找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computational Data and Social Networks; 10th International C David Mohaisen,Ruoming Jin Conference proceedings 2021 Springer Nature Switzer

[復制鏈接]
41#
發(fā)表于 2025-3-28 15:02:56 | 只看該作者
Approximation Algorithm for Maximizing Nonnegative Weakly Monotonic Set Functionsions in practice do not fully meet the characteristics of diminishing returns. In this paper, we consider the problem of maximizing unconstrained non-negative weakly-monotone non-submodular set function. The generic submodularity ratio . is a bridge connecting the non-negative monotone functions and
42#
發(fā)表于 2025-3-28 21:02:36 | 只看該作者
43#
發(fā)表于 2025-3-29 02:35:22 | 只看該作者
Maximizing the Sum of a Supermodular Function and a Monotone DR-submodular Function Subject to a Kna of the sum of a supermodular function and a monotone DR-submodular function on the integer lattice. As our main contribution, we present a streaming algorithm under the assumption that the optimum is known, and a two-pass streaming algorithm in general case. The proposed algorithms are proved to ha
44#
發(fā)表于 2025-3-29 04:56:07 | 只看該作者
A Framework for Accelerating Graph Convolutional Networks on Massive Datasetsicularly among them, because of massive scale of graphs, there is not only a large computation time, but also the need for partitioning and loading data multiple times. This paper presents a different framework in which existing GCN methods can be accelerated for execution on large graphs. Building
45#
發(fā)表于 2025-3-29 07:51:46 | 只看該作者
AdvEdge: Optimizing Adversarial Perturbations Against Interpretable Deep Learningion for a given task is derived from the correct problem representation and not from the misuse of artifacts in the data. Hence, interpretation models have become a key ingredient in developing deep learning models. Utilizing interpretation models enables a better understanding of how DNN models wor
46#
發(fā)表于 2025-3-29 12:10:34 | 只看該作者
47#
發(fā)表于 2025-3-29 18:18:04 | 只看該作者
48#
發(fā)表于 2025-3-29 21:03:32 | 只看該作者
49#
發(fā)表于 2025-3-30 02:54:39 | 只看該作者
50#
發(fā)表于 2025-3-30 05:14:21 | 只看該作者
MIC Model for Cervical Cancer Risk Factors Deep Association Analysisrs for CC including the direct risk factors and indirect risk factors that may be caused by other diseases or reasons. In this paper, we proposed a MIC (Multiple Indicators Correlation) model to resolve the problem of analyzing risk factors by establishing the indicators structure. Based on the clos
 關于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-18 10:35
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
沛县| 邛崃市| 金山区| 时尚| 亳州市| 黄平县| 洪泽县| 时尚| 民县| 军事| 砀山县| 宣恩县| 科尔| 绍兴县| 涿鹿县| 高州市| 隆子县| 博湖县| 乌鲁木齐县| 兴山县| 休宁县| 吉林省| 石河子市| 全州县| 简阳市| 怀仁县| 衡东县| 玛多县| 出国| 浦东新区| 微山县| 盘锦市| 长沙县| 拉萨市| 社会| 祁阳县| 张掖市| 怀化市| 温州市| 河曲县| 永顺县|