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 go…
Collapsing Sequence-Level Data-Policy Coverage via Poisoning Attack in Offline Reinforcement Learning
Xue Zhou, Dapeng Man, Chen Xu +6
Offline reinforcement learning (RL) heavily relies on the coverage of pre-collected data over the target policy's distribution. Existing studies aim to improve data-policy coverage…
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 di…
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…