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ORCIDMachine Learning, Volume 113
Volume 113, Number 1, January 2024
- Déborah Sulem
, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong:
Graph similarity learning for change-point detection in dynamic networks. 1-44 - Rahul Singh, Fang Liu, Yin Sun, Ness B. Shroff:
Multi-armed bandits with dependent arms. 45-71 - Vasco Lopes, Fabio Maria Carlucci, Pedro M. Esperança, Marco Singh, Antoine Yang, Victor Gabillon, Hang Xu, Zewei Chen, Jun Wang:
Manas: multi-agent neural architecture search. 73-96 - Ehsan Kazemi, Liqiang Wang:
Efficient zeroth-order proximal stochastic method for nonconvex nonsmooth black-box problems. 97-120 - Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoff Holmes:
Feature extractor stacking for cross-domain few-shot learning. 121-158 - Dimitris Bertsimas, Kimberly Villalobos Carballo, Léonard Boussioux, Michael Lingzhi Li, Alex Paskov, Ivan S. Paskov:
Holistic deep learning. 159-183 - Davide Cacciarelli, Murat Kulahci:
Active learning for data streams: a survey. 185-239 - Young Woong Park, Jinhak Kim, Dan Zhu:
Discordance minimization-based imputation algorithms for missing values in rating data. 241-279 - Nam Le Hai, Trang Nguyen, Ngo Van Linh, Thien Huu Nguyen, Khoat Than:
Continual variational dropout: a view of auxiliary local variables in continual learning. 281-323 - Konstantinos Kalpakis:
Consensus-relevance kNN and covariate shift mitigation. 325-353 - Yanzhe Bekkemoen:
Explainable reinforcement learning (XRL): a systematic literature review and taxonomy. 355-441 - Alex Beeson, Giovanni Montana:
Balancing policy constraint and ensemble size in uncertainty-based offline reinforcement learning. 443-488 - Anna Arutyunova, Anna Großwendt, Heiko Röglin, Melanie Schmidt, Julian Wargalla:
Upper and lower bounds for complete linkage in general metric spaces. 489-518
Volume 113, Number 2, February 2024
- Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant:
A general framework for the practical disintegration of PAC-Bayesian bounds. 519-604 - Cyprien Gilet, Marie Guyomard, Sébastien Destercke, Lionel Fillatre:
Softmin discrete minimax classifier for imbalanced classes and prior probability shifts. 605-645 - Charles A. Hepburn, Giovanni Montana:
Model-based trajectory stitching for improved behavioural cloning and its applications. 647-674 - Mohammadreza Qaraei, Rohit Babbar:
Meta-classifier free negative sampling for extreme multilabel classification. 675-697 - Xingjian Li, Di Hu, Xuhong Li, Haoyi Xiong, Cheng-Zhong Xu, Dejing Dou:
Towards accurate knowledge transfer via target-awareness representation disentanglement. 699-723 - Mike Huisman, Aske Plaat, Jan N. van Rijn:
Subspace Adaptation Prior for Few-Shot Learning. 725-752 - Christophe Denis, Mohamed Hebiri, Boris Ndjia Njike, Xavier Siebert:
Active learning algorithm through the lens of rejection arguments. 753-788 - Cheng-Der Fuh, Chuan-Ju Wang, Chen-Hung Pai:
Markov chain importance sampling for minibatches. 789-814 - Xiaotong Jiang, Xin Zhou, Michael R. Kosorok:
Deep doubly robust outcome weighted learning. 815-842 - John Pavlopoulos, Alv Romell, Jacob Curman, Olof Steinert, Tony Lindgren, Markus Borg, Korbinian Randl:
Automotive fault nowcasting with machine learning and natural language processing. 843-861 - René Heinrich, Christoph Scholz, Stephan Vogt, Malte Lehna:
Targeted adversarial attacks on wind power forecasts. 863-889 - Yuan Zhong, Wei Xu, Xin Gao:
Heterogeneous multi-task feature learning with mixed ℓ 2,1 regularization. 891-932 - Michael Lau, Tamara Schikowski, Holger Schwender:
logicDT: a procedure for identifying response-associated interactions between binary predictors. 933-992 - Vân Anh Huynh-Thu, Pierre Geurts:
Optimizing model-agnostic random subspace ensembles. 993-1042
Volume 113, Number 3, March 2024
- Théo Verhelst, Denis Mercier, Jeevan Shrestha, Gianluca Bontempi:
Partial counterfactual identification and uplift modeling: theoretical results and real-world assessment. 1043-1067 - Lingfei Ren, Ruimin Hu, Yang Liu, Dengshi Li, Junhang Wu, Yilong Zang, Wenyi Hu:
Improving fraud detection via imbalanced graph structure learning. 1069-1090 - Ashwin Srinivasan, A. Baskar, Tirtharaj Dash, Devanshu Shah:
Composition of relational features with an application to explaining black-box predictors. 1091-1132 - Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao:
Differentially private Riemannian optimization. 1133-1161 - Heon Song, Nariaki Mitsuo, Seiichi Uchida, Daiki Suehiro:
No regret sample selection with noisy labels. 1163-1188 - Raoul Heese, Moritz Wolter, Sascha Mücke, Lukas Franken, Nico Piatkowski:
On the effects of biased quantum random numbers on the initialization of artificial neural networks. 1189-1217 - Gayathri Girish, Deepak Mishra, Subrahamanian Moosath K. S.:
Utilising energy function and variational inference training for learning a graph neural network architecture. 1219-1241 - Zezeng Li, Shenghao Li, Lianbao Jin, Na Lei, Zhongxuan Luo:
OT-net: a reusable neural optimal transport solver. 1243-1268 - Thais Luca, Aline Paes, Gerson Zaverucha:
Word embeddings-based transfer learning for boosted relational dependency networks. 1269-1302 - Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli:
