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Data Mining and Knowledge Discovery, Volume 38
Volume 38, Number 1, January 2024
- William Shiao, Benjamin A. Miller, Kevin Chan, Paul L. Yu, Tina Eliassi-Rad, Evangelos E. Papalexakis:
TenGAN: adversarially generating multiplex tensor graphs. 1-21 - Navid Mohammadi Foumani, Chang Wei Tan, Geoffrey I. Webb, Mahsa Salehi:
Improving position encoding of transformers for multivariate time series classification. 22-48 - Barbara Zogala-Siudem, Szymon Jaroszewicz:
Variable screening for Lasso based on multidimensional indexing. 49-78 - Ninghan Chen, Xihui Chen, Zhiqiang Zhong, Jun Pang:
A tale of two roles: exploring topic-specific susceptibility and influence in cascade prediction. 79-109 - Georgios Katsimpras, Georgios Paliouras:
Improving Graph Neural Networks by combining active learning with self-training. 110-127 - Nikolaos Mylonas, Ioannis Mollas, Grigorios Tsoumakas:
An attention matrix for every decision: faithfulness-based arbitration among multiple attention-based interpretations of transformers in text classification. 128-153 - Wei Wang, Wenhan Ruan, Xiangfu Meng:
MODE-Bi-GRU: orthogonal independent Bi-GRU model with multiscale feature extraction. 154-172 - Haiyang Xia, Nayyar Zaidi, Yishuo Zhang, Gang Li:
Improving neural network's robustness on tabular data with D-layers. 173-205 - Zed Lee, Tony Lindgren, Panagiotis Papapetrou:
Z-Time: efficient and effective interpretable multivariate time series classification. 206-236 - Amir Hossein Akhavan Rahnama, Judith Bütepage, Pierre Geurts, Henrik Boström:
Can local explanation techniques explain linear additive models? 237-280 - Simone Fabbrizzi, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi:
Studying bias in visual features through the lens of optimal transport. 281-312 - Simone Fabbrizzi, Xuan Zhao, Emmanouil Krasanakis, Symeon Papadopoulos, Eirini Ntoutsi:
Correction to: Studying bias in visual features through the lens of optimal transport. 313-314 - João Palet, Vasco Manquinho, Rui Henriques:
Multiple-input neural networks for time series forecasting incorporating historical and prospective context. 315-341
Volume 38, Number 2, March 2024
- Tao He, Ming Liu, Yixin Cao, Meng Qu, Zihao Zheng, Bing Qin:
VEM2L: an easy but effective framework for fusing text and structure knowledge on sparse knowledge graph completion. 343-371 - Clément Gautrais, Peggy Cellier, Thomas Guyet, René Quiniou, Alexandre Termier:
Sky-signatures: detecting and characterizing recurrent behavior in sequential data. 372-419 - Ashna Jose, João Paulo Almeida de Mendonça, Emilie Devijver, Noël Jakse, Valérie Monbet, Roberta Poloni:
Regression tree-based active learning. 420-460 - João Luiz Junho Pereira, Kate Smith-Miles, Mario Andrés Muñoz, Ana Carolina Lorena:
Optimal selection of benchmarking datasets for unbiased machine learning algorithm evaluation. 461-500 - Dongsheng Duan, Cheng Zhang, Lingling Tong, Jie Lu, Cunchi Lv, Wei Hou, Yangxi Li, Xiaofang Zhao:
An anomaly aware network embedding framework for unsupervised anomalous link detection. 501-534 - Alessio Molinari, Andrea Esuli:
SALτ: efficiently stopping TAR by improving priors estimates. 535-568 - Martin Khannouz, Tristan Glatard:
Mondrian forest for data stream classification under memory constraints. 569-596 - Gang-Feng Ma, Xu-Hua Yang, Wei Ye, Xin-Li Xu, Lei Ye:
Network embedding based on high-degree penalty and adaptive negative sampling. 597-622 - Zhenxiang Cao, Nick Seeuws, Maarten De Vos, Alexander Bertrand:
A semi-supervised interactive algorithm for change point detection. 623-651 - Zhenxiang Cao, Nick Seeuws, Maarten De Vos, Alexander Bertrand:
Correction: A semi‑supervised interactive algorithm for change point detection. 652 - Hélder Alves, Paula Brito, Pedro Campos:
Community detection in interval-weighted networks. 653-698 - Guihong Wan, Baokun He, Haim Schweitzer:
The art of centering without centering for robust principal component analysis. 699-724 - Ilaria Bombelli, Ichcha Manipur, Mario Rosario Guarracino, Maria Brigida Ferraro:
Representing ensembles of networks for fuzzy cluster analysis: a case study. 725-747 - Nestor Cabello, Elham Naghizade, Jianzhong Qi, Lars Kulik:
Fast, accurate and explainable time series classification through randomization. 748-811 - Ashkan Farhangi, Jiang Bian, Arthur Huang, Haoyi Xiong, Jun Wang, Zhishan Guo:
Correction to: AA-forecast: anomaly-aware forecast for extreme events. 812
Volume 38, Number 3, May 2024
- Ali Javed, Donna M. Rizzo, Byung Suk Lee, Robert Gramling:
Somtimes: self organizing maps for time series clustering and its application to serious illness conversations. 813-839 - Moritz Herrmann, Daniyal Kazempour, Fabian Scheipl, Peer Kröger:
Enhancing cluster analysis via topological manifold learning. 840-887 - Sowon Jeon, Gilhee Lee, Hyoungshick Kim, Simon S. Woo:
Design and evaluation of highly accurate smart contract code vulnerability detection framework. 888-912 - Arian Prabowo, Hao Xue, Wei Shao, Piotr Koniusz, Flora D. Salim:
Traffic forecasting on new roads using spatial contrastive pre-training (SCPT). 913-937 - Anne Hartebrodt, Richard Röttger, David B. Blumenthal:
Federated singular value decomposition for high-dimensional data. 938-975 - Luka Biedebach, María Óskarsdóttir, Erna Sif Arnardóttir, Sigríður Sigurðardóttir, Michael Clausen, Sigurveig Þóra Sigurardóttir, Marta Serwatko, Anna Sigridur Islind:
Anomaly detection in sleep: detecting mouth breathing in children. 976-1005 - Nourhan Ahmed, Lars Schmidt-Thieme:
Structure-aware decoupled imputation network for multivariate time series. 1006-1026 - Sondre Sørbø, Massimiliano Ruocco:
Navigating the metric maze: a taxonomy of evaluation metrics for anomaly detection in time series. 1027-1068 - Moshe Unger, Michel Wedel, Alexander Tuzhilin:
Predicting consumer choice from raw eye-movement data using the RETINA deep learning architecture. 1069-1100 - Ling Jian, Kai Shao, Ying Liu, Jundong Li, Xijun Liang:
OEC: an online ensemble classifier for mining data streams with noisy labels. 1101-1124 - Michael G. Schimek, Luca Vitale, Bastian Pfeifer, Michele La Rocca:
Effective signal reconstruction from multiple ranked lists via convex optimization. 1125-1169 - Michael G. Schimek, Luca Vitale, Bastian Pfeifer, Michele La Rocca:
Correction to: Effective signal reconstruction from multiple ranked lists via convex optimization. 1170 - Zhanbo Liang, Jie Guo, Weidong Qiu, Zheng Huang, Shujun Li:
When graph convolution meets double attention: online privacy disclosure detection with multi-label text classification. 1171-1192 - Huizi Wu, Cong Geng, Hui Fang:
Session-based recommendation by exploiting substitutable and complementary relationships from multi-behavior data. 1193-1221 - Jaewan Chun, Geon Lee, Kijung Shin, Jinhong Jung:
Random walk with restart on hypergraphs: fast computation and an application to anomaly detection. 1222-1257 - Tobias Koopmann, Martin Becker, Florian Lemmerich, Andreas Hotho:
CompTrails: comparing hypotheses across behavioral networks. 1258-1288 - Antonio R. Moya, Bruno Veloso, João Gama, Sebastián Ventura:
Improving hyper-parameter self-tuning for data streams by adapting an evolutionary approach. 1289-1315 - Kang Tang, Shasha Li, Jintao Tang, Dong Li, Pancheng Wang, Ting Wang:
Fusing structural information with knowledge enhanced text representation for knowledge graph completion. 1316-1333 - Marco Heyden, Edouard Fouché, Vadim Arzamasov, Tanja Fenn, Florian Kalinke, Klemens Böhm:
Adaptive Bernstein change detector for high-dimensional data streams. 1334-1363 - Rafael Gomes Mantovani, Tomás Horváth, André L. D. Rossi, Ricardo Cerri, Sylvio Barbon Junior, Joaquin Vanschoren, André C. P. L. F. de Carvalho:
Better trees: an empirical study on hyperparameter tuning of classification decision tree induction algorithms. 1364-1416 - Yan Liu, Xue Feng, Jun Lou, Lianyu Hu, Zengyou He:
Central node identification via weighted kernel density estimation. 1417-1439 - Stefano Masini, Silvia Bacci, Fabrizio Cipollini, Bruno Bertaccini:
Revealing the structural behaviour of Brunelleschi's Dome with machine learning techniques. 1440-1465 - Sheng Zhong, Abdullah Mueen:
MASS: distance profile of a query over a time series. 1466-1492 - Nazanin Moradinasab, Suchetha Sharma, Ronen Bar-Yoseph, Shlomit Radom-Aizik, Kenneth C. Bilchick, Dan M. Cooper, Arthur Weltman, Donald E. Brown:
Universal representation learning for multivariate time series using the instance-level and cluster-level supervised contrastive learning. 1493-1519 - Manuele Leonelli, Gherardo Varando:
Structural learning of simple staged trees. 1520-1544
Volume 38, Number 4, July 2024
- Manjusha Ravindranath, K. Selçuk Candan, Maria Luisa Sapino, Brian Appavu:
MMA: metadata supported multi-variate attention for onset detection and prediction. 1545-1588 - Husheng Guo, Hai Li, Lu Cong, Wenjian Wang:
Online concept evolution detection based on active learning. 1589-1633 - Xinran Wu, Kun Yue, Liang Duan, Xiaodong Fu:
Learning a Bayesian network with multiple latent variables for implicit relation representation. 1634-1669 - Pablo González, Alejandro Moreo, Fabrizio Sebastiani:
Binary quantification and dataset shift: an experimental investigation. 1670-1712 - Paolo Bonetti, Alberto Maria Metelli, Marcello Restelli:
Interpretable linear dimensionality reduction based on bias-variance analysis. 1713-1781 - Lars Henry Berge Olsen, Ingrid Kristine Glad, Martin Jullum, Kjersti Aas:
A comparative study of methods for estimating model-agnostic Shapley value explanations. 1782-1829 - Annabelle Redelmeier, Martin Jullum, Kjersti Aas, Anders Løland:
MCCE: Monte Carlo sampling of valid and realistic counterfactual explanations for tabular data. 1830-1861 - Jorge Marco-Blanco, Rubén Cuevas:
Time series clustering with random convolutional kernels. 1862-1888 - Helen L. Smith, Patrick J. Biggs, Nigel French, Adam N. H. Smith, Jonathan C. Marshall:
Lost in the Forest: Encoding categorical variables and the absent levels problem. 1889-1908 - Raphael Fischer, Thomas Liebig, Katharina Morik:
Towards more sustainable and trustworthy reporting in machine learning. 1909-1928 - Hongyu Wang, Wei Zhou, Junhao Wen, Shutong Qiao:
Multiple hypergraph convolutional network social recommendation using dual contrastive learning. 1929-1957 - Matthew Middlehurst, Patrick Schäfer, Anthony J. Bagnall:
Bake off redux: a review and experimental evaluation of recent time series classification algorithms. 1958-2031 - Bo Peng, Srinivasan Parthasarathy, Xia Ning:
Intention enhanced mixed attentive model for session-based recommendation. 2032-2061 - Antonio Ferrara, Francesco Bonchi, Francesco Fabbri, Fariba Karimi, Claudia Wagner:
Bias-aware ranking from pairwise comparisons. 2062-2086 - Colin Troisemaine, Alexandre Reiffers-Masson, Stéphane Gosselin, Vincent Lemaire, Sandrine Vaton:
A practical approach to novel class discovery in tabular data. 2087-2116 - Thomas Robinson, Niek Tax, Richard Mudd, Ido Guy:
Active learning with biased non-response to label requests. 2117-2140 - David Guijo-Rubio, Matthew Middlehurst, Guilherme Arcencio, Diego Furtado Silva, Anthony J. Bagnall:
Unsupervised feature based algorithms for time series extrinsic regression. 2141-2185 - Eliana Pastor, Francesco Bonchi:
Intersectional fair ranking via subgroup divergence. 2186-2222 - Yishuo Zhang, Nayyar Zaidi, Jiahui Zhou, Tao Wang, Gang Li:
Effective interpretable learning for large-scale categorical data. 2223-2251 - Karima Makhlouf, Héber Hwang Arcolezi, Sami Zhioua, Ghassen Ben Brahim, Catuscia Palamidessi:
On the impact of multi-dimensional local differential privacy on fairness. 2252-2275 - Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel:
LoCoMotif: discovering time-warped motifs in time series. 2276-2305 - Martino Ciaperoni, Aristides Gionis, Heikki Mannila:
The Hadamard decomposition problem. 2306-2347 - Mingjie Qiu, Zhiyi Tan, Bing-Kun Bao:
MSGNN: Multi-scale Spatio-temporal Graph Neural Network for epidemic forecasting. 2348-2376 - Angus Dempster, Daniel F. Schmidt, Geoffrey I. Webb:
quant: a minimalist interval method for time series classification. 2377-2402 - Etienne Lehembre, Bruno Crémilleux, Albrecht Zimmermann, Bertrand Cuissart, Abdelkader Ouali:
WaveLSea: helping experts interactively explore pattern mining search spaces. 2403-2439 - Chih-Chieh Chang, Diing-Ruey Tzeng, Chia-Hsun Lu, Ming-Yi Chang, Chih-Ya Shen:
Improving graph-based recommendation with unraveled graph learning. 2440-2465 - Jannat Ara Meem, Muhammad Shihab Rashid, Vagelis Hristidis:
Modeling the impact of out-of-schema questions in task-oriented dialog systems. 2466-2494 - Jinping Hu, Evert de Haan, Bernd Skiera:
Uplift modeling with quasi-loss-functions. 2495-2519 - Navid Mohammadi Foumani, Chang Wei Tan, Geoffrey I. Webb, Hamid Rezatofighi, Mahsa Salehi:
Series2vec: similarity-based self-supervised representation learning for time series classification. 2520-2544 - Neville Kenneth Kitson, Anthony C. Constantinou:
The impact of variable ordering on Bayesian network structure learning. 2545-2569
Volume 38, Number 5, September 2024
- Martin Atzmueller, Johannes Fürnkranz, Tomás Kliegr, Ute Schmid:
Explainable and interpretable machine learning and data mining. 2571-2595 - Hubert Baniecki, Dariusz Parzych, Przemyslaw Biecek:
The grammar of interactive explanatory model analysis. 2596-2632 - Andreas Brandsæter, Ingrid Kristine Glad:
Shapley values for cluster importance. 2633-2664 - Dieter Brughmans, Pieter Leyman, David Martens:
NICE: an algorithm for nearest instance counterfactual explanations. 2665-2703 - Bernat Coma-Puig, Albert Calvo, Josep Carmona, Ricard Gavaldà:
A case study of improving a non-technical losses detection system through explainability. 2704-2732 - Riccardo Crupi, Alessandro Castelnovo, Daniele Regoli, Beatriz San Miguel González:
Counterfactual explanations as interventions in latent space. 2733-2769 - Riccardo Guidotti:
Counterfactual explanations and how to find them: literature review and benchmarking. 2770-2824 - Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri, Francesca Naretto, Franco Turini, Dino Pedreschi, Fosca Giannotti:
Stable and actionable explanations of black-box models through factual and counterfactual rules. 2825-2862 - Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov:
Sparse oblique decision trees: a tool to understand and manipulate neural net features. 2863-2902 - Christoph Molnar, Gunnar König, Bernd Bischl, Giuseppe Casalicchio:
Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach. 2903-2941 - Marcos M. Raimundo, Luis Gustavo Nonato, Jorge Poco:
Mining Pareto-optimal counterfactual antecedents with a branch-and-bound model-agnostic algorithm. 2942-2974 - Johannes Schneider, Michalis Vlachos:
Reflective-net: learning from explanations. 2975-2996 - Christian A. Scholbeck, Giuseppe Casalicchio, Christoph Molnar, Bernd Bischl, Christian Heumann:
Marginal effects for non-linear prediction functions. 2997-3042 - Gesina Schwalbe, Bettina Finzel:
A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts. 3043-3101 - Kacper Sokol, Peter A. Flach:
Interpretable representations in explainable AI: from theory to practice. 3102-3140 - Francesco Sovrano, Fabio Vitali:
Explanatory artificial intelligence (YAI): human-centered explanations of explainable AI and complex data. 3141-3168 - Francesco Ventura, Salvatore Greco, Daniele Apiletti, Tania Cerquitelli:
Explaining deep convolutional models by measuring the influence of interpretable features in image classification. 3169-3226 - Luca Veyrin-Forrer, Ataollah Kamal, Stefan Duffner, Marc Plantevit, Céline Robardet:
On GNN explainability with activation rules. 3227-3261 - Domen Vres, Marko Robnik-Sikonja:
Preventing deception with explanation methods using focused sampling. 3262-3307 - Yichen Zhou, Zhengze Zhou, Giles Hooker:
Approximation trees: statistical reproducibility in model distillation. 3308-3346
Volume 38, Number 6, November 2024
- Omar Bahri, Peiyu Li, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi:
Discord-based counterfactual explanations for time series classification. 3347-3371 - Thu Trang Nguyen, Thach Le Nguyen, Georgiana Ifrim:
Robust explainer recommendation for time series classification. 3372-3413 - Margot Geerts, Seppe vanden Broucke, Jochen De Weerdt:
GeoRF: a geospatial random forest. 3414-3448 - Bingqing Liu:
Modelling event sequence data by type-wise neural point process. 3449-3472 - Xiaosheng Li, Wenjie Xi, Jessica Lin:
Randomnet: clustering time series using untrained deep neural networks. 3473-3502 - Pu Wang, Jingya Sun, Wei Chen, Lei Zhao:
Towards effective urban region-of-interest demand modeling via graph representation learning. 3503-3530 - Zhuoxun Zheng, Baifan Zhou, Hui Yang, Zhipeng Tan, Zequn Sun, Chunnong Li, Arild Waaler, Evgeny Kharlamov, Ahmet Soylu:
Knowledge graph embedding closed under composition. 3531-3562 - Yingying Zhang, Shuchismita Sarkar, Yuanyuan Chen, Xuwen Zhu:
On regime changes in text data using hidden Markov model of contaminated vMF distribution. 3563-3589 - Adil Bahaj, Mounir Ghogho:
Negative-sample-free knowledge graph embedding. 3590-3620 - Nikolaj Tatti:
Explainable decomposition of nested dense subgraphs. 3621-3642 - Yi Sui, Alex Kwan, Alexander W. Olson, Scott Sanner, Daniel A. Silver:
Bayesian network Motifs for reasoning over heterogeneous unlinked datasets. 3643-3689 - Sacha Corbugy, Rebecca Marion, Benoît Frénay:
Gradient-based explanation for non-linear non-parametric dimensionality reduction. 3690-3718 - Philipp Röchner, Henrique O. Marques, Ricardo J. G. B. Campello, Arthur Zimek:
Evaluating outlier probabilities: assessing sharpness, refinement, and calibration using stratified and weighted measures. 3719-3757