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Machine Learning, Volume 111
Volume 111, Number 1, January 2022
- Pang Wei Koh, Jacob Steinhardt, Percy Liang:
Stronger data poisoning attacks break data sanitization defenses. 1-47 - Hansi Hettiarachchi, Mariam Adedoyin-Olowe, Jagdev Bhogal, Mohamed Medhat Gaber:
Embed2Detect: temporally clustered embedded words for event detection in social media. 49-87 - Vu-Linh Nguyen, Mohammad Hossein Shaker, Eyke Hüllermeier:
How to measure uncertainty in uncertainty sampling for active learning. 89-122 - Kun Gao, Hanpin Wang, Yongzhi Cao, Katsumi Inoue:
Learning from interpretation transition using differentiable logic programming semantics. 123-145 - Andrew Cropper, Sebastijan Dumancic, Richard Evans, Stephen H. Muggleton:
Inductive logic programming at 30. 147-172 - Alexander I. Cowen-Rivers, Daniel Palenicek, Vincent Moens, Mohammed Amin Abdullah, Aivar Sootla, Jun Wang, Haitham Bou-Ammar:
SAMBA: safe model-based & active reinforcement learning. 173-203 - Subhadeep Mukhopadhyay:
InfoGram and admissible machine learning. 205-242 - Guangyuan Gao, He Wang, Mario V. Wüthrich:
Boosting Poisson regression models with telematics car driving data. 243-272 - Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
ReliefE: feature ranking in high-dimensional spaces via manifold embeddings. 273-317 - Yaqiong Li, Xuhui Fan, Ling Chen, Bin Li, Scott A. Sisson:
Smoothing graphons for modelling exchangeable relational data. 319-344 - Yi Zhou, Yingbin Liang, Huishuai Zhang:
Understanding generalization error of SGD in nonconvex optimization. 345-375 - Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy:
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders. 377-414
Volume 111, Number 2, February 2022
- Tino Werner:
A review on instance ranking problems in statistical learning. 415-463 - Ozsel Kilinc, Giovanni Montana:
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations. 465-486 - Bernat Coma-Puig, Josep Carmona:
Non-technical losses detection in energy consumption focusing on energy recovery and explainability. 487-517 - Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy:
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks. 519-541 - Markus Viljanen, Antti Airola, Tapio Pahikkala:
Generalized vec trick for fast learning of pairwise kernel models. 543-573 - Tirtharaj Dash, Ashwin Srinivasan, A. Baskar:
Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment. 575-623 - Michele Fraccaroli, Evelina Lamma, Fabrizio Riguzzi:
Symbolic DNN-Tuner. 625-650 - Dimitrios Iliadis, Bernard De Baets, Willem Waegeman:
Multi-target prediction for dummies using two-branch neural networks. 651-684 - Ningyi Liao, Shufan Wang, Liyao Xiang, Nanyang Ye, Shuo Shao, Pengzhi Chu:
Achieving adversarial robustness via sparsity. 685-711 - Eyke Hüllermeier, Marcel Wever, Eneldo Loza Mencía, Johannes Fürnkranz, Michael Rapp:
A flexible class of dependence-aware multi-label loss functions. 713-737 - Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis, Christoph Bergmeir:
Model selection in reconciling hierarchical time series. 739-789 - Dimosthenis Pasadakis, Christie Louis Alappat, Olaf Schenk, Gerhard Wellein:
Multiway p-spectral graph cuts on Grassmann manifolds. 791-829
Volume 111, Number 3, March 2022
- Haonan Zhang, Longjun Liu, Hengyi Zhou, Hongbin Sun, Nanning Zheng:
CMD: controllable matrix decomposition with global optimization for deep neural network compression. 831-851 - Yi-Fan Ma, Ming Li:
The flowing nature matters: feature learning from the control flow graph of source code for bug localization. 853-870 - Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online strongly convex optimization with unknown delays. 871-893 - Changjian Shui, Boyu Wang, Christian Gagné:
On the benefits of representation regularization in invariance based domain generalization. 895-915 - Xueqing Wu, Yingce Xia, Jinhua Zhu, Lijun Wu, Shufang Xie, Tao Qin:
A study of BERT for context-aware neural machine translation. 917-935 - Junfan Li, Shizhong Liao:
Worst-case regret analysis of computationally budgeted online kernel selection. 937-976 - Yi-Feng Zhang, Fan-Ming Luo, Yang Yu:
Improve generated adversarial imitation learning with reward variance regularization. 977-995 - Trung Le, Khanh Nguyen, Dinh Q. Phung:
Improving kernel online learning with a snapshot memory. 997-1018 - Shogo Hayashi, Junya Honda, Hisashi Kashima:
Bayesian optimization with partially specified queries. 1019-1048 - Shudong Huang, Ivor W. Tsang, Zenglin Xu, Jiancheng Lv:
Multiple partitions alignment via spectral rotation. 1049-1072 - Chi Zhang, Benyi Hu, Yuhang Liuzhang, Le Wang, Li Liu, Yuehu Liu:
Switching: understanding the class-reversed sampling in tail sample memorization. 1073-1101 - Shaoyuan Li, Ye Shi, Sheng-Jun Huang, Songcan Chen:
Improving deep label noise learning with dual active label correction. 1103-1124 - Haoran Liu, Haoyi Xiong, Yaqing Wang, Haozhe An, Dejing Dou, Dongrui Wu:
Exploring the common principal subspace of deep features in neural networks. 1125-1157 - Jiezhang Cao, Jincheng Li, Xiping Hu, Xiangmiao Wu, Mingkui Tan:
Towards interpreting deep neural networks via layer behavior understanding. 1159-1179 - Shufang Xie, Yingce Xia, Lijun Wu, Yiqing Huang, Yang Fan, Tao Qin:
End-to-end entity-aware neural machine translation. 1181-1203
Volume 111, Number 4, April 2022
- Luca Pasa, Nicolò Navarin, Alessandro Sperduti:
Polynomial-based graph convolutional neural networks for graph classification. 1205-1237 - Tomoharu Iwata, Yusuke Tanaka:
Few-shot learning for spatial regression via neural embedding-based Gaussian processes. 1239-1257 - Federico Cerutti, Lance M. Kaplan, Angelika Kimmig, Murat Sensoy:
Handling epistemic and aleatory uncertainties in probabilistic circuits. 1259-1301 - Alice Tarzariol, Martin Gebser, Konstantin Schekotihin:
Lifting symmetry breaking constraints with inductive logic programming. 1303-1326 - Jiangjiang Gao, Jinhui Lan, Bingxu Wang, Feifan Li:
SDANet: spatial deep attention-based for point cloud classification and segmentation. 1327-1348 - Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm:
Efficient SVDD sampling with approximation guarantees for the decision boundary. 1349-1375 - Dennis Bäßler, Tobias Kortus, Gabriele Gühring:
Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks. 1377-1408 - Dawon Ahn, Jun-Gi Jang, U Kang:
Time-aware tensor decomposition for sparse tensors. 1409-1430 - Lionel Blondé, Pablo Strasser, Alexandros Kalousis:
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning. 1431-1521 - Ludovico Mitchener, David Tuckey, Matthew Crosby, Alessandra Russo:
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework. 1523-1549 - András Hajdu, György Terdik, Attila Tiba, Henrietta Tomán:
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning. 1551-1595 - Joseph Marino, Lei Chen, Jiawei He, Stephan Mandt:
Improving sequential latent variable models with autoregressive flows. 1597-1620
Volume 111, Number 5, May 2022
- Deepayan Chakrabarti:
Robust linear classification from limited training data. 1621-1649 - Alain Rakotomamonjy, Rémi Flamary, Gilles Gasso, M. El Alaya, Maxime Berar, Nicolas Courty:
Optimal transport for conditional domain matching and label shift. 1651-1670 - Ayano Nakai-Kasai, Toshiyuki Tanaka:
Nested aggregation of experts using inducing points for approximated Gaussian process regression. 1671-1694 - Jireh Huang, Qing Zhou:
Partitioned hybrid learning of Bayesian network structures. 1695-1738 - Paul Riverain, Simon Fossier, Mohamed Nadif:
Semi-supervised Latent Block Model with pairwise constraints. 1739-1764 - Hervé Falciani, Enrique Alfonso Sánchez-Pérez:
Semi-Lipschitz functions and machine learning for discrete dynamical systems on graphs. 1765-1797 - Johannes Rabold, Michael Siebers, Ute Schmid:
Generating contrastive explanations for inductive logic programming based on a near miss approach. 1799-1820 - Arthur Leroy, Pierre Latouche, Benjamin Guedj, Servane Gey:
