Theodor Misiakiewicz

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 23

Top Topics

Learning Curves

Kernel Ridge Regression

Top Venues

Publications

Nirmit Joshi, Theodor Misiakiewicz, Nathan Srebro
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries. CoRR (2024)
Leonardo Defilippis, Bruno Loureiro, Theodor Misiakiewicz
Dimension-free deterministic equivalents for random feature regression. CoRR (2024)
Theodor Misiakiewicz, Basil Saeed
A non-asymptotic theory of Kernel Ridge Regression: deterministic equivalents, test error, and GCV estimator. CoRR (2024)
Hong Hu, Yue M. Lu, Theodor Misiakiewicz
Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime. CoRR (2024)
Emmanuel Abbe, Enric Boix-Adserà, Theodor Misiakiewicz
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics. CoRR (2023)
Theodor Misiakiewicz, Andrea Montanari
Six Lectures on Linearized Neural Networks. CoRR (2023)
Emmanuel Abbe, Enric Boix Adserà, Theodor Misiakiewicz
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics. COLT (2023)
Theodor Misiakiewicz, Song Mei
Learning with convolution and pooling operations in kernel methods. NeurIPS (2022)
Lechao Xiao, Hong Hu, Theodor Misiakiewicz, Yue Lu, Jeffrey Pennington
Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression. NeurIPS (2022)
Emmanuel Abbe, Enric Boix Adserà, Theodor Misiakiewicz
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks. COLT (2022)
Emmanuel Abbe, Enric Boix-Adserà, Theodor Misiakiewicz
The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks. CoRR (2022)
Theodor Misiakiewicz, Song Mei
Learning with convolution and pooling operations in kernel methods. CoRR (2021)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Learning with invariances in random features and kernel models. COLT (2021)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Learning with invariances in random features and kernel models. CoRR (2021)
Michael Celentano, Theodor Misiakiewicz, Andrea Montanari
Minimum complexity interpolation in random features models. CoRR (2021)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
When Do Neural Networks Outperform Kernel Methods? NeurIPS (2020)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
When Do Neural Networks Outperform Kernel Methods? CoRR (2020)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. CoRR (2019)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
Linearized two-layers neural networks in high dimension. CoRR (2019)
Song Mei, Theodor Misiakiewicz, Andrea Montanari
Mean-field theory of two-layers neural networks: dimension-free bounds and kernel limit. COLT (2019)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
Limitations of Lazy Training of Two-layers Neural Network. NeurIPS (2019)
Behrooz Ghorbani, Song Mei, Theodor Misiakiewicz, Andrea Montanari
Limitations of Lazy Training of Two-layers Neural Networks. CoRR (2019)
Song Mei, Theodor Misiakiewicz, Andrea Montanari, Roberto Imbuzeiro Oliveira
Solving SDPs for synchronization and MaxCut problems via the Grothendieck inequality. COLT (2017)
Marc Vuffray, Theodor Misiakiewicz
Concentration to Zero Bit-Error Probability for Regular LDPC Codes on the Binary Symmetric Channel: Proof by Loop Calculus. CoRR (2015)
Marc Vuffray, Theodor Misiakiewicz
Concentration to zero bit-error probability for regular LDPC codes on the binary symmetric channel: Proof by loop calculus. Allerton (2015)
Andrey Y. Lokhov, Theodor Misiakiewicz
Efficient reconstruction of transmission probabilities in a spreading process from partial observations. CoRR (2015)