Explainable models via compression of tree ensembles. 1303-1328 - Matej Zecevic, Devendra Singh Dhami, Kristian Kersting:
Structural causal models reveal confounder bias in linear program modelling. 1329-1349 - Victor Verreet, Luc De Raedt, Jessa Bekker:
Modeling PU learning using probabilistic logic programming. 1351-1372 - Zhetong Dong, Hongwei Lin, Chi Zhou, Ben Zhang, Gengchen Li:
Persistence B-spline grids: stable vector representation of persistence diagrams based on data fitting. 1373-1420 - Ioannis Papantonis, Vaishak Belle:
Principled diverse counterfactuals in multilinear models. 1421-1443 - Evangelos Michelioudakis, Alexander Artikis, Georgios Paliouras:
Online semi-supervised learning of composite event rules by combining structure and mass-based predicate similarity. 1445-1481 - Clement Etienam, Kody J. H. Law, Sara Wade, Vitaly Zankin:
Fast deep mixtures of Gaussian process experts. 1483-1508 - Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu:
Correction to: Learning to bid and rank together in recommendation systems. 1509
Volume 113, Number 4, April 2024
- Shudong Zhang, Haichang Gao, Chao Shu, Xiwen Cao, Yunyi Zhou, Jianping He:
Black-box Bayesian adversarial attack with transferable priors. 1511-1528 - Zac Pullar-Strecker, Katharina Dost, Eibe Frank, Jörg Wicker:
Hitting the target: stopping active learning at the cost-based optimum. 1529-1547 - Xiang-Ru Yu, Deng-Bao Wang, Min-Ling Zhang:
Partial label learning with emerging new labels. 1549-1565 - Sambhav Jain, Reshma Rastogi:
Parametric non-parallel support vector machines for pattern classification. 1567-1594 - Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao:
Riemannian block SPD coupling manifold and its application to optimal transport. 1595-1622 - Yunyun Wang, Yao Liu, Songcan Chen:
Towards adaptive unknown authentication for universal domain adaptation by classifier paradox. 1623-1641 - Jie-Jing Shao, Xiaowen Yang, Lan-Zhe Guo:
Open-set learning under covariate shift. 1643-1659 - Chen Jia, Yue Zhang:
Meta-learning the invariant representation for domain generalization. 1661-1681 - Henry W. J. Reeve, Ata Kabán, Jakramate Bootkrajang:
Heterogeneous sets in dimensionality reduction and ensemble learning. 1683-1704 - Xiangyu Yin, Wenjie Ruan, Jonathan E. Fieldsend:
DIMBA: discretely masked black-box attack in single object tracking. 1705-1723 - Tong Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo:
Transfer and share: semi-supervised learning from long-tailed data. 1725-1742 - Tianxiang Qin, Shikui Tu, Lei Xu:
IA-NGM: A bidirectional learning method for neural graph matching with feature fusion. 1743-1769 - Ronghui Mu, Wenjie Ruan, Leandro Soriano Marcolino, Qiang Ni:
3DVerifier: efficient robustness verification for 3D point cloud models. 1771-1798 - Shonosuke Harada, Hisashi Kashima:
InfoCEVAE: treatment effect estimation with hidden confounding variables matching. 1799-1817 - Luofeng Liao, Li Shen, Jia Duan, Mladen Kolar, Dacheng Tao:
Local AdaGrad-type algorithm for stochastic convex-concave optimization. 1819-1838 - Peng Tan, Zhi-Hao Tan, Yuan Jiang, Zhi-Hua Zhou:
Towards enabling learnware to handle heterogeneous feature spaces. 1839-1860 - Lan Li, De-Chuan Zhan, Xin-Chun Li:
Aligning model outputs for class imbalanced non-IID federated learning. 1861-1884 - Guoxi Zhang, Hisashi Kashima:
Learning state importance for preference-based reinforcement learning. 1885-1901 - Jialiang Shen, Yu Yao, Shaoli Huang, Zhiyong Wang, Jing Zhang, Ruxing Wang, Jun Yu, Tongliang Liu:
ProtoSimi: label correction for fine-grained visual categorization. 1903-1920 - Suncheng Xiang, Hao Chen, Wei Ran, Zefang Yu, Ting Liu, Dahong Qian, Yuzhuo Fu:
Deep multimodal representation learning for generalizable person re-identification. 1921-1939 - Charles Moussa, Yash J. Patel, Vedran Dunjko, Thomas Bäck, Jan N. van Rijn:
Hyperparameter importance and optimization of quantum neural networks across small datasets. 1941-1966 - Iiro Kumpulainen, Nikolaj Tatti:
Dense subgraphs induced by edge labels. 1967-1987 - Niloofar Ranjbar, Saeedeh Momtazi, MohammadMehdi Homayoonpour:
Explaining recommendation system using counterfactual textual explanations. 1989-2012 - Michela Proietti, Alessio Ragno, Biagio La Rosa, Rino Ragno, Roberto Capobianco:
Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening. 2013-2044 - Valentina Arrigoni, Luisa Repele, Dario Marino Saccavino:
Textmatcher: cross-attentional neural network to compare image and text. 2045-2066 - Félix Iglesias Vázquez, Tanja Zseby:
Temporal silhouette: validation of stream clustering robust to concept drift. 2067-2091 - Ruidong Jin, Xin Liu, Tsuyoshi Murata:
Predicting potential real-time donations in YouTube live streaming services via continuous-time dynamic graphs. 2093-2127 - Thanh Duy Do, Thuan Dinh Nguyen, Viet Cuong Ta, Duong Tran Anh, Tuyet-Hanh Tran Thi, Diep Phan, Son T. Mai:
Dynamic weighted ensemble for diarrhoea incidence predictions. 2129-2152 - Elena Battaglia, Federico Peiretti, Ruggero G. Pensa:
Fast parameterless prototype-based co-clustering. 2153-2181 - Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas:
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. 2183-2205 - Manuel Dileo, Matteo Zignani, Sabrina Gaito:
