95 citations · 155 across the 16 of their papers we have counts for
5 papers · 1 filter
Finding the Homology of Decision Boundaries with Active Learning
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy +1
Accurately and efficiently characterizing the decision boundary of classifiers is important for problems related to model selection and meta-learning. Inspired by topological data…
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model
John Janiczek, Parth Thaker, Gautam Dasarathy +3
Hyperspectral unmixing is an important remote sensing task with applications including material identification and analysis. Characteristic spectral features make many pure materia…
On the alpha-loss Landscape in the Logistic Model
Tyler Sypherd, Mario Diaz, Lalitha Sankar +1
We analyze the optimization landscape of a recently introduced tunable class of loss functions called -loss, , in the logistic model. This family encapsulates t…
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems
Parth Thaker, Gautam Dasarathy, Angelia Nedić
We consider the problem of recovering a complex vector from quadratic measurements . This pro…
Regularization via Structural Label Smoothing
Weizhi Li, Gautam Dasarathy, Visar Berisha
Regularization is an effective way to promote the generalization performance of machine learning models. In this paper, we focus on label smoothing, a form of output distribution r…