MAGMA: inference and prediction using multi-task Gaussian processes with common mean. 1821-1849 - Daniel Bakkelund:
Order preserving hierarchical agglomerative clustering. 1851-1901 - Rick Wilming, Céline Budding, Klaus-Robert Müller, Stefan Haufe:
Scrutinizing XAI using linear ground-truth data with suppressor variables. 1903-1923 - Wei Huang, Xingyu Zhao, Xiaowei Huang:
Embedding and extraction of knowledge in tree ensemble classifiers. 1925-1958 - Zhuoer Xu, Guanghui Zhu, Chunfeng Yuan, Yihua Huang:
One-Stage Tree: end-to-end tree builder and pruner. 1959-1985
Volume 111, Number 6, June 2022
- Mohammad Nabati, Seyed Ali Ghorashi, Reza Shahbazian:
JGPR: a computationally efficient multi-target Gaussian process regression algorithm. 1987-2010 - Tuan Pham, Daniel Kottke, Georg Krempl, Bernhard Sick:
Stream-based active learning for sliding windows under the influence of verification latency. 2011-2036 - Ke Li, Gang Wu:
Randomized approximate class-specific kernel spectral regression analysis for large-scale face verification. 2037-2091 - Alberto Maria Metelli, Guglielmo Manneschi, Marcello Restelli:
Policy space identification in configurable environments. 2093-2145 - Tilmann Gneiting, Peter Vogel:
Receiver operating characteristic (ROC) curves: equivalences, beta model, and minimum distance estimation. 2147-2159 - Dimitris Bertsimas, Vassilis Digalakis:
The backbone method for ultra-high dimensional sparse machine learning. 2161-2212 - Michaël Fanuel, Joachim Schreurs, Johan A. K. Suykens:
Nyström landmark sampling and regularized Christoffel functions. 2213-2254 - Floris den Hengst, Vincent François-Lavet, Mark Hoogendoorn, Frank van Harmelen:
Planning for potential: efficient safe reinforcement learning. 2255-2274 - Jiantao Wu, Lin Wang, Bo Yang, Fanqi Li, Chunxiuzi Liu, Jin Zhou:
DEFT: distilling entangled factors by preventing information diffusion. 2275-2295 - Jing Wang, Jie Shen:
Fast spectral analysis for approximate nearest neighbor search. 2297-2322 - Tingting Zhai, Frédéric Koriche, Yang Gao, Junwu Zhu, Bin Li:
Online active classification via margin-based and feature-based label queries. 2323-2348 - Ibrahim Ayed, Emmanuel de Bézenac, Arthur Pajot, Patrick Gallinari:
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations. 2349-2380
Volume 111, Number 7, July 2022
- Shuo Chen, Ke Xu, Zhongjie Mi, Xinghao Jiang, Tanfeng Sun:
Dual-domain graph convolutional networks for skeleton-based action recognition. 2381-2406 - Aleksei Kuvshinov, Stephan Günnemann:
Robustness verification of ReLU networks via quadratic programming. 2407-2433 - Ashwin Srinivasan, Michael Bain, A. Baskar:
Learning explanations for biological feedback with delays using an event calculus. 2435-2487 - Shufei Zhang, Kaizhu Huang, Zenglin Xu:
Re-thinking model robustness from stability: a new insight to defend adversarial examples. 2489-2513 - Kornraphop Kawintiranon, Lisa Singh, Ceren Budak:
Traditional and context-specific spam detection in low resource settings. 2515-2536 - Ga Wu, Justin Domke, Scott Sanner:
Arbitrary conditional inference in variational autoencoders via fast prior network training. 2537-2559 - Alberto Cano, Bartosz Krawczyk:
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams. 2561-2599 - Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
A generalized Weisfeiler-Lehman graph kernel. 2601-2629 - Bhisham Dev Verma, Rameshwar Pratap, Manoj Thakur:
Variance reduction in feature hashing using MLE and control variate method. 2631-2662 - Robert Hu, Geoff K. Nicholls, Dino Sejdinovic:
Large scale tensor regression using kernels and variational inference. 2663-2713 - Nicolas Karasiak, Jean-Francois Dejoux, Claude Monteil, David Sheeren:
Spatial dependence between training and test sets: another pitfall of classification accuracy assessment in remote sensing. 2715-2740 - Maxime Amram, Jack Dunn, Ying Daisy Zhuo:
Optimal policy trees. 2741-2768
Volume 111, Number 8, August 2022
- Tilmann Gneiting, Eva-Maria Walz:
Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA). 2769-2797 - Sriram Srinivasan, Charles Dickens, Eriq Augustine, Golnoosh Farnadi, Lise Getoor:
A taxonomy of weight learning methods for statistical relational learning. 2799-2838 - Nikolaj Tatti:
Maintaining AUC and H-measure over time. 2839-2862 - Oliver Urs Lenz, Daniel Peralta, Chris Cornelis:
Optimised one-class classification performance. 2863-2883 - Laercio de Oliveira Junior, Florian Stelzer, Liang Zhao:
Clustered and deep echo state networks for signal noise reduction. 2885-2904 - Chaojie Wang, Jin Du, Xiaodan Fan:
High-dimensional correlation matrix estimation for general continuous data with Bagging technique. 2905-2927 - Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Hisashi Kashima:
Context-aware spatio-temporal event prediction via convolutional Hawkes processes. 2929-2950 - Dimitris Bertsimas, Jack Dunn, Emma Gibson, Agni Orfanoudaki:
Optimal survival trees. 2951-3023 - Ha Nguyen, Hoang Pham, Son Nguyen, Ngo Van Linh, Khoat Than:
Adaptive infinite dropout for noisy and sparse data streams. 3025-3060 - Stassa Patsantzis, Stephen H. Muggleton:
Correction to: Meta-interpretive learning as metarule specialisation. 3061 - Dimitris Bertsimas, Alex Paskov:
World-class interpretable poker. 3063-3083 - Pedro Yuri Arbs Paiva, Camila Castro Moreno, Kate Smith-Miles, Maria Gabriela Valeriano, Ana Carolina Lorena:
Relating instance hardness to classification performance in a dataset: a visual approach. 3085-3123
Volume 111, Number 9, September 2022
- Lili Geng, Baoning Niu:
Pruning convolutional neural networks via filter similarity analysis. 3161-3180 - Chuang Zhang, Li Shen, Jian Yang, Chen Gong:
Towards harnessing feature embedding for robust learning with noisy labels. 3181-3201 - Thomas Baumhauer, Pascal Schöttle, Matthias Zeppelzauer:
Machine unlearning: linear filtration for logit-based classifiers. 3203-3226 - Mike Huisman, Aske Plaat, Jan N. van Rijn:
Stateless neural meta-learning using second-order gradients. 3227-3244 - Samer Saab Jr., Shashi Phoha, Minghui Zhu, Asok Ray:
An adaptive polyak heavy-ball method. 3245-3277 - Siwei Wang, Wei Chen:
The pure exploration problem with general reward functions depending on full distributions. 3279-3306 - Alexey Miroshnikov, Konstandinos Kotsiopoulos, Ryan Franks, Arjun Ravi Kannan:
Wasserstein-based fairness interpretability framework for machine learning models. 3307-3357 - Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu:
Stabilize deep ResNet with a sharp scaling factor τ. 3359-3392 - Benjamin Paaßen, Irena Koprinska, Kalina Yacef:
Recursive tree grammar autoencoders. 3393-3423 - Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif:
On the robustness of randomized classifiers to adversarial examples. 3425-3457 - Amal Saadallah, Matthias Jakobs, Katharina Morik:
Explainable online ensemble of deep neural network pruning for time series forecasting. 3459-3487
Volume 111, Number 10, October 2022
- Ben Halstead, Yun Sing Koh, Patricia Riddle, Russel Pears, Mykola Pechenizkiy, Albert Bifet, Gustavo Olivares, Guy Coulson:
Analyzing and repairing concept drift adaptation in data stream classification. 3489-3523 - Mohammad Tanveer, Aruna Tiwari, Rahul Choudhary, M. A. Ganaie:
Large-scale pinball twin support vector machines. 3525-3548 - Mariana Caravanti de Souza, Bruno Magalhães Nogueira, Rafael Geraldeli Rossi, Ricardo Marcondes Marcacini, Brucce Neves dos Santos, Solange Oliveira Rezende:
A network-based positive and unlabeled learning approach for fake news detection. 3549-3592 - Tony Ribeiro, Maxime Folschette, Morgan Magnin, Katsumi Inoue:
Learning any memory-less discrete semantics for dynamical systems represented by logic programs. 3593-3670 - Mohammad Mahdi Kamani, Farzin Haddadpour, Rana Forsati, Mehrdad Mahdavi:
Efficient fair principal component analysis. 3671-3702 - Stassa Patsantzis, Stephen H. Muggleton:
Meta-interpretive learning as metarule specialisation. 3703-3731 - Xin Ma, Suprateek Kundu, Jennifer S. Stevens:
Semi-parametric Bayes regression with network-valued covariates. 3733-3767 - Guilherme Ramos, Ludovico Boratto, Mirko Marras:
Robust reputation independence in ranking systems for multiple sensitive attributes. 3769-3796 - Wen-Chi Yang, Jean-François Raskin, Luc De Raedt:
Lifted model checking for relational MDPs. 3797-3838 - Victor Eberstein, Jonas Sjöblom, Nikolce Murgovski, Morteza Haghir Chehreghani:
A unified framework for online trip destination prediction. 3839-3865 - Yang Liu, Anthony C. Constantinou:
Greedy structure learning from data that contain systematic missing values. 3867-3896 - Anna Jenul, Stefan Schrunner, Jürgen Pilz, Oliver Tomic:
A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS). 3897-3923
Volume 111, Number 11, November 2022
- Julia Grabinski, Janis Keuper, Margret Keuper:
Aliasing and adversarial robust generalization of CNNs. 3925-3951 - Erik Schultheis, Rohit Babbar:
Speeding-up one-versus-all training for extreme classification via mean-separating initialization. 3953-3976 - Mingze Ni, Ce Wang, Tianqing Zhu, Shui Yu, Wei Liu:
Attacking neural machine translations via hybrid attention learning. 3977-4002 - Surojit Saha, Shireen Y. Elhabian, Ross T. Whitaker:
GENs: generative encoding networks. 4003-4038 - Saad Mohamad, Hamad Alamri, Abdelhamid Bouchachia:
Scaling up stochastic gradient descent for non-convex optimisation. 4039-4079 - Matteo Papini, Matteo Pirotta, Marcello Restelli:
Smoothing policies and safe policy gradients. 4081-4137 - Fateme Nateghi Haredasht, Celine Vens:
Predicting Survival Outcomes in the Presence of Unlabeled Data. 4139-4157 - Mourad El Hamri, Younès Bennani, Issam Falih:
Hierarchical optimal transport for unsupervised domain adaptation. 4159-4182 - Nora Muñoz-Izquierdo, María Jesús Segovia-Vargas, María-del-Mar Camacho-Miñano, Yolanda Pérez-Pérez:
Machine learning in corporate credit rating assessment using the expanded audit report. 4183-4215 - Javier García, Álvaro Visús, Fernando Fernández:
A taxonomy for similarity metrics between Markov decision processes. 4217-4247 - César Sabater, Aurélien Bellet, Jan Ramon:
An accurate, scalable and verifiable protocol for federated differentially private averaging. 4249-4293 - Moritz Wolter, Felix Blanke, Raoul Heese, Jochen Garcke:
Wavelet-packets for deepfake image analysis and detection. 4295-4327
Volume 111, Number 12, December 2022
- Keng-Te Liao, Bo-Wei Huang, Chih-Chun Yang, Shou-De Lin:
Bayesian mixture variational autoencoders for multi-modal learning. 4329-4357 - Benjamin Dubois-Taine, Sharan Vaswani, Reza Babanezhad, Mark Schmidt, Simon Lacoste-Julien:
SVRG meets AdaGrad: painless variance reduction. 4359-4409 - Zahra Atashgahi, Joost Pieterse, Shiwei Liu, Decebal Constantin Mocanu, Raymond N. J. Veldhuis, Mykola Pechenizkiy:
A brain-inspired algorithm for training highly sparse neural networks. 4411-4452 - Nicolas Nadisic, Jeremy E. Cohen, Arnaud Vandaele, Nicolas Gillis:
Matrix-wise ℓ 0-constrained sparse nonnegative least squares. 4453-4495 - Stefanos Bennett, Mihai Cucuringu, Gesine Reinert:
Lead-lag detection and network clustering for multivariate time series with an application to the US equity market. 4497-4538 - Mohammadreza Qaraei, Rohit Babbar:
Adversarial examples for extreme multilabel text classification. 4539-4563 - Matthias König, Holger H. Hoos, Jan N. van Rijn:
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio. 4565-4584 - Narinder Singh Punn, Sonali Agarwal:
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models. 4585-4600 - Aniket Anand Deshmukh, Jayanth Reddy Regatti, Eren Manavoglu, Ürün Dogan:
Representation learning for clustering via building consensus. 4601-4638 - Wenjie Li, Zhanyu Wang, Yichen Zhang, Guang Cheng:
Variance reduction on general adaptive stochastic mirror descent. 4639-4677 - Matthew J. Holland:
Learning with risks based on M-location. 4679-4718 - Weijia Shao, Fikret Sivrikaya, Sahin Albayrak:
Optimistic optimisation of composite objective with exponentiated update. 4719-4764
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