Unsupervised Metric Learning in Presence of Missing Data. - Anna C. Gilbert; Rishi Sonthalia (Allerton, 2018)

Unrolling Swiss Cheese: Metric repair on manifolds with holes. - Anna C. Gilbert; Rishi Sonthalia (CoRR, 2018)

Generalized Metric Repair on Graphs. - Anna C. Gilbert; Rishi Sonthalia (CoRR, 2018)

Tree! I am no Tree! I am a low dimensional Hyperbolic Embedding. - Rishi Sonthalia; Anna C. Gilbert (NeurIPS, 2020)

Generalized Metric Repair on Graphs. - Chenglin Fan; Anna C. Gilbert; Benjamin Raichel; Rishi Sonthalia; Gregory Van Buskirk (SWAT, 2020)

Dual Regularized Optimal Transport. - Rishi Sonthalia; Anna C. Gilbert (CoRR, 2020)

An Analysis of COVID-19 Knowledge Graph Construction and Applications. - Dominic Flocco; Bryce Palmer-Toy; Ruixiao Wang 001; Hongyu Zhu; Rishi Sonthalia; Junyuan Lin; Andrea L. Bertozzi; P. Jeffrey Brantingham (IEEE BigData, 2021)

Dynamic Embedding-based Methods for Link Prediction in Machine Learning Semantic Network. - Harlin Lee; Rishi Sonthalia; Jacob G. Foster (IEEE BigData, 2021)

How can classical multidimensional scaling go wrong? - Rishi Sonthalia; Greg Van Buskirk; Benjamin Raichel; Anna C. Gilbert (NeurIPS, 2021)

Knowledge Graphs of the QAnon Twitter Network. - Clay Adams; Malvina Bozhidarova; James Chen; Andrew Gao; Zhengtong Liu; J. Hunter Priniski; Junyuan Lin; Rishi Sonthalia; Andrea L. Bertozzi; P. Jeffrey Brantingham (IEEE Big Data, 2022)

ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. - Adele Myers; Saiteja Utpala; Shubham Talbar; Sophia Sanborn; Christian Shewmake; Claire Donnat; Johan Mathe; Rishi Sonthalia; Xinyue Cui; Tom Szwagier; Arthur Pignet; Andri Bergsson; et al. (TAG-ML, 2022)

CubeRep: Learning Relations Between Different Views of Data. - Rishi Sonthalia; Anna C. Gilbert; Matthew Durham (TAG-ML, 2022)

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. - Adele Myers; Saiteja Utpala; Shubham Talbar; Sophia Sanborn; Christian Shewmake; Claire Donnat; Johan Mathe; Umberto Lupo; Rishi Sonthalia; Xinyue Cui; Tom Szwagier; Arthur Pignet; et al. (CoRR, 2022)

Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network. - Mario Krenn; Lorenzo Buffoni; Bruno C. Coutinho; Sagi Eppel; Jacob Gates Foster; Andrew Gritsevskiy; Harlin Lee; Yichao Lu; João P. Moutinho; Nima Sanjabi; Rishi Sonthalia; Ngoc Mai Tran; et al. (CoRR, 2022)

Project and Forget: Solving Large-Scale Metric Constrained Problems. - Rishi Sonthalia; Anna C. Gilbert (J. Mach. Learn. Res., 2022)

Under-Parameterized Double Descent for Ridge Regularized Least Squares Denoising of Data on a Line. - Rishi Sonthalia; Xinyue Li; Bochao Gu (CoRR, 2023)

Generalization Error without Independence: Denoising, Linear Regression, and Transfer Learning. - Chinmaya Kausik; Kashvi Srivastava; Rishi Sonthalia (CoRR, 2023)

Spectral Neural Networks: Approximation Theory and Optimization Landscape. - Chenghui Li; Rishi Sonthalia; Nicolás García Trillos (CoRR, 2023)

Training Data Size Induced Double Descent For Denoising Feedforward Neural Networks and the Role of Training Noise. - Rishi Sonthalia; Raj Rao Nadakuditi (Trans. Mach. Learn. Res., 2023)

Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network. - Mario Krenn; Lorenzo Buffoni; Bruno C. Coutinho; Sagi Eppel; Jacob Gates Foster; Andrew Gritsevskiy; Harlin Lee; Yichao Lu; João P. Moutinho; Nima Sanjabi; Rishi Sonthalia; Ngoc Mai Tran; et al. (Nat. Mac. Intell., 2023)

Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization. - Yutong Wang 002; Rishi Sonthalia; Wei Hu (AISTATS, 2024)

Least Squares Regression Can Exhibit Under-Parameterized Double Descent. - Xinyue Li; Rishi Sonthalia (NeurIPS, 2024)

Discrete error dynamics of mini-batch gradient descent for least squares regression. - Jackie Lok; Rishi Sonthalia; Elizaveta Rebrova (CoRR, 2024)

On Regularization via Early Stopping for Least Squares Regression. - Rishi Sonthalia; Jackie Lok; Elizaveta Rebrova (CoRR, 2024)

Generalization for Least Squares Regression With Simple Spiked Covariances. - Jiping Li; Rishi Sonthalia (CoRR, 2024)

Identification of Mean-Field Dynamics using Transformers. - Shiba Biswal; Karthik Elamvazhuthi; Rishi Sonthalia (CoRR, 2024)

Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers. - Chinmaya Kausik; Kashvi Srivastava; Rishi Sonthalia (Trans. Mach. Learn. Res., 2024)

Error dynamics of mini-batch gradient descent with random reshuffling for least squares regression. - Jackie Lok; Rishi Sonthalia; Elizaveta Rebrova (ALT, 2025)

Supermodular Rank: Set Function Decomposition and Optimization. - Rishi Sonthalia; Anna Seigal; Guido Montúfar (SIAM J. Math. Data Sci., 2025)

Low Rank Gradients and Where to Find Them. - Rishi Sonthalia; Michael Murray; Guido Montúfar (CoRR, 2025)

Risk Phase Transitions in Spiked Regression: Alignment Driven Benign and Catastrophic Overfitting. - Jiping Li; Rishi Sonthalia (CoRR, 2025)

Matricial Free Energy as a Gaussianizing Regularizer: Enhancing Autoencoders for Gaussian Code Generation. - Rishi Sonthalia; Raj Rao Nadakuditi (CoRR, 2025)