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: Machine Learning and Knowledge Discovery in Databases; European Conference, Ulf Brefeld,Elisa Fromont,Céline Robardet Conference proceeding

[復(fù)制鏈接]
樓主: Sinuate
41#
發(fā)表于 2025-3-28 15:40:37 | 只看該作者
Distributed Learning of Non-convex Linear Models with One Round of Communication data, and so has negligible computational cost. Compared with similar distributed estimators that merge locally trained models, OWA either has stronger statistical guarantees, is applicable to more models, or has a more computationally efficient merging procedure.
42#
發(fā)表于 2025-3-28 22:07:57 | 只看該作者
43#
發(fā)表于 2025-3-29 01:22:43 | 只看該作者
Shift Happens: Adjusting Classifiers exact class distribution is known. We also demonstrate experimentally that, when in practice the class distribution is known only approximately, there is often still a reduction in loss depending on the amount of shift and the precision to which the class distribution is known.
44#
發(fā)表于 2025-3-29 06:08:52 | 只看該作者
45#
發(fā)表于 2025-3-29 07:28:10 | 只看該作者
Conference proceedings 2020overy in Databases, ECML PKDD 2019, held in Würzburg, Germany, in September 2019..The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track. ..The contributions were organized in topical sections named a
46#
發(fā)表于 2025-3-29 14:11:10 | 只看該作者
47#
發(fā)表于 2025-3-29 16:29:25 | 只看該作者
48#
發(fā)表于 2025-3-29 21:01:18 | 只看該作者
SLSGD: Secure and Efficient Distributed On-device Machine Learningrithm with efficient communication and attack tolerance. The proposed algorithm has provable convergence and robustness under non-IID settings. Empirical results show that the proposed algorithm stabilizes the convergence and tolerates data poisoning on a small number of workers.
49#
發(fā)表于 2025-3-30 02:11:36 | 只看該作者
978-3-030-46146-1Springer Nature Switzerland AG 2020
50#
發(fā)表于 2025-3-30 07:21:58 | 只看該作者
Machine Learning and Knowledge Discovery in Databases978-3-030-46147-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
 關(guān)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(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 21:47
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
汕头市| 封丘县| 曲周县| 泉州市| 开远市| 沂水县| 正宁县| 满洲里市| 固原市| 韶关市| 玛多县| 辽阳市| 长岭县| 邻水| 奉节县| 区。| 新邵县| 黄平县| 鲁甸县| 昂仁县| 新绛县| 铜川市| 大渡口区| 肇源县| 常德市| 阜宁县| 宝兴县| 喀喇| 济宁市| 武胜县| 怀集县| 二连浩特市| 广丰县| 锡林浩特市| 宁强县| 钟山县| 垫江县| 本溪| 中江县| 辽宁省| 玉溪市|