82 citations · 103 across the 15 of their papers we have counts for
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On Regularization via Early Stopping for Least Squares Regression
Rishi Sonthalia, Jackie Lok, Elizaveta Rebrova
A fundamental problem in machine learning is understanding the effect of early stopping on the parameters obtained and the generalization capabilities of the model. Even for linear…
Spectral Neural Networks: Approximation Theory and Optimization Landscape
Chenghui Li, Rishi Sonthalia, Nicolas Garcia Trillos
There is a large variety of machine learning methodologies that are based on the extraction of spectral geometric information from data. However, the implementations of many of the…
Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers
Chinmaya Kausik, Kashvi Srivastava, Rishi Sonthalia
Despite the importance of denoising in modern machine learning and ample empirical work on supervised denoising, its theoretical understanding is still relatively scarce. One conce…
Project and Forget: Solving Large-Scale Metric Constrained Problems
Rishi Sonthalia, Anna C. Gilbert
Given a set of dissimilarity measurements amongst data points, determining what metric representation is most "consistent" with the input measurements or the metric that best captu…
Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding
Rishi Sonthalia, Anna C. Gilbert
Given data, finding a faithful low-dimensional hyperbolic embedding of the data is a key method by which we can extract hierarchical information or learn representative geometric f…
Unsupervised Metric Learning in Presence of Missing Data
Anna C. Gilbert, Rishi Sonthalia
For many machine learning tasks, the input data lie on a low-dimensional manifold embedded in a high dimensional space and, because of this high-dimensional structure, most algorit…