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Titlebook: Neural Information Processing; 28th International C Teddy Mantoro,Minho Lee,Achmad Nizar Hidayanto Conference proceedings 2021 Springer Nat

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樓主: broach
21#
發(fā)表于 2025-3-25 07:02:15 | 只看該作者
Honggang Wang,Xing Wu,Jingsheng Liu,Jiangnan Li and physical processes. The starting point of the text is the process - and not soil classification. Effects of weathering and new formation of minerals, mobilisation, transport, and breakdown or immobilisation of dissolved and suspended compounds are discussed. Soil processes and profiles are disc
22#
發(fā)表于 2025-3-25 08:30:03 | 只看該作者
23#
發(fā)表于 2025-3-25 13:00:11 | 只看該作者
24#
發(fā)表于 2025-3-25 17:08:41 | 只看該作者
25#
發(fā)表于 2025-3-25 21:50:43 | 只看該作者
Emoji-Based Co-Attention Network for?Microblog Sentiment Analysis as important features of emotions towards the recipient or subject for sentiment analysis. However, existing methods mainly take emojis as heuristic information that fails to resolve the problem of ambiguity noise. Recent researches have utilized emojis as an independent input to classify text sent
26#
發(fā)表于 2025-3-26 03:57:27 | 只看該作者
What Will You Tell Me About the?Chart? – Automated Description of?Chartsision problems. Furthermore, charts have a different specificity to natural-scene pictures, so commonly used methods do not perform well. To tackle these problems, we propose a process consisting of three sub-tasks: (1) chart classification, (2) detection of a chart’s essential elements, and (3) gen
27#
發(fā)表于 2025-3-26 07:54:04 | 只看該作者
Multi-Domain Adversarial Balancing for?the?Estimation of?Individual Treatment Effectdata from observational studies has selection bias: the treatment assigned to an individual related to that individual’s properties. In this paper, we proposed multi-domain adversarial balancing (MDAB), a method incorporates multi-domain adversarial learning with context-aware sample balancing to re
28#
發(fā)表于 2025-3-26 09:01:23 | 只看該作者
Exploring Self-training for?Imbalanced Node Classificationnarios. When trained on an imbalanced dataset, the performance of GNNs is distant from satisfactory for nodes of minority classes. Due to the small population, these minority nodes have less engagement in the objective function of training and the message-passing mechanism behind GNNs exacerbates th
29#
發(fā)表于 2025-3-26 14:43:34 | 只看該作者
Leveraging Multi-granularity Heterogeneous Graph for?Chinese Electronic Medical Records Summarizatioing. In particular, electronic medical record (EMR) summarization techniques can help doctors carry out diagnosis and treatment services more effectively, thus presenting substantial practical value. However, we point out there lacks investigation and dedicated designs for Chinese EMRs summarization
30#
發(fā)表于 2025-3-26 19:49:47 | 只看該作者
Multi-objective Clustering: A?Data-Driven Analysis of?MOCLE, MOCK and?,-MOCKsp clustering. More specifically, based on a collection of 12 datasets presenting different proprieties, we investigate the performance of MOCLE and MOCK compared to the recently proposed .-MOCK. Besides performing a quantitative analysis identifying which method presents a good/poor performance wit
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