Temporal graph learning for dynamic link prediction with text in online social networks. 2207-2226 - Alberto Berenguer, Jose-Norberto Mazón, David Tomás:
Word embeddings for retrieving tabular data from research publications. 2227-2248 - Bilal Abu-Salih, Mohammed Alweshah, Moutaz Alazab, Manaf Al-Okaily, Muteeb Alahmari, Mohammad Alhabashneh, Saleh H. Al-Sharaeh:
Natural language inference model for customer advocacy detection in online customer engagement. 2249-2275 - Vidyadhar Jinnappa Aski, Rugved Sanjay Chavan, Vijaypal Singh Dhaka, Geeta Rani, Ester Zumpano, Eugenio Vocaturo:
Forecasting of mobile network traffic and spatio-temporal analysis using modLSTM. 2277-2300
Volume 113, Number 5, May 2024
- Xingjun Ma, Linxi Jiang, Hanxun Huang, Zejia Weng, James Bailey, Yu-Gang Jiang:
Imbalanced gradients: a subtle cause of overestimated adversarial robustness. 2301-2326 - Wei Wei, Da Wang, Lin Li, Jiye Liang:
Re-attentive experience replay in off-policy reinforcement learning. 2327-2349 - Zayd Hammoudeh, Daniel Lowd:
Training data influence analysis and estimation: a survey. 2351-2403 - Carlos Pinzón, Catuscia Palamidessi, Pablo Piantanida, Frank Valencia:
On the incompatibility of accuracy and equal opportunity. 2405-2434 - Mianchu Wang, Yue Jin, Giovanni Montana:
Goal-conditioned offline reinforcement learning through state space partitioning. 2435-2465 - Taeyoung Kim, Myungjoo Kang:
Bounding the Rademacher complexity of Fourier neural operators. 2467-2498 - Mahum Naseer, Bharath Srinivas Prabakaran, Osman Hasan, Muhammad Shafique:
UnbiasedNets: a dataset diversification framework for robustness bias alleviation in neural networks. 2499-2526 - Lisheng Wu, Ke Chen:
Goal exploration augmentation via pre-trained skills for sparse-reward long-horizon goal-conditioned reinforcement learning. 2527-2557 - Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing Zhu:
Learning to bid and rank together in recommendation systems. 2559-2573 - Chenkang Zhang, Heng Huang, Bin Gu:
Tackle balancing constraints in semi-supervised ordinal regression. 2575-2595 - Aleksandr Dekhovich, David M. J. Tax, Marcel H. F. Sluiter, Miguel A. Bessa:
Neural network relief: a pruning algorithm based on neural activity. 2597-2618 - Tianyu Li, Doina Precup, Guillaume Rabusseau:
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning. 2619-2653 - Jenny Yang, Rasheed El-Bouri, Odhran O'Donoghue, Alexander S. Lachapelle, Andrew A. S. Soltan, David W. Eyre, Lei Lu, David A. Clifton:
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare. 2655-2674 - Ramij Raja Hossain, Tianzhixi Yin, Yan Du, Renke Huang, Jie Tan, Wenhao Yu, Yuan Liu, Qiuhua Huang:
Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning. 2675-2700 - Antonio Candelieri, Andrea Ponti, Francesco Archetti:
Fair and green hyperparameter optimization via multi-objective and multiple information source Bayesian optimization. 2701-2731 - Kaito Ariu, Jungseul Ok, Alexandre Proutière, Seyoung Yun:
Optimal clustering from noisy binary feedback. 2733-2764 - Feliu Serra-Burriel, Pedro Delicado, Fernando M. Cucchietti, Eduardo Graells-Garrido, Alex Gil, Imanol Eguskiza Martínez:
When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days. 2765-2794 - Xiao-Yang Liu, Ziyi Xia, Hongyang Yang, Jiechao Gao, Daochen Zha, Ming Zhu, Christina Dan Wang, Zhaoran Wang, Jian Guo:
Dynamic datasets and market environments for financial reinforcement learning. 2795-2839 - Denis Béchet, Annie Foret:
Incremental learning of iterated dependencies. 2841-2875 - Gail Weiss, Yoav Goldberg, Eran Yahav:
Extracting automata from recurrent neural networks using queries and counterexamples (extended version). 2877-2919 - Haoxi Zhan, Xiaobing Pei:
Dealing with the unevenness: deeper insights in graph-based attack and defense. 2921-2953 - Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Federated learning with superquantile aggregation for heterogeneous data. 2955-3022 - Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, J. Q. Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill:
Reinforcement learning tutor better supported lower performers in a math task. 3023-3048 - Pavlos Athanasios Apostolopoulos, Zehui Wang, Hanson Wang, Tenghyu Xu, Chad Zhou, Kittipat Virochsiri, Norm Zhou, Igor L. Markov:
Personalization for web-based services using offline reinforcement learning. 3049-3071 - Kilian Hendrickx, Lorenzo Perini, Dries Van der Plas, Wannes Meert, Jesse Davis:
Machine learning with a reject option: a survey. 3073-3110 - Sofie Goethals, David Martens, Toon Calders:
PreCoF: counterfactual explanations for fairness. 3111-3142 - Weronika Hryniewska, Adrianna Grudzien, Przemyslaw Biecek:
LIMEcraft: handcrafted superpixel selection and inspection for Visual eXplanations. 3143-3160 - Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer:
Wasserstein dropout. 3161-3204 - Clément Benesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin:
Fairness seen as global sensitivity analysis. 3205-3232 - Rémi Eyraud, Stéphane Ayache:
Distillation of weighted automata from recurrent neural networks using a spectral approach. 3233-3266 - Chihiro Shibata:
Learning (k,l)-context-sensitive probabilistic grammars with nonparametric Bayesian approach. 3267-3301 - Lukasz Korycki, Bartosz Krawczyk:
