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ORCIDAdityanarayanan Radhakrishnan
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Books and Theses
- 2023
[b1]Adityanarayanan Radhakrishnan:
Foundations of Machine Learning: Over-parameterization and Feature Learning. MIT, USA, 2023
Journal Articles
- 2020
- [j2]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler
:
Overparameterized neural networks implement associative memory. Proc. Natl. Acad. Sci. USA 117(44): 27162-27170 (2020) - 2018
- [j1]Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler:
Counting Markov equivalence classes for DAG models on trees. Discret. Appl. Math. 244: 170-185 (2018)
Conference and Workshop Papers
- 2024
- [c3]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Quadratic models for understanding catapult dynamics of neural networks. ICLR 2024 - [c2]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. ICML 2024 - 2017
- [c1]Adityanarayanan Radhakrishnan, Liam Solus, Caroline Uhler:
Counting Markov Equivalence Classes by Number of Immoralities. UAI 2017
Informal and Other Publications
- 2024
- [i17]Adityanarayanan Radhakrishnan, Mikhail Belkin, Dmitriy Drusvyatskiy:
Linear Recursive Feature Machines provably recover low-rank matrices. CoRR abs/2401.04553 (2024) - [i16]Neil Mallinar, Daniel Beaglehole, Libin Zhu, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin:
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product. CoRR abs/2407.20199 (2024) - 2023
- [i15]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. CoRR abs/2306.04815 (2023) - [i14]Daniel Beaglehole, Adityanarayanan Radhakrishnan, Parthe Pandit, Mikhail Belkin:
Mechanism of feature learning in convolutional neural networks. CoRR abs/2309.00570 (2023) - 2022
- [i13]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Wide and Deep Neural Networks Achieve Optimality for Classification. CoRR abs/2204.14126 (2022) - [i12]Libin Zhu, Chaoyue Liu, Adityanarayanan Radhakrishnan, Mikhail Belkin:
Quadratic models for understanding neural network dynamics. CoRR abs/2205.11787 (2022) - [i11]Adityanarayanan Radhakrishnan, Max Ruiz Luyten, Neha Prasad, Caroline Uhler:
Transfer Learning with Kernel Methods. CoRR abs/2211.00227 (2022) - [i10]Adityanarayanan Radhakrishnan, Daniel Beaglehole, Parthe Pandit, Mikhail Belkin:
Feature learning in neural networks and kernel machines that recursively learn features. CoRR abs/2212.13881 (2022) - 2021
- [i9]Saachi Jain, Adityanarayanan Radhakrishnan, Caroline Uhler:
A Mechanism for Producing Aligned Latent Spaces with Autoencoders. CoRR abs/2106.15456 (2021) - [i8]Adityanarayanan Radhakrishnan, George Stefanakis, Mikhail Belkin, Caroline Uhler:
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks. CoRR abs/2108.00131 (2021) - [i7]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Local Quadratic Convergence of Stochastic Gradient Descent with Adaptive Step Size. CoRR abs/2112.14872 (2021) - 2020
- [i6]Adityanarayanan Radhakrishnan, Eshaan Nichani, Daniel Irving Bernstein, Caroline Uhler:
Balancedness and Alignment are Unlikely in Linear Neural Networks. CoRR abs/2003.06340 (2020) - [i5]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Linear Convergence and Implicit Regularization of Generalized Mirror Descent with Time-Dependent Mirrors. CoRR abs/2009.08574 (2020) - [i4]Eshaan Nichani, Adityanarayanan Radhakrishnan, Caroline Uhler:
Do Deeper Convolutional Networks Perform Better? CoRR abs/2010.09610 (2020) - 2019
- [i3]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Overparameterized Neural Networks Can Implement Associative Memory. CoRR abs/1909.12362 (2019) - 2018
- [i2]Adityanarayanan Radhakrishnan, Mikhail Belkin, Caroline Uhler:
Downsampling leads to Image Memorization in Convolutional Autoencoders. CoRR abs/1810.10333 (2018) - 2017
- [i1]Adityanarayanan Radhakrishnan, Charles Durham, Ali Soylemezoglu, Caroline Uhler:
Patchnet: Interpretable Neural Networks for Image Classification. CoRR abs/1705.08078 (2017)
Coauthor Index
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