Zobrazeno 1 - 10
of 2 982
pro vyhledávání: '"Zheng, Da"'
Autor:
Karczmarz, Adam, Zheng, Da Wei
Le and Wulff-Nilsen [SODA '24] initiated a systematic study of VC set systems to unweighted $K_h$-minor-free directed graphs. We extend their results in the following ways: $\bullet$ We present the first application of VC set systems for real-weighte
Externí odkaz:
http://arxiv.org/abs/2410.12003
Large language models (LLM) have prioritized expanding the context window from which models can incorporate more information. However, training models to handle long contexts presents significant challenges. These include the scarcity of high-quality
Externí odkaz:
http://arxiv.org/abs/2409.04774
We investigate the problem of carving an $n$-face triangulated three-dimensional polytope using a tool to make cuts modelled by either a half-plane or sweeps from an infinite ray. In the case of half-planes cuts, we present a deterministic algorithm
Externí odkaz:
http://arxiv.org/abs/2407.15981
We introduce a new balanced separator theorem for unit-disk graphs involving two shortest paths combined with the 1-hop neighbours of those paths and two other vertices. This answers an open problem of Yan, Xiang and Dragan [CGTA '12] and improves th
Externí odkaz:
http://arxiv.org/abs/2407.15980
In the Directed Steiner Tree (DST) problem the input is a directed edge-weighted graph $G=(V,E)$, a root vertex $r$ and a set $S \subseteq V$ of $k$ terminals. The goal is to find a min-cost subgraph that connects $r$ to each of the terminals. DST ad
Externí odkaz:
http://arxiv.org/abs/2407.01904
Autor:
Zhang, Shichang, Zheng, Da, Zhang, Jiani, Zhu, Qi, song, Xiang, Adeshina, Soji, Faloutsos, Christos, Karypis, George, Sun, Yizhou
Text-rich graphs, prevalent in data mining contexts like e-commerce and academic graphs, consist of nodes with textual features linked by various relations. Traditional graph machine learning models, such as Graph Neural Networks (GNNs), excel in enc
Externí odkaz:
http://arxiv.org/abs/2406.11884
Autor:
Zheng, Da, Song, Xiang, Zhu, Qi, Zhang, Jian, Vasiloudis, Theodore, Ma, Runjie, Zhang, Houyu, Wang, Zichen, Adeshina, Soji, Nisa, Israt, Mottini, Alejandro, Cui, Qingjun, Rangwala, Huzefa, Zeng, Belinda, Faloutsos, Christos, Karypis, George
Publikováno v:
KDD 2024
Graph machine learning (GML) is effective in many business applications. However, making GML easy to use and applicable to industry applications with massive datasets remain challenging. We developed GraphStorm, which provides an end-to-end solution
Externí odkaz:
http://arxiv.org/abs/2406.06022
Text-rich graphs, which exhibit rich textual information on nodes and edges, are prevalent across a wide range of real-world business applications. Large Language Models (LLMs) have demonstrated remarkable abilities in understanding text, which also
Externí odkaz:
http://arxiv.org/abs/2404.18271
Polynomial partitioning techniques have recently led to improved geometric data structures for a variety of fundamental problems related to semialgebraic range searching and intersection searching in 3D and higher dimensions (e.g., see [Agarwal, Aron
Externí odkaz:
http://arxiv.org/abs/2403.12303
Autor:
Egan, Susan Chan
Publikováno v:
China Review International, 2019 Jan 01. 26(3), 221-224.
Externí odkaz:
https://www.jstor.org/stable/27098359