Correction: Adversarial concept drift detection under poisoning attacks for robust data stream mining. 3303-3304 - António Pereira Barata, Frank W. Takes, H. Jaap van den Herik, Cor J. Veenman:
Fair tree classifier using strong demographic parity. 3305-3324 - Nuwan Gunasekara, Bernhard Pfahringer, Heitor Murilo Gomes, Albert Bifet:
Gradient boosted trees for evolving data streams. 3325-3352 - Yogesh Bansal, David Lillis, M. Tahar Kechadi:
Correction to: A neural meta-model for predicting winter wheat crop yield. 3353 - Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry:
Correction to: Multi-agent reinforcement learning for fast-timescale demand response of residential loads. 3355
Volume 113, Number 6, June 2024
- Hao-Yuan He, Wang-Zhou Dai, Ming Li:
Reduced implication-bias logic loss for neuro-symbolic learning. 3357-3377 - Malte Nalenz, Julian Rodemann, Thomas Augustin:
Learning de-biased regression trees and forests from complex samples. 3379-3398 - Baowen Xu, Xuelei Wang, Jingwei Li, Chengbao Liu:
Hierarchical U-net with re-parameterization technique for spatio-temporal weather forecasting. 3399-3417 - Abolhassan Banisheikholeslami, Farhad Qaderi:
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity. 3419-3441 - Wenlan Kuang, Zhixin Li:
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation. 3443-3461 - Senlin Shu, Haobo Wang, Zhuowei Wang, Bo Han, Tao Xiang, Bo An, Lei Feng:
Online binary classification from similar and dissimilar data. 3463-3484 - Zhiyu Jin, Xuli Shen, Bin Li, Xiangyang Xue:
Style spectroscope: improve interpretability and controllability through Fourier analysis. 3485-3503 - Tonglin Chen, Zhimeng Shen, Bin Li, Xiangyang Xue:
Compositional scene modeling with global object-centric representations. 3505-3524 - Sándor Szedmák, Riikka Huusari, Tat Hong Duong Le, Juho Rousu:
Scalable variable selection for two-view learning tasks with projection operators. 3525-3544 - Yi-Xiao He, Yu-Chang Wu, Chao Qian, Zhi-Hua Zhou:
Margin distribution and structural diversity guided ensemble pruning. 3545-3567 - Cameron R. Wolfe, Anastasios Kyrillidis:
Better schedules for low precision training of deep neural networks. 3569-3587 - Zhen Chen, Fu Wang, Ronghui Mu, Peipei Xu, Xiaowei Huang, Wenjie Ruan:
Nrat: towards adversarial training with inherent label noise. 3589-3610 - Yuntao Du, Haiyang Yang, Mingcai Chen, Hongtao Luo, Juan Jiang, Yi Xin, Chongjun Wang:
Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation. 3611-3631 - Sascha Marton, Stefan Lüdtke, Christian Bartelt, Andrej Tschalzev, Heiner Stuckenschmidt:
Explaining neural networks without access to training data. 3633-3652 - Tian Qin, Long-Fei Li, Tian-Zuo Wang, Zhi-Hua Zhou:
Tracking treatment effect heterogeneity in evolving environments. 3653-3673 - Fedor Buzaev, Jiexing Gao, Ivan Chuprov, Evgeniy Kazakov:
Hybrid acceleration techniques for the physics-informed neural networks: a comparative analysis. 3675-3692 - Ralf Riedel, Aviv Segev:
Neural network structure simplification by assessing evolution in node weight magnitude. 3693-3710 - Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
Sanitized clustering against confounding bias. 3711-3730 - Zhongzhen Wang, Petros Dellaportas, Ioannis Kosmidis:
Bayesian tensor factorisations for time series of counts. 3731-3750 - Damien Dablain, Colin Bellinger, Bartosz Krawczyk, David W. Aha, Nitesh V. Chawla:
Understanding imbalanced data: XAI & interpretable ML framework. 3751-3769 - Yogesh Bansal, David Lillis, M. Tahar Kechadi:
A neural meta model for predicting winter wheat crop yield. 3771-3788 - Feng Yan, Zhe Li, Wushour Silamu, Yanbing Li:
Knowledge-aware image understanding with multi-level visual representation enhancement for visual question answering. 3789-3805 - Haiyang Yu, Jingye Chen, Bin Li, Xiangyang Xue:
Chinese character recognition with radical-structured stroke trees. 3807-3827 - Mai Liu, Jichao Jiao, Ning Li, Min Pang:
Task-decoupled interactive embedding network for object detection. 3829-3848 - Fei Zhang, Yunjie Ye, Lei Feng, Zhongwen Rao, Jieming Zhu, Marcus Kalander, Chen Gong, Jianye Hao, Bo Han:
Exploiting counter-examples for active learning with partial labels. 3849-3868 - Mao Zhang, Tie Zhang, Yifei Cheng, Changcun Bao, Haoyu Cao, Deqiang Jiang, Linli Xu:
Communication-efficient clustered federated learning via model distance. 3869-3888
Volume 113, Number 8, July 2024
- Wenya Shi, Gang Wu:
New algorithms for trace-ratio problem with application to high-dimension and large-sample data dimensionality reduction. 3889-3916 - Tim Verdonck, Bart Baesens, María Óskarsdóttir, Seppe vanden Broucke:
Special issue on feature engineering editorial. 3917-3928 - Rui-Ray Zhang, Massih-Reza Amini:
Generalization bounds for learning under graph-dependence: a survey. 3929-3959 - Susobhan Ghosh, Raphael Kim, Prasidh Chhabria, Raaz Dwivedi, Predrag Klasnja, Peng Liao, Kelly W. Zhang, Susan A. Murphy:
Did we personalize? Assessing personalization by an online reinforcement learning algorithm using resampling. 3961-3997 - Keheng Wang, Chuantao Yin, Rumei Li, Sirui Wang, Yunsen Xian, Wenge Rong, Zhang Xiong:
TOCOL: improving contextual representation of pre-trained language models via token-level contrastive learning. 3999-4012 - Spyros Theodoropoulos, Patrik Zajec, Joze M. Rozanec, Dimosthenis Kyriazis, Panayiotis Tsanakas:
