Risk Phase Transition in Spiked Regression: Alignment Driven Benign and Catastrophic Overfitting International Conference on Learning Representations (ICLR) 2026. Also Oral HILD Workshop ICML 2025
Jiping Li, Rishi Sonthalia
[Code][Published Version][Workshop Version]
Low Rank Gradients and Where to Find Them. Neural Information Processing Symposium (NeurIPS) 2025
Rishi Sonthalia, Michael Murray, Guido Montufar
[Code][Published Version]
Project and Forget: Solving Large Scale Metric Constrained Problems. Journal of Machine Learning Research. 2022
Rishi Sonthalia and Anna Gilbert
[Code][Published Version][Youtube Video]
Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding. Neural Information Processing Symposium (NeurIPS) 2020
Rishi Sonthalia and Anna Gilbert
[Code][Published Version]
Risk Phase Transition in Spiked Regression: Alignment Driven Benign and Catastrophic Overfitting International Conference on Learning Representations (ICLR) 2026. Also Oral HILD Workshop ICML 2025
Jiping Li, Rishi Sonthalia
[Code][Published Version][Workshop Version]
Low Rank Gradients and Where to Find Them. Neural Information Processing Symposium (NeurIPS) 2025
Rishi Sonthalia, Michael Murray, Guido Montufar
[Code][Published Version]
Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression. Algorithmic Learning Theory (ALT) 2025
Jackie Lok, Rishi Sonthalia, Eizaveta Rebrova
[Published Version]
Least Squares Regression Can Exhibit Under-Parameterized Double Descent. Neural Information Processing Symposium (NeurIPS) 2024
Xinyue Li, Rishi Sonthalia
[Code][Published Version]
Generalization Error without Independence: Denoising, Linear Regression, and Transfer Learning. Transactions of Machine Learning Research. 2024
Chinmaya Kausik, Kashvi Srivastava, and Rishi Sonthalia
[Code][Published Version]
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization. AISTATS Conference 2024
Yutong Wang, Rishi Sonthalia, Wei Hu
[Published Version]
Training Data Induced Double Descent and the Role of Training Noise Level. Transactions of Machine Learning Research. 2023
Rishi Sonthalia, Raj Rao Nadakuditi
[code][paper]
Spectral Neural Networks: Approximation Theory and Optimization Landscape. Journal of Machine Learning. 2026
Chenghui Li, Rishi Sonthalia, and Nicolas Garcia-Trillos
[Published Version]
Universal Approximation of Mean-Field Models via Transformers. International Conference on Machine Learning (ICML) 2025
Shiba Biswal, Karthik Elamvazhuthi, Rishi Sonthalia
[Code][Published Version]
Project and Forget: Solving Large Scale Metric Constrained Problems. Journal of Machine Learning Research. 2022
Rishi Sonthalia and Anna Gilbert
[Code][Published Version][Youtube Video]
How can classical multidimensional scaling go wrong? Neural Information Processing Symposium (NeurIPS) 2021
Rishi Sonthalia, Gregory Van Buskirk, Benjamin Raichel, and Anna Gilbert
[Published Version]
Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding. Neural Information Processing Symposium (NeurIPS) 2020
Rishi Sonthalia and Anna Gilbert
[Code][Published Version]
Generalized Metric Repair on Graphs. 17th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT) 2020
Fan Chengling, Anna Gilbert, Ben Raichel, Rishi Sonthalia, Greg Van Buskirk (Alphabetical ordering)
[Published Version]
Unsupervised Metric Learning in Presence of Missing Data. 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) 2018
Rishi Sonthalia and Anna Gilbert
[Code][Published Version]
Geometry-Preserving Neural Architectures on Manifolds with Boundary. 2026
Karthik Elamvazhuthi, Shiba Biswal, Kian Rosenblum, Arushi Katyal, Tianli Qu, Grady Ma, Rishi Sonthalia
[Preprint]
Supermodular Rank: Set Function Decomposition and Optimization. SIAM Journal on Mathematics of Data Science 2025
Rishi Sonthalia, Anna Seigal, and Guido Montufar
[Code][Published Version]
Project and Forget: Solving Large Scale Metric Constrained Problems. Journal of Machine Learning Research. 2022
Rishi Sonthalia and Anna Gilbert
[Code][Published Version][Youtube Video]
On Regularization via Early Stopping for Least Squares Regression. 2025, revised 2026
Rishi Sonthalia, Jackie Lok, Elizaveta Rebrova.
[Preprint]
On Regularization via Early Stopping for Least Squares Regression. 2025, revised 2026
Rishi Sonthalia, Jackie Lok, Elizaveta Rebrova.
