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Comparative analyses of phylogenetic trees typically require identical taxon sets, however, in practice, trees often include distinct but overlapping taxa. Pruning non-shared leaves discards phylogenetic signal, whereas tree completion can…

种群与进化 · 定量生物学 2026-04-28 Aleksandr Koshkarov , Nadia Tahiri

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that…

统计方法学 · 统计学 2017-01-27 Max R. Tolkoff , Michael L. Alfaro , Guy Baele , Philippe Lemey , Marc A. Suchard

Factorization machine (FM) is a prevalent approach to modeling pairwise (second-order) feature interactions when dealing with high-dimensional sparse data. However, on the one hand, FM fails to capture higher-order feature interactions…

机器学习 · 计算机科学 2025-02-24 Shu Wu , Zekun Li , Yunyue Su , Zeyu Cui , Xiaoyu Zhang , Liang Wang

Matrix factorization is a widely used approach for top-N recommendation and collaborative filtering. When implemented on implicit feedback data (such as clicks), a common heuristic is to upweight the observed interactions. This strategy has…

信息检索 · 计算机科学 2025-10-14 Alex Ayoub , Samuel Robertson , Dawen Liang , Harald Steck , Nathan Kallus

Matrix factorization is a common machine learning technique for recommender systems. Despite its high prediction accuracy, the Bayesian Probabilistic Matrix Factorization algorithm (BPMF) has not been widely used on large scale data because…

分布式、并行与集群计算 · 计算机科学 2017-05-12 Tom Vander Aa , Imen Chakroun , Tom Haber

Non-negative matrix factorization (NMF) is an important technique for obtaining low dimensional representations of datasets. However, classical NMF does not take into account data that is collected at different times or in different…

机器学习 · 计算机科学 2023-11-21 James Chapman , Yotam Yaniv , Deanna Needell

Non-negative Matrix Factorization (NMF) is an intensively used technique for obtaining parts-based, lower dimensional and non-negative representation. Researchers in biology, medicine, pharmacy and other fields often prefer NMF over other…

机器学习 · 计算机科学 2025-02-04 Matej Mihelčić , Pauli Miettinen

Recommendation systems and computing advertisements have gradually entered the field of academic research from the field of commercial applications. Click-through rate prediction is one of the core research issues because the prediction…

机器学习 · 计算机科学 2019-02-26 Li Zhang , Weichen Shen , Shijian Li , Gang Pan

Phylogenetic networks generalise phylogenetic trees and allow for the accurate representation of the evolutionary history of a set of present-day species whose past includes reticulate events such as hybridisation and lateral gene transfer.…

种群与进化 · 定量生物学 2018-09-05 Joan Carles Pons , Charles Semple , Mike Steel

Knowledge tracing is a sequence prediction problem where the goal is to predict the outcomes of students over questions as they are interacting with a learning platform. By tracking the evolution of the knowledge of some student, one can…

信息检索 · 计算机科学 2018-11-16 Jill-Jênn Vie , Hisashi Kashima

The prospect of informed and optimal decision-making regarding the operation and maintenance (O&M) of structures provides impetus to the development of structural health monitoring (SHM) systems. A probabilistic risk-based framework for…

人工智能 · 计算机科学 2023-03-27 Aidan J. Hughes , Paul Gardner , Keith Worden

Nonnegative matrix factorization (NMF) has found many applications including topic modeling and document analysis. Hierarchical NMF (HNMF) variants are able to learn topics at various levels of granularity and illustrate their hierarchical…

机器学习 · 计算机科学 2022-02-16 Joshua Vendrow , Jamie Haddock , Deanna Needell

Matrix factorization is a widely adopted recommender system technique that fits scalar rating values by dot products of user feature vectors and item feature vectors. However, the formulation of matrix factorization as a scalar fitting…

信息检索 · 计算机科学 2021-12-07 Hao Wang

Cancer, with its inherent heterogeneity, is commonly categorized into distinct subtypes based on unique traits, cellular origins, and molecular markers specific to each type. However, current studies primarily rely on complete multi-omics…

机器学习 · 计算机科学 2024-11-26 Yingxuan Ren , Fengtao Ren , Bo Yang

Structural information of phylogenetic tree topologies plays an important role in phylogenetic inference. However, finding appropriate topological structures for specific phylogenetic inference tasks often requires significant design effort…

机器学习 · 统计学 2023-02-20 Cheng Zhang

Nonnegative Matrix Factorization (NMF) is a widely used technique for data representation. Inspired by the expressive power of deep learning, several NMF variants equipped with deep architectures have been proposed. However, these methods…

机器学习 · 计算机科学 2017-11-21 Yuning Qiu , Guoxu Zhou , Kan Xie

The traditional social recommendation algorithm ignores the following fact: the preferences of users with trust relationships are not necessarily similar, and the consideration of user preference similarity should be limited to specific…

信息检索 · 计算机科学 2019-03-13 Wei Peng , Baogui Xin

Although many techniques have been applied to matrix factorization (MF), they may not fully exploit the feature structure. In this paper, we incorporate the grouping effect into MF and propose a novel method called Robust Matrix…

机器学习 · 计算机科学 2021-07-09 Haiyan Jiang , Shuyu Li , Luwei Zhang , Haoyi Xiong , Dejing Dou

Phylogenetic stochastic mapping is a method for reconstructing the history of trait changes on a phylogenetic tree relating species/organisms carrying the trait. State-of-the-art methods assume that the trait evolves according to a…

统计计算 · 统计学 2014-03-21 Jan Irvahn , Vladimir N. Minin

Social recommender systems exploit users' social relationships to improve the recommendation accuracy. Intuitively, a user tends to trust different subsets of her social friends, regarding with different scenarios. Therefore, the main…

信息检索 · 计算机科学 2016-03-16 Yong Liu , Peilin Zhao , Xin Liu , Min Wu , Xiao-Li Li