On-the-fly image-level oversampling for imbalanced datasets of manufacturing defects. 4013-4035 - Haiting Sun, Peng Tian, Yun Xiong, Yao Zhang, Yali Xiang, Xing Jia, Haofen Wang:
DynamiSE: dynamic signed network embedding for link prediction. 4037-4053 - Beatriz Flamia Azevedo, Ana Maria A. C. Rocha, Ana I. Pereira:
Hybrid approaches to optimization and machine learning methods: a systematic literature review. 4055-4097 - Songwen Pei, Jiyao Wang, Bingxue Zhang, Wei Qin, Hai Xue, Xiaochun Ye, Mingsong Chen:
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network. 4099-4112 - Mike Huisman, Aske Plaat, Jan N. van Rijn:
Understanding transfer learning and gradient-based meta-learning techniques. 4113-4132 - Xiaodong Wang, Fushing Hsieh:
An encoding approach for stable change point detection. 4133-4163 - Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano:
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework. 4165-4243 - Yanou Ramon, David Martens, Theodoros Evgeniou, Stiene Praet:
Can metafeatures help improve explanations of prediction models when using behavioral and textual data? 4245-4284 - Tran Thi Hong Hanh, Matej Martinc, Andraz Repar, Nikola Ljubesic, Antoine Doucet, Senja Pollak:
Can cross-domain term extraction benefit from cross-lingual transfer and nested term labeling? 4285-4314 - Kejie Tang, Weidong Liu, Xiaojun Mao:
Multi-consensus decentralized primal-dual fixed point algorithm for distributed learning. 4315-4357 - Emad Kebriaei, Ali Homayouni, Roghayeh Faraji, Armita Razavi, Azadeh Shakery, Heshaam Faili, Yadollah Yaghoobzadeh:
Persian offensive language detection. 4359-4379 - Arnaud Bougaham, Mohammed El Adoui, Isabelle Linden, Benoît Frénay:
Composite score for anomaly detection in imbalanced real-world industrial dataset. 4381-4406 - Zhong Chen, Victor S. Sheng, Andrea Edwards, Kun Zhang:
Cost-sensitive sparse group online learning for imbalanced data streams. 4407-4444 - Paolo Mignone, Roberto Corizzo, Michelangelo Ceci:
Distributed and explainable GHSOM for anomaly detection in sensor networks. 4445-4486 - Jaromír Janisch, Tomás Pevný, Viliam Lisý:
Classification with costly features in hierarchical deep sets. 4487-4522 - Vítor Cerqueira, Nuno Moniz, Carlos Soares:
VEST: automatic feature engineering for forecasting. 4523-4545 - Carlos Ortega Vázquez, Seppe vanden Broucke, Jochen De Weerdt:
Hellinger distance decision trees for PU learning in imbalanced data sets. 4547-4578 - Andreas C. Bueff, Vaishak Belle:
Learning explanatory logical rules in non-linear domains: a neuro-symbolic approach. 4579-4614 - Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal, Benedita Malheiro, Juan-Carlos Burguillo:
Exposing and explaining fake news on-the-fly. 4615-4637 - Zhendong Wang, Isak Samsten, Ioanna Miliou, Rami Mochaourab, Panagiotis Papapetrou:
Glacier: guided locally constrained counterfactual explanations for time series classification. 4639-4669 - Chun Wai Chiu, Leandro L. Minku:
Smoclust: synthetic minority oversampling based on stream clustering for evolving data streams. 4671-4721 - Özge Sürer, Daniel W. Apley, Edward C. Malthouse:
Coefficient tree regression: fast, accurate and interpretable predictive modeling. 4723-4759 - Ekaterina Loginova, Wai Kit Tsang, Guus van Heijningen, Louis-Philippe Kerkhove, Dries F. Benoit:
Forecasting directional bitcoin price returns using aspect-based sentiment analysis on online text data. 4761-4784 - Damien Dablain, Kristen N. Jacobson, Colin Bellinger, Mark Roberts, Nitesh V. Chawla:
Understanding CNN fragility when learning with imbalanced data. 4785-4810 - Hampus Gummesson Svensson, Christian Tyrchan, Ola Engkvist, Morteza Haghir Chehreghani:
Utilizing reinforcement learning for de novo drug design. 4811-4843 - Kushankur Ghosh, Colin Bellinger, Roberto Corizzo, Paula Branco, Bartosz Krawczyk, Nathalie Japkowicz:
The class imbalance problem in deep learning. 4845-4901 - Dina Elreedy, Amir F. Atiya, Firuz Kamalov:
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning. 4903-4923 - Katarzyna Woznica, Mateusz Grzyb, Zuzanna Trafas, Przemyslaw Biecek:
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks. 4925-4949 - Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin:
Correction: Learning sample-aware threshold for semi-supervised learning. 4951 - Jakob Raymaekers, Peter J. Rousseeuw:
Transforming variables to central normality. 4953-4975 - Emrah Hancer:
An improved evolutionary wrapper-filter feature selection approach with a new initialisation scheme. 4977-5000 - Arne De Brabandere, Tim Op De Beéck, Kilian Hendrickx, Wannes Meert, Jesse Davis:
TSFuse: automated feature construction for multiple time series data. 5001-5056 - Qian Gui, Hong Zhou, Na Guo, Baoning Niu:
A survey of class-imbalanced semi-supervised learning. 5057-5086 - Petros Boulieris, John Pavlopoulos, Alexandros Xenos, Vasilis Vassalos:
Fraud detection with natural language processing. 5087-5108 - Sauptik Dhar, Bernardo Gonzalez Torres:
DOC3: deep one class classification using contradictions. 5109-5150 - Muhammad Kamran Janjua, Haseeb Shah, Martha White, Erfan Miahi, Marlos C. Machado, Adam White:
GVFs in the real world: making predictions online for water treatment. 5151-5181 - Iwo Naglik, Mateusz Lango:
