Search Results for author: Ngoc Mai Tran

Found 7 papers, 3 papers with code

Improving random walk rankings with feature selection and imputation

1 code implementation29 Nov 2021 Ngoc Mai Tran, Yangxinyu Xie

The Science4cast Competition consists of predicting new links in a semantic network, with each node representing a concept and each edge representing a link proposed by a paper relating two concepts.

Imputation

Minimax Rates for High-Dimensional Random Tessellation Forests

no code implementations22 Sep 2021 Eliza O'Reilly, Ngoc Mai Tran

In this work, we show that a large class of random forests with general split directions also achieve minimax rates in arbitrary dimension.

Learning Theory

Estimating a Latent Tree for Extremes

no code implementations11 Feb 2021 Ngoc Mai Tran, Johannes Buck, Claudia Klüppelberg

The Latent River Problem has emerged as a flagship problem for causal discovery in extreme value statistics.

Causal Discovery Causal Inference

Clustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking

no code implementations19 Mar 2020 Hanlin Zhu, Xue Li, Liuyang Sun, Fei He, Zhengtuo Zhao, Lan Luan, Ngoc Mai Tran, Chong Xie

Across many areas, from neural tracking to database entity resolution, manual assessment of clusters by human experts presents a bottleneck in rapid development of scalable and specialized clustering methods.

Entity Resolution Model Selection +1

Classification on Large Networks: A Quantitative Bound via Motifs and Graphons

no code implementations24 Oct 2017 Andreas Haupt, Mohammad Khatami, Thomas Schultz, Ngoc Mai Tran

When each data point is a large graph, graph statistics such as densities of certain subgraphs (motifs) can be used as feature vectors for machine learning.

General Classification

Linear and Rational Factorization of Tropical Polynomials

1 code implementation11 Jul 2017 Bo Lin, Ngoc Mai Tran

Already for bivariate tropical polynomials, factorization is an NP-Complete problem.

Combinatorics

Cannot find the paper you are looking for? You can Submit a new open access paper.