[Preprint]
Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation. 2025
Rishi Sonthalia, Raj Rao Nadakuditi
[Preprint]
Geometry-Preserving Neural Architectures on Manifolds with Boundary. 2026
Karthik Elamvazhuthi, Shiba Biswal, Kian Rosenblum, Arushi Katyal, Tianli Qu, Grady Ma, Rishi Sonthalia
[Preprint]
Spectral Neural Networks: Approximation Theory and Optimization Landscape. Journal of Machine Learning. 2026
Chenghui Li, Rishi Sonthalia, and Nicolas Garcia-Trillos
[Published Version]
Supermodular Rank: Set Function Decomposition and Optimization. SIAM Journal on Mathematics of Data Science 2025
Rishi Sonthalia, Anna Seigal, and Guido Montufar
[Code][Published Version]
Generalization Error without Independence: Denoising, Linear Regression, and Transfer Learning. Transactions of Machine Learning Research. 2024
Chinmaya Kausik, Kashvi Srivastava, and Rishi Sonthalia
[Code][Published Version]
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. Nature Machine Intelligence. 2023
Mario Kreen, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, Joa Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp. (Besides the first and last author, the rest are alphabetical)
[Code][Published Version]
Training Data Induced Double Descent and the Role of Training Noise Level. Transactions of Machine Learning Research. 2023
Rishi Sonthalia and Raj Rao Nadakuditi
[Code][Published Version]
Project and Forget: Solving Large Scale Metric Constrained Problems. Journal of Machine Learning Research. 2022
Rishi Sonthalia and Anna Gilbert
[Code][Published Version][Youtube Video]
Risk Phase Transition in Spiked Regression: Alignment Driven Benign and Catastrophic Overfitting International Conference on Learning Representations (ICLR) 2026
Jipining Li, Rishi Sonthalia
[Code][Published Version]
Low Rank Gradients and Where to Find Them. Neural Information Processing Symposium (NeurIPS) 2025
Rishi Sonthalia, Michael Murray, Guido Montufar
[Code][Published Version]
Universal Approximation of Mean-Field Models via Transformers. International Conference on Machine Learning (ICML) 2025
Shiba Biswal, Karthik Elamvazhuthi, Rishi Sonthalia
[Code][Published Version]
Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression. Algorithmic Learning Theory (ALT) 2025
Jackie Lok, Rishi Sonthalia, Eizaveta Rebrova
[Published Version]
Least Squares Regression Can Exhibit Under-Parameterized Double Descent. Neural Information Processing Symposium (NeurIPS) 2024
Xinyue Li, Rishi Sonthalia
[Code][Published Version]
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization. AISTATS Conference 2024
Yutong Wang, Rishi Sonthalia, Wei Hu
[Published Version]
How can classical multidimensional scaling go wrong? Neural Information Processing Symposium (NeurIPS) 2021
Rishi Sonthalia, Gregory Van Buskirk, Benjamin Raichel, and Anna Gilbert
[Published Version]
Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding. Neural Information Processing Symposium (NeurIPS) 2020
Rishi Sonthalia and Anna Gilbert
[Code][Published Version]
Generalized Metric Repair on Graphs. 17th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT) 2020
Fan Chengling, Anna Gilbert, Ben Raichel, Rishi Sonthalia, Greg Van Buskirk (Alphabetical ordering)
[Published Version]
Unsupervised Metric Learning in Presence of Missing Data. 56th Annual Allerton Conference on Communication, Control, and Computing (Allerton) 2018
Rishi Sonthalia and Anna Gilbert
[Code][Published Version]
RelWire: Metric Based Graph Rewiring. NeurIPS Workshop on Symmetry and Geometry in Neural Representations 2024
Rishi Sonthalia, Anna Gilbert, and Matthew Durham
[Published Version]
CubeRep: Learning Relations Between Different Views of Data. Proceedings of Machine Learning Research Volume: Topological, Algebraic, and Geometric Learning. 2022
Rishi Sonthalia, Anna Gilbert, Matthew Durham
[Published Version]
ICLR 2022 Challenge for Computational Geometry and Topology. Proceedings of Machine Learning Research Volume: Topological, Algebraic, and Geometric Learning. 2022
Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, S\oren Hauberg, Dmitriy Nielsen, Stefan Sommer, David Klindt, Erik Hermansen, Melvin Vaupel, Benjamin Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe’er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane.
[Code][Published Version]
Knowledge Graphs of the QAnon Twitter Network. IEEE BigData Conference 2022.
Clay Adams, Malvina Bohzidarova, James Chen, Andrew Gao, Zhengtong Liu, Hunter Priniski, Junyuan Lin, Rishi Sonthalia, Andrea Bertozzi, and Jeffrey Brantingham
[Code][Published Version]
Hyperbolic and Mixed Geometry Neural Networks. NeurIPS Workshop on Symmetry and Geometry in Neural Representations. 2022
Xinyue Cui and Rishi Sonthalia
[Published Version]
Dynamic Embedding-based Methods for Link Prediction in Machine Learning Semantic Network IEEE BigData Conference 2021.
Harlin Lee, Rishi Sonthalia, and Jacob Foster
[Code][Published Version]
An Analysis of COVID-19 Knowledge Graphs Construction and Applications. IEEE BigData Conference 2021.
Dominic Flocco, Bryce Palmer-Toy, Ruixiao Wang, Hongyu Zhu, Rishi Sonthalia, Junyuan Lin, Andrea L Bertozzi, P Jeffrey Brantingham
[Code][Published Version]