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ORCID21st PKDD / 28th ECML 2017: Skopje, Macedonia
- Michelangelo Ceci, Jaakko Hollmén, Ljupco Todorovski, Celine Vens, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part II. Lecture Notes in Computer Science 10535, Springer 2017, ISBN 978-3-319-71245-1
Pattern and Sequence Mining
- Bryan Hooi, Shenghua Liu, Asim Smailagic, Christos Faloutsos:
BeatLex: Summarizing and Forecasting Time Series with Patterns. 3-19 - Johannes De Smedt
, Galina Deeva, Jochen De Weerdt:
Behavioral Constraint Template-Based Sequence Classification. 20-36 - Severin Gsponer, Barry Smyth, Georgiana Ifrim:
Efficient Sequence Regression by Learning Linear Models in All-Subsequence Space. 37-52 - Florian Adriaens, Jefrey Lijffijt, Tijl De Bie:
Subjectively Interesting Connecting Trees. 53-69
Privacy and Security
- Paul Prasse, Lukás Machlica, Tomás Pevný, Jirí Havelka, Tobias Scheffer:
Malware Detection by Analysing Encrypted Network Traffic with Neural Networks. 73-88 - Yi Li, Yitao Duan, Wei Xu:
PEM: A Practical Differentially Private System for Large-Scale Cross-Institutional Data Mining. 89-105
Probabilistic Models and Methods
- Edwin Simpson, Steven Reece, Stephen J. Roberts:
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources. 109-125 - Nikolaos Tziortziotis, Christos Dimitrakakis:
Bayesian Inference for Least Squares Temporal Difference Regularization. 126-141 - Fattaneh Jabbari, Joseph D. Ramsey, Peter Spirtes, Gregory F. Cooper:
Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints. 142-157 - Etienne Auclair, Nathalie Peyrard, Régis Sabbadin:
Labeled DBN Learning with Community Structure Knowledge. 158-174 - Mickaël Chen, Ludovic Denoyer:
Multi-view Generative Adversarial Networks. 175-188 - Sophie Burkhardt, Stefan Kramer:
Online Sparse Collapsed Hybrid Variational-Gibbs Algorithm for Hierarchical Dirichlet Process Topic Models. 189-204 - Anil Goyal, Emilie Morvant, Pascal Germain, Massih-Reza Amini:
PAC-Bayesian Analysis for a Two-Step Hierarchical Multiview Learning Approach. 205-221 - Michael Ciere, Carlos Gañán, Michel van Eeten:
Partial Device Fingerprints. 222-237 - Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima:
Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies. 238-250
Recommendation
- Dimitrios Rafailidis, Fabio Crestani:
A Regularization Method with Inference of Trust and Distrust in Recommender Systems. 253-268 - Maryam Tavakol, Ulf Brefeld:
A Unified Contextual Bandit Framework for Long- and Short-Term Recommendations. 269-284 - Shoujin Wang, Liang Hu, Longbing Cao:
Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation. 285-302
Regression
- Martin Pavlovski, Fang Zhou, Ivan Stojkovic, Ljupco Kocarev, Zoran Obradovic:
Adaptive Skip-Train Structured Regression for Temporal Networks. 305-321 - Krisztián Búza, Ladislav Peska:
ALADIN: A New Approach for Drug-Target Interaction Prediction. 322-337 - Katrin Ullrich, Michael Kamp, Thomas Gärtner, Martin Vogt, Stefan Wrobel:
Co-Regularised Support Vector Regression. 338-354 - Edward Moroshko, Koby Crammer:
Online Regression with Controlled Label Noise Rate. 355-369
Reinforcement Learning
- Masahiro Kohjima, Tatsushi Matsubayashi, Hiroshi Sawada:
Generalized Inverse Reinforcement Learning with Linearly Solvable MDP. 373-388 - Mastane Achab, Stéphan Clémençon, Aurélien Garivier, Anne Sabourin, Claire Vernade:
Max K-Armed Bandit: On the ExtremeHunter Algorithm and Beyond. 389-404 - Sylvain Lamprier, Thibault Gisselbrecht, Patrick Gallinari:
Variational Thompson Sampling for Relational Recurrent Bandits. 405-421
Subgroup Discovery
- Antti Ukkonen, Vladimir Dzyuba, Matthijs van Leeuwen:
Explaining Deviating Subsets Through Explanation Networks. 425-441 - Adnene Belfodil, Sylvie Cazalens, Philippe Lamarre, Marc Plantevit:
Flash Points: Discovering Exceptional Pairwise Behaviors in Vote or Rating Data. 442-458
Time Series and Streams
- Frank Höppner, Tobias Sobek:
A Multiscale Bezier-Representation for Time Series that Supports Elastic Matching. 461-477 - Vítor Cerqueira, Luís Torgo, Fábio Pinto, Carlos Soares:
Arbitrated Ensemble for Time Series Forecasting. 478-494 - Shoumik Roychoudhury, Mohamed F. Ghalwash, Zoran Obradovic:
Cost Sensitive Time-Series Classification. 495-511 - Bartosz Krawczyk, Przemyslaw Skryjomski:
Cost-Sensitive Perceptron Decision Trees for Imbalanced Drifting Data Streams. 512-527 - Romain Tavenard, Simon Malinowski, Laetitia Chapel, Adeline Bailly, Heider Sanchez, Benjamin Bustos:
Efficient Temporal Kernels Between Feature Sets for Time Series Classification. 528-543 - Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet:
Forecasting and Granger Modelling with Non-linear Dynamical Dependencies. 544-558 - Ammar Shaker, Waleri Heldt, Eyke Hüllermeier:
Learning TSK Fuzzy Rules from Data Streams. 559-574 - Balázs Szörényi, Snir Cohen, Shie Mannor:
Non-parametric Online AUC Maximization. 575-590 - Izaskun Oregi, Aritz Pérez, Javier Del Ser, José Antonio Lozano:
On-Line Dynamic Time Warping for Streaming Time Series. 591-605 - Hyun Ah Song, Bryan Hooi, Marko Jereminov, Amritanshu Pandey, Larry T. Pileggi, Christos Faloutsos:
PowerCast: Mining and Forecasting Power Grid Sequences. 606-621 - Xian Wu, Yuxiao Dong, Chao Huang, Jian Xu, Dong Wang, Nitesh V. Chawla:
UAPD: Predicting Urban Anomalies from Spatial-Temporal Data. 622-638
Transfer and Multi-task Learning
- Yizhou Zang, Xiaohua Hu:
LKT-FM: A Novel Rating Pattern Transfer Model for Improving Non-overlapping Cross-Domain Collaborative Filtering. 641-656 - Jiyi Li, Tomohiro Arai, Yukino Baba, Hisashi Kashima, Shotaro Miwa:
Distributed Multi-task Learning for Sensor Network. 657-672 - Meghana Kshirsagar, Eunho Yang, Aurélie C. Lozano:
Learning Task Clusters via Sparsity Grouped Multitask Learning. 673-689 - Christopher Clingerman, Eric Eaton:
Lifelong Learning with Gaussian Processes. 690-704 - Hanh T. H. Nguyen, Martin Wistuba, Lars Schmidt-Thieme:
Personalized Tag Recommendation for Images Using Deep Transfer Learning. 705-720 - Ivan Stojkovic, Mohamed F. Ghalwash, Zoran Obradovic:
Ranking Based Multitask Learning of Scoring Functions. 721-736 - Ievgen Redko, Amaury Habrard, Marc Sebban:
Theoretical Analysis of Domain Adaptation with Optimal Transport. 737-753 - Xia Cui, Frans Coenen, Danushka Bollegala:
TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation. 754-771
Unsupervised and Semisupervised Learning
- Eirikur Agustsson, Radu Timofte, Luc Van Gool:
k^2 k 2 -means for Fast and Accurate Large Scale Clustering. 775-791 - Vinay Kumar Verma, Piyush Rai:
A Simple Exponential Family Framework for Zero-Shot Learning. 792-808 - Kai Tian, Shuigeng Zhou, Jihong Guan:
DeepCluster: A General Clustering Framework Based on Deep Learning. 809-825 - Xiao He, Limin Li, Damian Roqueiro, Karsten M. Borgwardt:
Multi-view Spectral Clustering on Conflicting Views. 826-842 - Caitlin Kuhlman, Yizhou Yan, Lei Cao, Elke A. Rundensteiner:
Pivot-Based Distributed K-Nearest Neighbor Mining. 843-860
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