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ORCID22nd DS 2019: Split, Croatia
- Petra Kralj Novak, Tomislav Smuc, Saso Dzeroski:
Discovery Science - 22nd International Conference, DS 2019, Split, Croatia, October 28-30, 2019, Proceedings. Lecture Notes in Computer Science 11828, Springer 2019, ISBN 978-3-030-33777-3
Advanced Machine Learning
- Colin Bellinger, Paula Branco, Luís Torgo
:
The CURE for Class Imbalance. 3-17 - Vincent Branders, Guillaume Derval, Pierre Schaus, Pierre Dupont:
Mining a Maximum Weighted Set of Disjoint Submatrices. 18-28 - André Correia, Carlos Soares, Alípio Jorge:
Dataset Morphing to Analyze the Performance of Collaborative Filtering. 29-39 - Takayasu Fushimi, Kiyoto Iwasaki, Seiya Okubo, Kazumi Saito:
Construction of Histogram with Variable Bin-Width Based on Change Point Detection. 40-50 - Nyoman Juniarta, Miguel Couceiro, Amedeo Napoli:
A Unified Approach to Biclustering Based on Formal Concept Analysis and Interval Pattern Structure. 51-60 - Sandy Moens, Boris Cule, Bart Goethals:
A Sampling-Based Approach for Discovering Subspace Clusters. 61-71 - Vu-Linh Nguyen, Sébastien Destercke, Eyke Hüllermeier:
Epistemic Uncertainty Sampling. 72-86 - Aljaz Osojnik, Pance Panov, Saso Dzeroski:
Utilizing Hierarchies in Tree-Based Online Structured Output Prediction. 87-95 - Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz:
On the Trade-Off Between Consistency and Coverage in Multi-label Rule Learning Heuristics. 96-111 - Abhinav Sharma, Jan N. van Rijn, Frank Hutter, Andreas Müller:
Hyperparameter Importance for Image Classification by Residual Neural Networks. 112-126
Applications
- Amin Azari, Panagiotis Papapetrou, Stojan Z. Denic, Gunnar Peters:
Cellular Traffic Prediction and Classification: A Comparative Evaluation of LSTM and ARIMA. 129-144 - Andreia Conceição, João Gama:
Main Factors Driving the Open Rate of Email Marketing Campaigns. 145-154 - Erik Dovgan, Bojan Leskosek, Gregor Jurak, Gregor Starc, Maroje Soric, Mitja Lustrek:
Enhancing BMI-Based Student Clustering by Considering Fitness as Key Attribute. 155-165 - Qianqian Gu, Ross King:
Deep Learning Does Not Generalize Well to Recognizing Cats and Dogs in Chinese Paintings. 166-175 - Vladimir Kuzmanovski, Mika Sulkava, Taru Palosuo, Jaakko Hollmén:
Temporal Analysis of Adverse Weather Conditions Affecting Wheat Production in Finland. 176-185 - Bozhidar Stevanoski, Dragi Kocev, Aljaz Osojnik, Ivica Dimitrovski, Saso Dzeroski:
Predicting Thermal Power Consumption of the Mars Express Satellite with Data Stream Mining. 186-201
Data and Knowledge Representation
- Elena Battaglia, Ruggero G. Pensa:
Parameter-Less Tensor Co-clustering. 205-219 - Dino Ienco, Ruggero G. Pensa:
Deep Triplet-Driven Semi-supervised Embedding Clustering. 220-234 - Ana Kostovska, Ilin Tolovski, Fatima S. Maikore, Larisa N. Soldatova, Pance Panov:
Neurodegenerative Disease Data Ontology. 235-245 - Pavlin G. Policar, Martin Strazar, Blaz Zupan:
Embedding to Reference t-SNE Space Addresses Batch Effects in Single-Cell Classification. 246-260 - Blaz Skrlj, Nada Lavrac, Jan Kralj:
Symbolic Graph Embedding Using Frequent Pattern Mining. 261-275
Feature Importance
- Mohsen Ahmadi Fahandar, Eyke Hüllermeier:
Feature Selection for Analogy-Based Learning to Rank. 279-289 - Matej Petkovic, Saso Dzeroski, Dragi Kocev:
Ensemble-Based Feature Ranking for Semi-supervised Classification. 290-305 - Cláudio Rebelo de Sá:
Variance-Based Feature Importance in Neural Networks. 306-315
Interpretable Machine Learning
- Fabrizio Angiulli, Fabio Fassetti, Luigi Palopoli, Cristina Serrao:
A Density Estimation Approach for Detecting and Explaining Exceptional Values in Categorical Data. 319-334 - Martin Atzmueller, Stefan Bloemheuvel, Benjamin Klöpper:
A Framework for Human-Centered Exploration of Complex Event Log Graphs. 335-350 - Anton Björklund, Andreas Henelius, Emilia Oikarinen, Kimmo Kallonen, Kai Puolamäki:
Sparse Robust Regression for Explaining Classifiers. 351-366 - Yannik Klein, Michael Rapp, Eneldo Loza Mencía:
Efficient Discovery of Expressive Multi-label Rules Using Relaxed Pruning. 367-382
Networks
- Sofia Fernandes, Hadi Fanaee-T, João Gama:
Evolving Social Networks Analysis via Tensor Decompositions: From Global Event Detection Towards Local Pattern Discovery and Specification. 385-395 - Angelo Impedovo, Michelangelo Ceci, Toon Calders:
Efficient and Accurate Non-exhaustive Pattern-Based Change Detection in Dynamic Networks. 396-411 - Domenico Mandaglio, Andrea Tagarelli:
A Combinatorial Multi-Armed Bandit Based Method for Dynamic Consensus Community Detection in Temporal Networks. 412-427 - Kazumi Saito, Kouzou Ohara, Masahiro Kimura, Hiroshi Motoda:
Resampling-Based Framework for Unbiased Estimator of Node Centrality over Large Complex Network. 428-442
Pattern Discovery
- Vítor Cerqueira, Luís Torgo, Carlos Soares:
Layered Learning for Early Anomaly Detection: Predicting Critical Health Episodes. 445-459 - Kemilly Dearo Garcia, Elaine Ribeiro de Faria, Cláudio Rebelo de Sá, João Mendes-Moreira, Charu C. Aggarwal, André C. P. L. F. de Carvalho, Joost N. Kok:
Ensemble Clustering for Novelty Detection in Data Streams. 460-470 - Hoang-Son Pham, Siegfried Nijssen, Kim Mens, Dario Di Nucci, Tim Molderez, Coen De Roover, Johan Fabry, Vadim Zaytsev:
Mining Patterns in Source Code Using Tree Mining Algorithms. 471-480 - Adriano Rivolli, Catarina Amaral, Luís Guardão, Cláudio Rebelo de Sá, Carlos Soares:
KnowBots: Discovering Relevant Patterns in Chatbot Dialogues. 481-492 - Natasa Sarafijanovic-Djukic, Jesse Davis:
Fast Distance-Based Anomaly Detection in Images Using an Inception-Like Autoencoder. 493-508
Time Series
- Samaneh Khoshrou, Mykola Pechenizkiy:
Adaptive Long-Term Ensemble Learning from Multiple High-Dimensional Time-Series. 511-521 - Sascha Krstanovic, Heiko Paulheim:
Fourier-Based Parametrization of Convolutional Neural Networks for Robust Time Series Forecasting. 522-532 - Julian Vexler, Stefan Kramer:
Integrating LSTMs with Online Density Estimation for the Probabilistic Forecast of Energy Consumption. 533-543
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