature learning
(1)
sample complexity
(1)
asymptotic analysis
(1)
vc dimension
(1)
global convergence
(1)
mean field theory
(1)
image classification
(1)
ridge regression
(1)
interpretability
(1)
invariance learning
(1)
Papers
A Theory of Learning with Autoregressive Chain of Thought
COLT 2025
Dimension-free deterministic equivalents and scaling laws for random feature regression
NeurIPS 2024
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
NeurIPS 2024
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics
COLT 2023
Learning with convolution and pooling operations in kernel methods
NeurIPS 2022
Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression
NeurIPS 2022
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks
COLT 2022
Learning with invariances in random features and kernel models
COLT 2021
When Do Neural Networks Outperform Kernel Methods?
NeurIPS 2020
Limitations of Lazy Training of Two-layers Neural Network
NeurIPS 2019
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit
COLT 2019
Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality
COLT 2017