GMMSampling: a new model-based, data difficulty-driven resampling method for multi-class imbalanced data. 5183-5202 - Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry:
Multi-agent reinforcement learning for fast-timescale demand response of residential loads. 5203-5234 - Hao Mei, Xiaoliang Lei, Longchao Da, Bin Shi, Hua Wei:
Libsignal: an open library for traffic signal control. 5235-5271 - Salvatore Lusito, Andrea Pugnana, Riccardo Guidotti:
Solving imbalanced learning with outlier detection and features reduction. 5273-5330 - Yuchen Li, Haoyi Xiong, Linghe Kong, Jiang Bian, Shuaiqiang Wang, Guihai Chen, Dawei Yin:
GS2P: a generative pre-trained learning to rank model with over-parameterization for web-scale search. 5331-5349 - Xinzhi Wang, Nengjun Zhu, Jiahao Li, Yudong Chang, Zhennan Li:
Entity recognition based on heterogeneous graph reasoning of visual region and text candidate. 5351-5378 - Malik Al-Essa, Giuseppina Andresini, Annalisa Appice, Donato Malerba:
PANACEA: a neural model ensemble for cyber-threat detection. 5379-5422 - Qi Wei, Lei Feng, Haoliang Sun, Ren Wang, Rundong He, Yilong Yin:
Learning sample-aware threshold for semi-supervised learning. 5423-5445 - V. Adarsh, G. R. Gangadharan:
Mental stress detection from ultra-short heart rate variability using explainable graph convolutional network with network pruning and quantisation. 5467-5494 - Rasoul Kiani, Wei Jin, Victor S. Sheng:
Survey on extreme learning machines for outlier detection. 5495-5531 - Jean-Gabriel Gaudreault, Paula Branco:
Empirical analysis of performance assessment for imbalanced classification. 5533-5575 - Wei Liang, Derui Ding, Hui Yu:
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker. 5577-5600 - Yunsheng Xue, Mi Wen, Wei He, Weiwei Li:
DPG: a model to build feature subspace against adversarial patch attack. 5601-5622 - Chamalee Wickrama Arachchi, Nikolaj Tatti:
Recurrent segmentation meets block models in temporal networks. 5623-5653 - Michela Quadrini, Antonino Capuccio, Denise Falcone, Sebastian Daberdaku, Alessandro Blanda, Luca Bellanova, Gianluca Gerard:
Stress detection with encoding physiological signals and convolutional neural network. 5655-5683 - Ata Kabán, Henry W. J. Reeve:
Structure discovery in PAC-learning by random projections. 5685-5730 - Alejandro Kuratomi, Ioanna Miliou, Zed Lee, Tony Lindgren, Panagiotis Papapetrou:
Ijuice: integer JUstIfied counterfactual explanations. 5731-5771 - Janet Oluwasola Bolorunduro, Zhaonian Zou, Mohamed Jaward Bah:
An effective keyword search co-occurrence multi-layer graph mining approach. 5773-5806 - Tomás Gutierrez, Davi Valladão, Bernardo K. Pagnoncelli:
PolieDRO: a novel classification and regression framework with non-parametric data-driven regularization. 5807-5846 - Claire Glanois, Paul Weng, Matthieu Zimmer, Dong Li, Tianpei Yang, Jianye Hao, Wulong Liu:
A survey on interpretable reinforcement learning. 5847-5890 - Shaofeng H.-C. Jiang, Robert Krauthgamer, Jianing Lou, Yubo Zhang:
Coresets for kernel clustering. 5891-5906
Volume 113, Number 9, September 2024
- Mingze Ni, Zhensu Sun, Wei Liu:
Reversible jump attack to textual classifiers with modification reduction. 5907-5937 - Hana Sebia, Thomas Guyet, Etienne Audureau:
SWoTTeD: an extension of tensor decomposition to temporal phenotyping. 5939-5980 - Yue Wang, Yi Zhou, Shaofeng Zou:
Finite-time error bounds for Greedy-GQ. 5981-6018 - Arne Gevaert, Axel-Jan Rousseau, Thijs Becker, Dirk Valkenborg, Tijl De Bie, Yvan Saeys:
Evaluating feature attribution methods in the image domain. 6019-6064 - Emirhan Ilhan, Ahmet B. Koc, Suleyman S. Kozat:
Exploiting residual errors in nonlinear online prediction. 6065-6091 - Tomoharu Iwata, Yoichi Chikahara:
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers. 6093-6114 - Kei Ota, Devesh K. Jha, Asako Kanezaki:
A framework for training larger networks for deep Reinforcement learning. 6115-6139 - Pedro P. Santos, Diogo S. Carvalho, Alberto Sardinha, Francisco S. Melo:
The impact of data distribution on Q-learning with function approximation. 6141-6163 - Ofir Moshe, Gil Fidel, Ron Bitton, Asaf Shabtai:
Improving interpretability via regularization of neural activation sensitivity. 6165-6196 - Deliang Yang, Hou-Duo Qi:
Supervised maximum variance unfolding. 6197-6226 - Marco Markwald, Elena Demidova:
REFUEL: rule extraction for imbalanced neural node classification. 6227-6246 - Hanrui Wu, Yanxin Wu, Nuosi Li, Min Yang, Jia Zhang, Michael K. Ng, Jinyi Long:
High-order proximity and relation analysis for cross-network heterogeneous node classification. 6247-6272 - Omer Hofman, Amit Giloni, Yarin Hayun, Ikuya Morikawa, Toshiya Shimizu, Yuval Elovici, Asaf Shabtai:
X-Detect: explainable adversarial patch detection for object detectors in retail. 6273-6292 - Wenhao Shu, Dongtao Cao, Wenbin Qian, Shipeng Li:
Neighborhood relation-based incremental label propagation algorithm for partially labeled hybrid data. 6293-6339 - Yunting Zhang, Shang Li, Lin Ye, Hongli Zhang, Zhe Chen, Binxing Fang:
Kalt: generating adversarial explainable chinese legal texts. 6341-6371 - Andrea Basteri, Dario Trevisan:
Quantitative Gaussian approximation of randomly initialized deep neural networks. 6373-6393 - Manuel Dileo, Matteo Zignani:
Discrete-time graph neural networks for transaction prediction in Web3 social platforms. 6395-6412 - Ganyu Wang, Qingsong Zhang, Xiang Li, Boyu Wang, Bin Gu, Charles X. Ling:
