Results 261 to 270 of about 468,741 (299)

Graph-based rank aggregation: a deep-learning approach

International Journal of Web Information Systems
Purpose This study aims to introduce a novel rank aggregation algorithm that leverages graph theory and deep-learning to improve the accuracy and relevance of aggregated rankings in metasearch scenarios, particularly when faced with inconsistent and low-
A. Keyhanipour
semanticscholar   +1 more source

LLM-Rank: A Graph Theoretical Approach to Pruning Large Language Models

arXiv.org
The evolving capabilities of large language models are accompanied by growing sizes and deployment costs, necessitating effective inference optimisation techniques.
David Hoffmann, Kailash Budhathoki, Matthaeus Kleindessner   +2 more
semanticscholar   +1 more source

Fast DCT+: A Family of Fast Transforms Based on Rank-One Updates of the Path Graph

IEEE International Conference on Acoustics, Speech, and Signal Processing
This paper develops fast graph Fourier transform (GFT) algorithms with O(nlogn) runtime complexity for rank-one updates of the path graph. We first show that several commonly-used audio and video coding transforms belong to this class of GFTs, which we ...
Samuel Fern'andez-Menduina, Eduardo Pavez, Antonio Ortega   +2 more
semanticscholar   +1 more source

Column and row subset selection using nuclear scores: algorithms and theory for Nyström approximation, CUR decomposition, and graph Laplacian reduction

arXiv.org
Column selection is an essential tool for structure-preserving low-rank approximation, with wide-ranging applications across many fields, such as data science, machine learning, and theoretical chemistry.
M. Fornace, Michael Lindsey
semanticscholar   +1 more source

Applying Genetic Algorithms to Validate a Conjecture in Graph Theory: The Minimum Dominating Set Problem

Mexican International Conference on Artificial Intelligence, 2023
J. Cervantes-Ojeda, María del Carmen Gómez Fuentes, Julián Fresán-Figueroa   +2 more
semanticscholar   +1 more source

Kendall rank correlation analysis of Malatya Centrality Algorithm with well-known centrality measures

Sigma Journal of Engineering and Natural Sciences
The concept of centrality is widely used in graph theory to determine the dominance of nodes within a graph. This concept is crucial for solving many real-life problems that are modeled using graphs.
Selman Yakut
semanticscholar   +1 more source

Exploring the Chameleon Effect of Contextual Dynamics in Temporal Knowledge Graph for Event Prediction

Tsinghua Science and Technology
: The ability to forecast future events brings great benefits for society and cyberspace in many public safety domains, such as civil unrest, pandemics and crimes.
Xin Liu, Yi He, Wenxin Tai, Xovee Xu, Fan Zhou, Guangchun Luo   +5 more
semanticscholar   +1 more source

Large-Scale Clustering With Anchor-Based Constrained Laplacian Rank

IEEE Transactions on Knowledge and Data Engineering
Graph-based clustering technique has garnered significant attention due to precise information characterization by pairwise graph similarity. Nevertheless, the post-processing step in traditional methods often limits clustering effects because of crucial
Zhenyu Ma, Jingyu Wang, Feiping Nie, Xuelong Li   +3 more
semanticscholar   +1 more source

Algebraic Graph Theory

Graduate texts in mathematics, 2001
Christopher D. Godsil, G. Royle
semanticscholar   +1 more source

Graph Theory

, 2016
Frank de Zeeuw
semanticscholar   +1 more source