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ORCID24th DS 2021: Halifax, NS, Canada
- Carlos Soares
, Luís Torgo:
Discovery Science - 24th International Conference, DS 2021, Halifax, NS, Canada, October 11-13, 2021, Proceedings. Lecture Notes in Computer Science 12986, Springer 2021, ISBN 978-3-030-88941-8
Applications
- Jimmy Ljungman, Vanessa Lislevand, John Pavlopoulos, Alexandra Farazouli, Zed Lee, Panagiotis Papapetrou, Uno Fors:
Automated Grading of Exam Responses: An Extensive Classification Benchmark. 3-18 - Chitsutha Soomlek, Jan N. van Rijn, Marcello M. Bonsangue:
Automatic Human-Like Detection of Code Smells. 19-28 - Kazuki Kawamura, Akihiro Yamamoto:
HTML-LSTM: Information Extraction from HTML Tables in Web Pages Using Tree-Structured LSTM. 29-43 - Théo Verhelst, Jeevan Shrestha, Denis Mercier, Jean-Christophe Dewitte, Gianluca Bontempi:
Predicting Reach to Find Persuadable Customers: Improving Uplift Models for Churn Prevention. 44-54
Classification
- Yueyang Liu, Zois Boukouvalas, Nathalie Japkowicz:
A Semi-supervised Framework for Misinformation Detection. 57-66 - Jean-Gabriel Gaudreault, Paula Branco, João Gama:
An Analysis of Performance Metrics for Imbalanced Classification. 67-77 - Florian Busch, Moritz Kulessa, Eneldo Loza Mencía, Hendrik Blockeel:
Combining Predictions Under Uncertainty: The Case of Random Decision Trees. 78-93 - Christie Courtnage, Evgueni N. Smirnov:
Shapley-Value Data Valuation for Semi-supervised Learning. 94-108
Data Streams
- Giuseppina Andresini, Annalisa Appice, Corrado Loglisci, Vincenzo Belvedere, Domenico Redavid, Donato Malerba:
A Network Intrusion Detection System for Concept Drifting Network Traffic Data. 111-121 - Maroua Bahri, Albert Bifet:
Incremental k-Nearest Neighbors Using Reservoir Sampling for Data Streams. 122-137 - Georg Krempl, Daniel Kottke, Tuan Pham:
Statistical Analysis of Pairwise Connectivity. 138-148
Graph and Network Mining
- Haoxi Zhan, Xiaobing Pei:
FHA: Fast Heuristic Attack Against Graph Convolutional Networks. 151-165 - Clemens Damke, Eyke Hüllermeier:
Ranking Structured Objects with Graph Neural Networks. 166-180
Machine Learning for COVID-19
- Aleksandar Novakovic, Adele H. Marshall, Carolyn McGregor:
Knowledge Discovery of the Delays Experienced in Reporting COVID-19 Confirmed Positive Cases Using Time to Event Models. 183-193 - Tarek Elsaka, Imad Afyouni, Ibrahim Abaker Targio Hashem, Zaher Al Aghbari:
Multi-scale Sentiment Analysis of Location-Enriched COVID-19 Arabic Social Data. 194-203 - Blaz Skrlj, Marko Jukic, Nika Erzen, Senja Pollak, Nada Lavrac:
Prioritization of COVID-19-Related Literature via Unsupervised Keyphrase Extraction and Document Representation Learning. 204-217 - Ioanna Miliou, John Pavlopoulos, Panagiotis Papapetrou:
Sentiment Nowcasting During the COVID-19 Pandemic. 218-228
Neural Networks and Deep Learning
- Jinghui Lu, Maeve Henchion, Ivan Bacher, Brian Mac Namee:
A Sentence-Level Hierarchical BERT Model for Document Classification with Limited Labelled Data. 231-241 - Colin Bellinger, Roberto Corizzo, Nathalie Japkowicz:
Calibrated Resampling for Imbalanced and Long-Tails in Deep Learning. 242-252 - Haimonti Dutta, Saurabh Amarnath Mahindre, Nitin Nataraj:
Consensus Based Vertically Partitioned Multi-layer Perceptrons for Edge Computing. 253-267 - Aman Jaiswal, Harpreet Singh Sodhi, Mohamed Muzamil H, Rajveen Singh Chandhok, Sageev Oore, Chandramouli Shama Sastry:
Controlling BigGAN Image Generation with a Segmentation Network. 268-281 - João Coutinho-Almeida, Pedro Pereira Rodrigues, Ricardo João Cruz Correia:
GANs for Tabular Healthcare Data Generation: A Review on Utility and Privacy. 282-291
Preferences and Recommender Systems
- Alireza Gharahighehi, Celine Vens, Konstantinos Pliakos:
An Ensemble Hypergraph Learning Framework for Recommendation. 295-304 - Mehrnaz Amjadi, Seyed Danial Mohseni Taheri, Theja Tulabandhula:
KATRec: Knowledge Aware aTtentive Sequential Recommendations. 305-320
Representation Learning and Feature Selection
- Aïssatou Diallo, Johannes Fürnkranz:
Elliptical Ordinal Embedding. 323-333 - Urh Primozic, Blaz Skrlj, Saso Dzeroski, Matej Petkovic:
Unsupervised Feature Ranking via Attribute Networks. 334-343
Responsible Artificial Intelligence
- Valerio Bonsignori, Riccardo Guidotti, Anna Monreale:
Deriving a Single Interpretable Model by Merging Tree-Based Classifiers. 347-357 - Riccardo Guidotti, Salvatore Ruggieri:
Ensemble of Counterfactual Explainers. 358-368 - Zhendong Wang, Isak Samsten, Rami Mochaourab, Panagiotis Papapetrou:
Learning Time Series Counterfactuals via Latent Space Representations. 369-384 - Francesco Paolo Caforio, Giuseppina Andresini, Gennaro Vessio, Annalisa Appice, Donato Malerba:
Leveraging Grad-CAM to Improve the Accuracy of Network Intrusion Detection Systems. 385-400 - Fabrizio Angiulli, Fabio Fassetti, Simona Nisticò:
Local Interpretable Classifier Explanations with Self-generated Semantic Features. 401-410 - Giacomo Mariani, Anna Monreale, Francesca Naretto:
Privacy Risk Assessment of Individual Psychometric Profiles. 411-421 - Caitlin Moroney, Evan Crothers, Sudip Mittal, Anupam Joshi, Tülay Adali, Christine Mallinson, Nathalie Japkowicz, Zois Boukouvalas:
The Case for Latent Variable Vs Deep Learning Methods in Misinformation Detection: An Application to COVID-19. 422-432
Spatial, Temporal and Spatiotemporal Data
- Dan Hudson, Travis J. Wiltshire, Martin Atzmueller:
Local Exceptionality Detection in Time Series Using Subgroup Discovery: An Approach Exemplified on Team Interaction Data. 435-445 - Bart Bussmann, Jannes Nys, Steven Latré:
Neural Additive Vector Autoregression Models for Causal Discovery in Time Series. 446-460 - Roberto Corizzo, Michelangelo Ceci, Gianvito Pio, Paolo Mignone, Nathalie Japkowicz:
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data. 461-471
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