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization. 6413-6451 - Arthur Hoarau, Vincent Lemaire, Yolande Le Gall, Jean-Christophe Dubois, Arnaud Martin:
Evidential uncertainty sampling strategies for active learning. 6453-6474 - Gabor Paczolay, Matteo Papini, Alberto Maria Metelli, István Á. Harmati, Marcello Restelli:
Sample complexity of variance-reduced policy gradient: weaker assumptions and lower bounds. 6475-6510 - Yinghua Yao, Yuangang Pan, Jing Li, Ivor W. Tsang, Xin Yao:
PROUD: PaRetO-gUided diffusion model for multi-objective generation. 6511-6538 - Joe Germino, Nuno Moniz, Nitesh V. Chawla:
FairMOE: counterfactually-fair mixture of experts with levels of interpretability. 6539-6559 - Jakob Raymaekers, Peter J. Rousseeuw, Tim Verdonck, Ruicong Yao:
Fast linear model trees by PILOT. 6561-6610 - Francesco Gullo, Domenico Mandaglio, Andrea Tagarelli:
Neural discovery of balance-aware polarized communities. 6611-6644 - Alberto Carlevaro, Teodoro Alamo, Fabrizio Dabbene, Maurizio Mongelli:
Conformal predictions for probabilistically robust scalable machine learning classification. 6645-6661 - Jiachen Lyu, Katharina Dost, Yun Sing Koh, Jörg Wicker:
Regional bias in monolingual English language models. 6663-6696 - Dai Hai Nguyen, Tetsuya Sakurai:
Moreau-Yoshida variational transport: a general framework for solving regularized distributional optimization problems. 6697-6724 - Dimitris Bertsimas, Nicholas A. G. Johnson:
Compressed sensing: a discrete optimization approach. 6725-6764 - John Pavlopoulos, Maria Konstantinidou, Elpida Perdiki, Isabelle Marthot-Santaniello, Holger Essler, Georgios Vardakas, Aristidis Likas:
Explainable dating of greek papyri images. 6765-6786 - Giuseppe Serra, Mathias Niepert:
L2XGNN: learning to explain graph neural networks. 6787-6809 - Tuan T. Nguyen, Hoang H. Nguyen, Mina Sartipi, Marco Fisichella:
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios. 6811-6837 - Roberto Esposito, Mattia Cerrato, Marco Locatelli:
Partitioned least squares. 6839-6869 - Benedict Clark, Rick Wilming, Stefan Haufe:
XAI-TRIS: non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance. 6871-6910 - Charalambos Eliades, Harris Papadopoulos:
ICM ensemble with novel betting functions for concept drift. 6911-6944 - Elia Peruzzo, Enver Sangineto, Yahui Liu, Marco De Nadai, Wei Bi, Bruno Lepri, Nicu Sebe:
Spatial entropy as an inductive bias for vision transformers. 6945-6975 - Jesse Davis, Lotte Bransen, Laurens Devos, Arne Jaspers, Wannes Meert, Pieter Robberechts, Jan Van Haaren, Maaike Van Roy:
Methodology and evaluation in sports analytics: challenges, approaches, and lessons learned. 6977-7010 - Ambarish Moharil, Joaquin Vanschoren, Prabhant Singh, Damian A. Tamburri:
Towards efficient AutoML: a pipeline synthesis approach leveraging pre-trained transformers for multimodal data. 7011-7053 - Victor Dheur, Tanguy Bosser, Rafael Izbicki, Souhaib Ben Taieb:
Distribution-free conformal joint prediction regions for neural marked temporal point processes. 7055-7102 - Chamalee Wickrama Arachchi, Nikolaj Tatti:
Jaccard-constrained dense subgraph discovery. 7103-7125 - Lucas P. Damasceno, Egzona Rexhepi, Allison Shafer, Ian Whitehouse, Nathalie Japkowicz, Charles C. Cavalcante, Roberto Corizzo, Zois Boukouvalas:
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events. 7127-7128
Volume 113, Number 10, October 2024
- Mark Kiermayer, Christian Weiß:
Neural calibration of hidden inhomogeneous Markov chains: information decompression in life insurance. 7129-7156 - Victoria Manfredi, Alicia P. Wolfe, Xiaolan Zhang, Bing Wang:
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency. 7157-7193 - Ludwig Lausser, Robin Szekely, Hans A. Kestler:
Permutation-invariant linear classifiers. 7195-7221 - Le Zhang, Qibin Hou, Yun Liu, Jia-Wang Bian, Xun Xu, Joey Tianyi Zhou, Ce Zhu:
Deep negative correlation classification. 7223-7241 - Margherita Gambini, Caterina Senette, Tiziano Fagni, Maurizio Tesconi:
Evaluating large language models for user stance detection on X (Twitter). 7243-7266 - Gokul Bhusal, Ekaterina Merkurjev, Guo-Wei Wei:
Persistent Laplacian-enhanced algorithm for scarcely labeled data classification. 7267-7292 - Rogério Ribeiro, Athos Moraes, Marta Moreno, Pedro G. Ferreira:
Integration of multi-modal datasets to estimate human aging. 7293-7317 - Soogeun Park, Eva Ceulemans, Katrijn Van Deun:
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression. 7319-7370 - Zhi-Lin Zhao, Longbing Cao:
Weighting non-IID batches for out-of-distribution detection. 7371-7391 - Pegah Rahimian, Balazs Mark Mihalyi, László Toka:
In-game soccer outcome prediction with offline reinforcement learning. 7393-7419 - Michal Koziarski, Michal Wozniak:
Local neighborhood encodings for imbalanced data classification. 7421-7449 - Eric F. Lock:
Empirical Bayes linked matrix decomposition. 7451-7477 - Albert Nössig, Tobias Hell, Georg Moser:
Rule learning by modularity. 7479-7508 - Duo Xu, Faramarz Fekri:
Generalization of temporal logic tasks via future dependent options. 7509-7540 - Calvin Yeung, Rory P. Bunker, Rikuhei Umemoto, Keisuke Fujii:
Evaluating soccer match prediction models: a deep learning approach and feature optimization for gradient-boosted trees. 7541-7564 - Fabrizio Angiulli, Fabio Fassetti, Simona Nisticò, Luigi Palopoli:
Explaining outliers and anomalous groups via subspace density contrastive loss. 7565-7589 - Andrea Failla, Rémy Cazabet, Giulio Rossetti, Salvatore Citraro:
Describing group evolution in temporal data using multi-faceted events. 7591-7615 - Ekaterina Antonenko, Ander Carreño, Jesse Read:
Autoreplicative random forests with applications to missing value imputation. 7617-7643 - Yunzhe Zhou, Peiru Xu, Giles Hooker:
A generic approach for reproducible model distillation. 7645-7688 - Nina Omejc, Bostjan Gec, Jure Brence, Ljupco Todorovski, Saso Dzeroski:
Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data. 7689-7721 - Andrea Fedele, Riccardo Guidotti, Dino Pedreschi:
Explaining Siamese networks in few-shot learning. 7723-7760 - Youcheng Qian, Xueyan Yin:
Semantic-enhanced graph neural networks with global context representation. 7761-7781 - Laura Maria Palomino Mariño, Francisco de Assis Tenório de Carvalho:
Self-organizing maps with adaptive distances for multiple dissimilarity matrices. 7783-7806 - Lee-Ad Gottlieb, Eran Kaufman, Aryeh Kontorovich, Gabriel Nivasch, Ofir Pele:
Nested barycentric coordinate system as an explicit feature map for polyhedra approximation and learning tasks. 7807-7840 - Solène Vilfroy, Lionel Bombrun, Thierry Urruty, Florence de Grancey, Jean-Philippe Lebrat, Philippe Carré:
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver. 7841-7866 - Yidi Bai, Hengjian Cui:
A class sensitivity feature guided T-type generative model for noisy label classification. 7867-7904 - Keqing Cen, Zhenghao Yang, Ze Wang, Minhong Dong:
A cross-domain user association scheme based on graph attention networks with trajectory embedding. 7905-7930 - Joanna Komorniczak, Pawel Ksieniewicz:
On metafeatures' ability of implicit concept identification. 7931-7966 - Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub, Konstantinos G. Papakonstantinou, Eleni N. Chatzi:
POMDP inference and robust solution via deep reinforcement learning: an application to railway optimal maintenance. 7967-7995 - Xavier Renard, Thibault Laugel, Marcin Detyniecki:
Understanding prediction discrepancies in classification. 7997-8026 - Sankhadeep Chatterjee, Saranya Bhattacharjee, Asit Kumar Das, Soumen Banerjee:
Imbalanced COVID-19 vaccine sentiment classification with synthetic resampling coupled deep adversarial active learning. 8027-8059 - Andreas Lohrer, Daniyal Kazempour, Maximilian Hünemörder, Peer Kröger:
CoMadOut - a robust outlier detection algorithm based on CoMAD. 8061-8135 - Kamil Faber, Dominik Zurek, Marcin Pietron, Nathalie Japkowicz, Antonio Vergari, Roberto Corizzo:
From MNIST to ImageNet and back: benchmarking continual curriculum learning. 8137-8164 - Daniel Berrar, Philippe Lopes, Werner Dubitzky:
A data- and knowledge-driven framework for developing machine learning models to predict soccer match outcomes. 8165-8204 - Yuxuan Wang, Ross D. King:
Extrapolation is not the same as interpolation. 8205-8232 - Yeasung Jeong, Kangbok Lee, Young Woong Park, Sumin Han:
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting. 8233-8299
Volume 113, Number 11, December 2024
- Florentin Coeurdoux, Nicolas Dobigeon, Pierre Chainais:
Normalizing flow sampling with Langevin dynamics in the latent space. 8301-8326 - Satoshi Hara, Mitsuru Matsuura, Junya Honda, Shinji Ito:
Active model selection: A variance minimization approach. 8327-8345 - Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus:
Adjusting regression models for conditional uncertainty calibration. 8347-8370 - Felix Mohr, Jan N. van Rijn:
Learning curves for decision making in supervised machine learning: a survey. 8371-8425 - Xiao Guo, Xiang Li, Xiangyu Chang, Shusen Wang, Zhihua Zhang:
Fedpower: privacy-preserving distributed eigenspace estimation. 8427-8458 - Mingzhen He, Fan He, Fanghui Liu, Xiaolin Huang:
Random fourier features for asymmetric kernels. 8459-8485 - Chenhan Jin, Kaiwen Zhou, Bo Han, James Cheng, Tieyong Zeng:
Efficient private SCO for heavy-tailed data via averaged clipping. 8487-8532 - Hikaru Shindo, Viktor Pfanschilling, Devendra Singh Dhami, Kristian Kersting:
Learning differentiable logic programs for abstract visual reasoning. 8533-8584 - Bozhidar Stevanoski, Ana Kostovska, Pance Panov, Saso Dzeroski:
Change detection and adaptation in multi-target regression on data streams. 8585-8622 - Myrto Limnios, Nathan Noiry, Stéphan Clémençon:
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics. 8623-8653 - Eliot Tron, Nicolas Couëllan, Stéphane Puechmorel:
Adversarial attacks on neural networks through canonical Riemannian foliations. 8655-8686 - Tiago Mendes-Neves, Luís Meireles, João Mendes-Moreira:
Towards a foundation large events model for soccer. 8687-8709 - Xiao Liu, Weidong Liu, Xiaojun Mao:
Efficient and provable online reduced rank regression via online gradient descent. 8711-8748 - Thao Thi Phuong Dao, Tan-Cong Nguyen, Viet-Tham Huynh, Xuan-Hai Bui, Trung-Nghia Le, Minh-Triet Tran:
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics. 8749-8767 - Gail Weiss, Yoav Goldberg, Eran Yahav:
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version). 8769
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