787 citations · 1.8k across the 51 of their papers we have counts for
29 papers · 1 filter
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
Jiacheng Guo, Minshuo Chen, Huan Wang +3
This paper studies the sample-efficiency of learning in Partially Observable Markov Decision Processes (POMDPs), a challenging problem in reinforcement learning that is known to be…
Improved Online Conformal Prediction via Strongly Adaptive Online Learning
Aadyot Bhatnagar, Huan Wang, Caiming Xiong +1
We study the problem of uncertainty quantification via prediction sets, in an online setting where the data distribution may vary arbitrarily over time. Recent work develops online…
Lower Bounds for Learning in Revealing POMDPs
Fan Chen, Huan Wang, Caiming Xiong +2
This paper studies the fundamental limits of reinforcement learning (RL) in the challenging \emph{partially observable} setting. While it is well-established that learning in Parti…
Efficient and Differentiable Conformal Prediction with General Function Classes
Yu Bai, Song Mei, Huan Wang +2
Quantifying the data uncertainty in learning tasks is often done by learning a prediction interval or prediction set of the label given the input. Two commonly desired properties f…
Learning Rich Nearest Neighbor Representations from Self-supervised Ensembles
Bram Wallace, Devansh Arpit, Huan Wang +1
Pretraining convolutional neural networks via self-supervision, and applying them in transfer learning, is an incredibly fast-growing field that is rapidly and iteratively improvin…
Merlion: A Machine Learning Library for Time Series
Aadyot Bhatnagar, Paul Kassianik, Chenghao Liu +20
We introduce Merlion, an open-source machine learning library for time series. It features a unified interface for many commonly used models and datasets for anomaly detection and…