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检索条件"机构=Data-Mining and Machine Learning"
67 条 记 录,以下是1-10 订阅
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CC-HIT: Creating Counterfactuals from High-Impact Transitions
CC-HIT: Creating Counterfactuals from High-Impact Transitio...
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International Workshops which were held in conjunction with the 6th International Conference on Process mining, ICPM 2024
作者: Xian, Zhicong Zellner, Ludwig Tavares, Gabriel Marques Seidl, Thomas Database Systems and Data Mining LMU Munich Munich Germany Munich Center for Machine Learning Munich Germany
Smooth process execution relies on high-quality insights extracted from event data. For instance, trace durations heavily affect performance and increase resource consumption. While many predictive systems aim to iden... 详细信息
来源: 评论
AlbNER: A Corpus for Named Entity Recognition in Albanian
arXiv
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arXiv 2023年
作者: Çano, Erion Digital Philology Data Mining Machine Learning University of Vienna Austria
Scarcity of resources such as annotated text corpora for under-resourced languages like Albanian is a serious impediment in computational linguistics and natural language processing research. This paper presents AlbNE... 详细信息
来源: 评论
AlbMoRe: A Corpus of Movie Reviews for Sentiment Analysis in Albanian
arXiv
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arXiv 2023年
作者: Çano, Erion Digital Philology Data Mining and Machine Learning University of Vienna Austria
Lack of available resources such as text corpora for low-resource languages seriously hinders research on natural language processing and computational linguistics. This paper presents AlbMoRe, a corpus of 800 sentime... 详细信息
来源: 评论
SHADE: Deep Density-based Clustering
arXiv
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arXiv 2024年
作者: Beer, Anna Weber, Pascal Miklautz, Lukas Leiber, Collin Durani, Walid Böhm, Christian Plant, Claudia Data Mining and Machine Learning University of Vienna Vienna Austria UniVie Doctoral School Computer Science Vienna Austria Database Systems and Data Mining LMU Munich Munich Germany Munich Center for Machine Learning Munich Germany UniVie Vienna Austria
Detecting arbitrarily shaped clusters in high-dimensional noisy data is challenging for current clustering methods. We introduce SHADE (Structure-preserving High-dimensional Analysis with Density-based Exploration), t... 详细信息
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SHADE: Deep Density-based Clustering  24
SHADE: Deep Density-based Clustering
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24th IEEE International Conference on data mining, ICDM 2024
作者: Beer, Anna Weber, Pascal Miklautz, Lukas Leiber, Collin Durani, Walid Bohm, Christian Plant, Claudia University of Vienna Faculty of Computer Science Vienna Austria UniVie Doctoral School Computer Science Vienna Austria LMU Munich Database Systems and Data Mining Munich Germany Munich Center for Machine Learning Munich Germany ds: UniVie University of Vienna Vienna Austria
Detecting arbitrarily shaped clusters in high-dimensional noisy data is challenging for current clustering methods. We introduce SHADE, the first deep clustering algorithm that incorporates density-connectivity into i... 详细信息
来源: 评论
AlbNews: A Corpus of Headlines for Topic Modeling in Albanian
arXiv
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arXiv 2024年
作者: Çano, Erion Lamaj, Dario Digital Philology Data Mining and Machine Learning University of Vienna Austria Cognitive Science Department of Applied Informatics Comenius University Bratislava Slovakia
The scarcity of available text corpora for low-resource languages like Albanian is a serious hurdle for research in natural language processing tasks. This paper introduces AlbNews, a collection of 600 topically label... 详细信息
来源: 评论
Batch Layer Normalization A new normalization layer for CNNs and RNNs  22
Batch Layer Normalization A new normalization layer for CNNs...
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Proceedings of the 6th International Conference on Advances in Artificial Intelligence
作者: Amir Ziaee Erion ÇAno Design Computing Group TU Wien Austria Research Group Data Mining and Machine Learning University of Vienna Austria
This study introduces a new normalization layer termed Batch Layer Normalization (BLN) to reduce the problem of internal covariate shift in deep neural network layers. As a combined version of batch and layer normaliz... 详细信息
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Motif Discovery Framework for Psychiatric EEG data Classification
arXiv
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arXiv 2025年
作者: Kraljevska, Melanija Hlavackova-Schindler, Katerina Miklautz, Lukas Plant, Claudia Research Group Data Mining and Machine Learning Faculty of Computer Science University of Vienna Währingerstrasse 29 Vienna1090 Austria ds:UniVie University of Vienna Austria
In current medical practice, patients undergoing depression treatment must wait four to six weeks before a clinician can assess medication response due to the delayed noticeable effects of antidepressants. Identificat... 详细信息
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Topic Segmentation of Research Article Collections
arXiv
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arXiv 2022年
作者: Çano, Erion Roth, Benjamin Digital Philology Research Group Data Mining and Machine Learning University of Vienna Austria
Collections of research article data harvested from the web have become common recently since they are important resources for experimenting on tasks such as named entity recognition, text summarization, or keyword ge... 详细信息
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Pattern Discovery in an EEG database of Depression Patients: Preliminary Results  14
Pattern Discovery in an EEG Database of Depression Patients:...
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14th International Conference on Measurement, MEASUREMENT 2023
作者: Hlavackova-Schindler, Katerina Pacher, Christina Plant, Claudia Lazarenko, Mykola Palus, Milan Hlinka, Jaroslav Kathpalia, Aditi Brunovsky, Martin University of Vienna Data Mining and Machine Learning Research Group Faculty of Computer Science Vienna Austria Czech Academy of Sciences Institute of Computer Science Department of Complex Systems Prague Czech Republic National Institute of Mental Health Clinical Research Programme Klecany Czech Republic
The ability to predict response to medication treatment of depressed patients, either early in the course of therapy or before treatment even begins can avoid trials of ineffective therapy and save patients from prolo... 详细信息
来源: 评论