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. Research Track; European Conference, Albert Bifet,Jesse Davis,Indr? ?liobait? Confer

[復(fù)制鏈接]
樓主: STRI
21#
發(fā)表于 2025-3-25 03:25:56 | 只看該作者
22#
發(fā)表于 2025-3-25 07:54:07 | 只看該作者
23#
發(fā)表于 2025-3-25 11:51:15 | 只看該作者
Dynamics Adaptive Safe Reinforcement Learning with?a?Misspecified Simulatortraditional methods. Subsequently, DASaR aligns the estimated value functions in the simulator and the real-world environment via inverse dynamics-based relabeling of reward and cost signals. Furthermore, to deal with the underestimation of cost value functions, DASaR employs uncertainty estimation
24#
發(fā)表于 2025-3-25 19:07:01 | 只看該作者
25#
發(fā)表于 2025-3-25 23:38:55 | 只看該作者
26#
發(fā)表于 2025-3-26 02:54:10 | 只看該作者
FairFlow: An Automated Approach to?Model-Based Counterfactual Data Augmentation for NLP paper proposes FairFlow, an automated approach to generating parallel data for training counterfactual text generator models that limits the need for human intervention. Furthermore, we show that FairFlow significantly overcomes the limitations of dictionary-based word-substitution approaches whils
27#
發(fā)表于 2025-3-26 05:56:13 | 只看該作者
28#
發(fā)表于 2025-3-26 12:16:29 | 只看該作者
MEGA: Multi-encoder GNN Architecture for?Stronger Task Collaboration and?Generalizationng of each task. This architecture allows for independent learning from multiple pretext tasks, followed by a simple self-supervised dimensionality reduction technique to combine the insights gleaned. Through extensive experiments, we demonstrate the superiority of our approach, showcasing an averag
29#
發(fā)表于 2025-3-26 15:01:41 | 只看該作者
MetaQuRe: Meta-learning from?Model Quality and?Resource Consumptionurce consumption of models evaluated across hundreds of data sets and four execution environments. We use this data to put our methodology into practice and conduct an in-depth analysis of how our approach and data set can help in making AutoML more resource-aware, which represents our third contrib
30#
發(fā)表于 2025-3-26 20:03:39 | 只看該作者
Propagation Structure-Semantic Transfer Learning for?Robust Fake News Detectiontion under a teacher-student architecture. Specifically, we design dual teacher models to learn semantics knowledge and structure knowledge from noisy news content and propagation structure independently. Besides, we design a Multi-channel Knowledge Distillation (MKD) loss to enable the student mode
 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 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) 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, 2025-10-6 05:14
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
新密市| 蕉岭县| 濉溪县| 满城县| 金山区| 城固县| 克山县| 嫩江县| 周口市| 延津县| 井冈山市| 新蔡县| 庆云县| 德清县| 北宁市| 太原市| 南华县| 利川市| 胶南市| 行唐县| 威远县| 徐汇区| 虞城县| 灵丘县| 中阳县| 错那县| 凌源市| 唐河县| 吉首市| 教育| 南漳县| 东兰县| 延庆县| 买车| 南宫市| 潞城市| 阳曲县| 洛浦县| 庐江县| 贵溪市| 东平县|