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PKDD / ECML 2020: Ghent, Belgium
- Frank Hutter
, Kristian Kersting
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Ghent, Belgium, September 14-18, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12457, Springer 2021, ISBN 978-3-030-67657-5
Pattern Mining
- Florian Seiffarth
Maximum Margin Separations in Finite Closure Systems. 3-18 - Hugo Manuel Proença
Discovering Outstanding Subgroup Lists for Numeric Targets Using MDL. 19-35 - Arnold Hien
A Relaxation-Based Approach for Mining Diverse Closed Patterns. 36-54 - Amila Silva
OMBA: User-Guided Product Representations for Online Market Basket Analysis. 55-71
Clustering
- Longqi Yang, Liangliang Zhang, Yuhua Tang:
Online Binary Incomplete Multi-view Clustering. 75-90 - Benjamin Schelling, Lena Greta Marie Bauer, Sahar Behzadi, Claudia Plant:
Utilizing Structure-Rich Features to Improve Clustering. 91-107 - Lele Cao
Simple, Scalable, and Stable Variational Deep Clustering. 108-124 - Richard Leibrandt, Stephan Günnemann:
Gauss Shift: Density Attractor Clustering Faster Than Mean Shift. 125-142
Privacy and Fairness
- Adi Akavia
Privacy-Preserving Decision Trees Training and Prediction. 145-161 - David Solans
Poisoning Attacks on Algorithmic Fairness. 162-177
(Social) Network Analysis and Computational Social Science
- Wenjie Feng
SpecGreedy: Unified Dense Subgraph Detection. 181-197 - Guilherme R. Borges, Flavio V. D. de Figueiredo, Renato M. Assunção, Pedro O. S. Vaz de Melo:
Networked Point Process Models Under the Lens of Scrutiny. 198-215 - Li Ma, Mingding Liao, Xiaofeng Gao, Guoze Zhang, Qiang Yan, Guihai Chen
FB2vec: A Novel Representation Learning Model for Forwarding Behaviors on Online Social Networks. 216-231 - Lei Qi, Mohammed Khaleel, Wallapak Tavanapong, Adisak Sukul, David A. M. Peterson:
A Framework for Deep Quantification Learning. 232-248 - Jason (Jiasheng) Zhang, Dongwon Lee:
PROMO for Interpretable Personalized Social Emotion Mining. 249-265 - Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi:
Progressive Supervision for Node Classification. 266-281 - Hansheng Xue
Modeling Dynamic Heterogeneous Network for Link Prediction Using Hierarchical Attention with Temporal RNN. 282-298 - Yang Yang, Jian Shen, Yanru Qu, Yunfei Liu, Kerong Wang, Yaoming Zhu, Weinan Zhang, Yong Yu:
GIKT: A Graph-Based Interaction Model for Knowledge Tracing. 299-315
Dimensionality Reduction and Autoencoders
- Guillaume Salha, Romain Hennequin, Michalis Vazirgiannis:
Simple and Effective Graph Autoencoders with One-Hop Linear Models. 319-334 - Nicolas Nadisic
Sparse Separable Nonnegative Matrix Factorization. 335-350
Domain Adaptation
- Victor Bouvier, Philippe Very, Clément Chastagnol, Myriam Tami, Céline Hudelot:
Robust Domain Adaptation: Representations, Weights and Inductive Bias. 353-377 - Luxin Zhang, Pascal Germain
Target to Source Coordinate-Wise Adaptation of Pre-trained Models. 378-394 - Guillaume Richard, Antoine de Mathelin, Georges Hébrail, Mathilde Mougeot, Nicolas Vayatis:
Unsupervised Multi-source Domain Adaptation for Regression. 395-411 - Marwa Kechaou, Romain Hérault, Mokhtar Z. Alaya, Gilles Gasso:
Open Set Domain Adaptation Using Optimal Transport. 412-435
Sketching, Sampling, and Binary Projections
- Stephan Sloth Lorenzen
Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search. 439-455 - Wenye Li:
Modeling Winner-Take-All Competition in Sparse Binary Projections. 456-472 - Dingzhu Lurong, Yanlong Wen, Jiangwei Zhang, Xiaojie Yuan:
LOAD: LSH-Based ℓ 0-Sampling over Stream Data with Near-Duplicates. 473-489 - Jing Ma, Qiuchen Zhang, Joyce C. Ho, Li Xiong:
Spatio-Temporal Tensor Sketching via Adaptive Sampling. 490-506
Graphical Models and Causality
- Negar Safinianaini, Camila P. E. de Souza
Orthogonal Mixture of Hidden Markov Models. 509-525 - Katerina Hlavácková-Schindler
Poisson Graphical Granger Causality by Minimum Message Length. 526-541 - Shonosuke Harada, Hisashi Kashima:
Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation. 542-558
(Spatio-)Temporal Data and Recurrent Neural Networks
- Yangxin Lin, Yang Zhou
Real-Time Fine-Grained Freeway Traffic State Estimation Under Sparse Observation. 561-577 - Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S. Rosenblum:
Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics. 578-594 - Akihiro Yamaguchi, Shigeru Maya, Ken Ueno:
RLTS: Robust Learning Time-Series Shapelets. 595-611 - Ding Zhou, Yuanjun Gao, Liam Paninski:
Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model. 612-627 - Kanishka Khandelwal, Devendra Dhaka, Vivek Barsopia:
Predicting Future Classifiers for Evolving Non-linear Decision Boundaries. 628-643 - Oleg Iegorov, Sebastian Fischmeister:
Parameterless Semi-supervised Anomaly Detection in Univariate Time Series. 644-659 - Matthew Middlehurst
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification. 660-676 - Antonio Carta
Incremental Training of a Recurrent Neural Network Exploiting a Multi-scale Dynamic Memory. 677-693 - Anne Lambert, Françoise Le Bolzer, François Schnitzler
Flexible Recurrent Neural Networks. 694-709 - Zed Lee, Sarunas Girdzijauskas, Panagiotis Papapetrou:
Z-Embedding: A Spectral Representation of Event Intervals for Efficient Clustering and Classification. 710-726
Collaborative Filtering and Matrix Completion
- Vijaikumar M, Shirish K. Shevade, M. Narasimha Murty:
Neural Cross-Domain Collaborative Filtering with Shared Entities. 729-745 - Dong Hu, Alex Gittens, Malik Magdon-Ismail:
NoisyCUR: An Algorithm for Two-Cost Budgeted Matrix Completion. 746-761
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