activity
20202026
most citedcoverforest: Conformal Predictions with Random Forest in Python

2 citations · 6 across the 11 of their papers we have counts for

collaborators

11 papers

math.ST2026

Minimax Optimal Estimation of Transport-Growth Pairs in Unbalanced Optimal Transport

Donlapark Ponnoprat, Noboru Isobe, Masaaki Imaizumi

Unbalanced optimal transport (UOT) extends classical optimal transport to measures with different total masses, but statistical guarantees for Monge-type estimation remain limited.…

stat.ML2026

Conditional Counterfactual Mean Embeddings: Doubly Robust Estimation and Learning Rates

Thatchanon Anancharoenkij, Donlapark Ponnoprat

A complete understanding of heterogeneous treatment effects involves characterizing the full conditional distribution of potential outcomes. To this end, we propose the Conditional…

cs.SI2025

Counting Graphlets of Size under Local Differential Privacy

Vorapong Suppakitpaisarn, Donlapark Ponnoprat, Nicha Hirankarn +1

The problem of counting subgraphs or graphlets under local differential privacy is an important challenge that has attracted significant attention from researchers. However, much o…

math.ST2025

Minimax Rates of Estimation for Optimal Transport Map between Infinite-Dimensional Spaces

Donlapark Ponnoprat, Masaaki Imaizumi

We investigate the estimation of an optimal transport map between probability measures on an infinite-dimensional space and reveal its minimax optimal rate. Optimal transport theor…

stat.ML2025★ 2 cited

coverforest: Conformal Predictions with Random Forest in Python

Panisara Meehinkong, Donlapark Ponnoprat

Conformal prediction provides a framework for uncertainty quantification, specifically in the forms of prediction intervals and sets with distribution-free guaranteed coverage. Whi…

cs.CR2024★ 2 cited

Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction Attack

Chayadon Lumbut, Donlapark Ponnoprat

This study investigates privacy leakage in dimensionality reduction methods through a novel machine learning-based reconstruction attack. Employing an informed adversary threat mod…

math.ST2023★ 1 cited

Uniform Confidence Band for Optimal Transport Map on One-Dimensional Data

Donlapark Ponnoprat, Ryo Okano, Masaaki Imaizumi

We develop a statistical inference method for an optimal transport map between distributions on real numbers with uniform confidence bands. The concept of optimal transport (OT) is…

cs.LG2022

Developing A Visual-Interactive Interface for Electronic Health Record Labeling: An Explainable Machine Learning Approach

Donlapark Ponnoprat, Parichart Pattarapanitchai, Phimphaka Taninpong +3

Labeling a large number of electronic health records is expensive and time consuming, and having a labeling assistant tool can significantly reduce medical experts' workload. Never…

cs.CR2022★ 1 cited

Detecting Anomalous LAN Activities under Differential Privacy

Norrathep Rattanavipanon, Donlapark Ponnoprat, Hideya Ochiai +3

Anomaly detection has emerged as a popular technique for detecting malicious activities in local area networks (LANs). Various aspects of LAN anomaly detection have been widely stu…

cs.CR2021

Dirichlet Mechanism for Differentially Private KL Divergence Minimization

Donlapark Ponnoprat

Given an empirical distribution of sensitive data , we consider the task of minimizing over a probability simplex, while protecting t…

stat.ML2020

Universal consistency of Wasserstein -NN classifier: Negative and Positive Results

Donlapark Ponnoprat

The Wasserstein distance provides a notion of dissimilarities between probability measures, which has recent applications in learning of structured data with varying size such as i…