4 papers
Learning Confidence Ellipsoids and Applications to Robust Subspace Recovery
Chao Gao, Liren Shan, Vaidehi Srinivas +1
We study the problem of finding confidence ellipsoids for an arbitrary distribution in high dimensions. Given samples from a distribution and a confidence parameter , the g…
A hierarchy of eigencomputations for polynomial optimization on the sphere
Benjamin Lovitz, Nathaniel Johnston
We introduce a convergent hierarchy of lower bounds on the minimum value of a real form over the unit sphere. The main practical advantage of our hierarchy over the real sum-of-squ…
Computing High-dimensional Confidence Sets for Arbitrary Distributions
Chao Gao, Liren Shan, Vaidehi Srinivas +1
We study the problem of learning a high-density region of an arbitrary distribution over . Given a target coverage parameter , and sample access to an arbitrary d…
Volume Optimality in Conformal Prediction with Structured Prediction Sets
Chao Gao, Liren Shan, Vaidehi Srinivas +1
Conformal Prediction is a widely studied technique to construct prediction sets of future observations. Most conformal prediction methods focus on achieving the necessary coverage…