1 citations · 3 across the 9 of their papers we have counts for
10 papers
Cluster-Aware Matching via Laplacian Optimal Transport
Gabriel Samberg, YoonHaeng Hur, Yuehaw Khoo +1
In many applications of matching, the point clouds to be matched are not merely unstructured sets of points but rather samples from distributions with an intrinsic cluster structur…
Weighted Conformal Clustering
Anirban Nath, YoonHaeng Hur, Genevera I. Allen
Clustering is a central tool for discovering latent structure in unlabeled data; yet modern clustering pipelines often end with a hard assignment of each observation to a cluster w…
Inference for Clustering: Conformal Sets for Cluster Labels
YoonHaeng Hur, Anirban Nath, Genevera Allen
While clustering is ubiquitously used across science and industry, uncertainty in cluster assignments is rarely quantified with rigorous guarantees. We propose a novel conformal in…
A Convexified Matching Approach to Imputation and Individualized Inference
YoonHaeng Hur, Tengyuan Liang
We introduce a new convexified matching method for missing value imputation and individualized inference inspired by computational optimal transport. Our method integrates favorabl…
Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction
Kulunu Dharmakeerthi, YoonHaeng Hur, Tengyuan Liang
Practitioners often face the challenge of deploying prediction models in new environments with shifted distributions of covariates and responses. With observational data, such shif…
Robust Point Matching with Distance Profiles
YoonHaeng Hur, Yuehaw Khoo
Computational difficulty of quadratic matching and the Gromov-Wasserstein distance has led to various approximation and relaxation schemes. One of such methods, relying on the noti…
Detecting Weak Distribution Shifts via Displacement Interpolation
YoonHaeng Hur, Tengyuan Liang
Detecting weak, systematic distribution shifts and quantitatively modeling individual, heterogeneous responses to policies or incentives have found increasing empirical application…
Generative Modeling via Tree Tensor Network States
Xun Tang, Yoonhaeng Hur, Yuehaw Khoo +1
In this paper, we present a density estimation framework based on tree tensor-network states. The proposed method consists of determining the tree topology with Chow-Liu algorithm,…
Generative modeling via tensor train sketching
YH. Hur, J. G. Hoskins, M. Lindsey +2
In this paper, we introduce a sketching algorithm for constructing a tensor train representation of a probability density from its samples. Our method deviates from the standard re…
Online Learning to Transport via the Minimal Selection Principle
Wenxuan Guo, YoonHaeng Hur, Tengyuan Liang +1
Motivated by robust dynamic resource allocation in operations research, we study the \textit{Online Learning to Transport} (OLT) problem where the decision variable is a probabilit…