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ORCIDPKDD/ECML 2021: Bilbao, Spain (Virtual Event) - Workshops
- Michael Kamp
, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee A. D. Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4
Machine Learning for CyberSecurity
- Malik Al-Essa, Annalisa Appice:
Dealing with Imbalanced Data in Multi-class Network Intrusion Detection Systems Using XGBoost. 5-21 - Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie:
Adversarial Robustness of Probabilistic Network Embedding for Link Prediction. 22-38 - Thomas Bekman, Masoumeh Abolfathi, Jafar Haadi Jafarian, Ashis Kumer Biswas, Farnoush Banaei Kashani, Kuntal Das:
Practical Black Box Model Inversion Attacks Against Neural Nets. 39-54 - Lander Segurola-Gil, Francesco Zola, Xabier Echeberria-Barrio, Raul Orduna Urrutia:
NBcoded: Network Attack Classifiers Based on Encoder and Naive Bayes Model for Resource Limited Devices. 55-70
Workshop on Machine Learning in Software Engineering
- Md. Mostafizer Rahman, Yutaka Watanobe, Rage Uday Kiran, Raihan Kabir:
A Stacked Bidirectional LSTM Model for Classifying Source Codes Built in MPLs. 75-89 - M. Saqib Nawaz, Philippe Fournier-Viger, Muhammad Zohaib Nawaz, Guoting Chen, Youxi Wu:
Metamorphic Malware Behavior Analysis Using Sequential Pattern Mining. 90-103 - André Sousa, João Pascoal Faria, João Mendes-Moreira, Duarte Gomes, Pedro Castro Henriques, Ricardo Graça:
Applying Machine Learning to Risk Assessment in Software Projects. 104-118 - Hossein Hajipour, Apratim Bhattacharyya, Cristian-Alexandru Staicu, Mario Fritz:
SampleFix: Learning to Generate Functionally Diverse Fixes. 119-133 - Janneke Morin, Krishnendu Ghosh:
Linguistic Analysis of Stack Overflow Data: Native English vs Non-native English Speakers. 134-142 - Hossein Hajipour, Mateusz Malinowski, Mario Fritz:
IReEn: Reverse-Engineering of Black-Box Functions via Iterative Neural Program Synthesis. 143-157 - Philippe Fournier-Viger, M. Saqib Nawaz, Wei Song, Wensheng Gan:
Machine Learning for Intelligent Industrial Design. 158-172
MIning DAta for financial applicationS
- Luca Barbaglia, Sergio Consoli, Susan Wang:
Financial Forecasting with Word Embeddings Extracted from News: A Preliminary Analysis. 179-188 - Sergio Consoli, Matteo Negri, Amirhossein Tebbifakhr, Elisa Tosetti, Marco Turchi:
On Neural Forecasting and News Emotions: The Case of the Spanish Stock Market. 189-194 - Eric Benhamou, David Saltiel, Serge Tabachnik, Corentin Bourdeix, François Chareyron, Beatrice Guez:
Adaptive Supervised Learning for Financial Markets Volatility Targeting Models. 195-209 - Hamish Hall, Pedro Baiz, Philip Nadler:
Efficient Analysis of Transactional Data Using Graph Convolutional Networks. 210-225 - Luigi Bellomarini, Livia Blasi, Rosario Laurendi, Emanuel Sallinger:
A Reasoning Approach to Financial Data Exchange with Statistical Confidentiality. 226-231 - Jorge Miguel Bravo:
Forecasting Longevity for Financial Applications: A First Experiment with Deep Learning Methods. 232-249
Sixth Workshop on Data Science for Social Good (SoGood 2021)
- Alexandra Sasha Luccioni, Katherine Hoffmann Pham, Cynthia Sin Nga Lam, Joseph Aylett-Bullock, Miguel A. Luengo-Oroz:
Ensuring the Inclusive Use of NLP in the Global Response to COVID-19. 259-266 - Miguel José Monteiro, Paulo Maia:
A Framework for Building pro-bono Data for Good Projects. 267-282 - Sónia Teixeira, Guilherme Londres, Bruno Veloso, Rita P. Ribeiro, João Gama:
Improving Smart Waste Collection Using AutoML. 283-298 - Paulo Maia, Joana Morgado, Tiago Gonçalves, Tomé Albuquerque:
Applying Machine Learning for Traffic Forecasting in Porto, Portugal. 299-308 - Deepak Uniyal, Amit Agarwal:
IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages. 309-324 - Adrien Ehrhardt, Minh Tuan Nguyen:
Automated ESG Report Analysis by Joint Entity and Relation Extraction. 325-340 - Hadi Mansourifar, Dana Alsagheer, Reza Fathi, Weidong Shi, Lan Ni, Yan Huang:
Hate Speech Detection in Clubhouse. 341-351 - Emma Beauxis-Aussalet:
Error Variance, Fairness, and the Curse on Minorities. 352-365
Machine Learning for Pharma and Healthcare Applications
- Pavithra Rajendran, Alexandros Zenonos, Joshua Spear, Rebecca Pope:
Embed Wisely: An Ensemble Approach to Predict ICD Coding. 371-389 - Fayyaz A. Minhas, Michael S. Toss, Noor ul Wahab, Emad Rakha, Nasir M. Rajpoot:
L1-Regularized Neural Ranking for Risk Stratification and Its Application to Prediction of Time to Distant Metastasis in Luminal Node Negative Chemotherapy Naïve Breast Cancer Patients. 390-400 - Nuria García-Santa, Kendrick Cetina:
Extracting Multilingual Relations with Joint Learning of Language Models. 401-407 - Aidan Cooper, Orla M. Doyle, Alison Bourke:
Supervised Clustering for Subgroup Discovery: An Application to COVID-19 Symptomatology. 408-422 - Tommaso Di Noto, Chirine Atat, Eduardo Gamito Teiga, Monika Hegi, Andreas Hottinger, Meritxell Bach Cuadra, Patric Hagmann, Jonas Richiardi:
Diagnostic Surveillance of High-Grade Gliomas: Towards Automated Change Detection Using Radiology Report Classification. 423-436 - Muhammad Dawood, Kim Branson, Nasir M. Rajpoot, Fayyaz ul Amir Afsar Minhas:
All You Need is Color: Image Based Spatial Gene Expression Prediction Using Neural Stain Learning. 437-450 - Klest Dedja, Felipe Kenji Nakano, Konstantinos Pliakos, Celine Vens:
Explaining a Random Survival Forest by Extracting Prototype Rules. 451-458 - Shirin Tavara, Alexander Schliep, Debabrota Basu:
Federated Learning of Oligonucleotide Drug Molecule Thermodynamics with Differentially Private ADMM-Based SVM. 459-467 - Keyuan Jiang, Dingkai Zhang, Gordon R. Bernard:
Mining Medication-Effect Relations from Twitter Data Using Pre-trained Transformer Language Model. 468-478 - Xiong Liu, Cheng Shi, Uday Deore, Yingbo Wang, Myah Tran, Iya Khalil, Murthy V. Devarakonda:
A Scalable AI Approach for Clinical Trial Cohort Optimization. 479-489 - Pallika Kanani, Virendra J. Marathe, Daniel W. Peterson, Rave Harpaz, Steve Bright:
Private Cross-Silo Federated Learning for Extracting Vaccine Adverse Event Mentions. 490-505
Machine Learning for Buildings Energy Management
- Zygimantas Jasiunas, Pedro M. Ferreira, José Cecílio:
Building Appliances Energy Performance Assessment. 511-524 - Jean-Louis Debezia, Mélodie Boillet, Christopher Kermorvant, Quentin Barral:
Drilling a Large Corpus of Document Images of Geological Information Extraction. 525-530 - Sushodhan Vaishampayan, Aditi Pawde, Akshada Shinde, Manoj Apte, Girish Keshav Palshikar:
Data Envelopment Analysis for Energy Audits of Housing Properties. 531-545 - Christian Nnaemeka Egwim, Oluwapelumi Oluwaseun Egunjobi, Álvaro Gomes, Hafiz Alaka:
A Comparative Study on Machine Learning Algorithms for Assessing Energy Efficiency of Buildings. 546-566 - Frederico Apolónia, Pedro M. Ferreira, José Cecílio:
Buildings Occupancy Estimation: Preliminary Results Using Bluetooth Signals and Artificial Neural Networks. 567-579
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