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ORCIDMachine Learning, Volume 114
Volume 114, Number 1, January 2025
- Yael Hochma, Mark Last:
Fast online feature selection in streaming data. 1 - Javier García-Sigüenza
, Manuel Curado, Faraón Llorens-Largo, Jose F. Vicent:
Self explainable graph convolutional recurrent network for spatio-temporal forecasting. 2 - Sehwan Moon, Hyunju Lee:
Deep metric loss for multimodal learning. 3 - Domen Soberl, Ivan Bratko:
Qualitative control learning can be much faster than reinforcement learning. 4 - Yuxin He, Weihang Hong, Lishuai Li, Jinlei Zhang, Jin Qin, Qin Luo:
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro. 5 - Zifan Peng, Mingchen Li, Yue Wang, Daniel Y. Mo:
Prompt-based contrastive learning to combat the COVID-19 infodemic. 6 - The Tien Mai:
Concentration properties of fractional posterior in 1-bit matrix completion. 7 - Oscar Blessed Deho, Michael Bewong, Selasi Kwashie, Jiuyong Li, Jixue Liu, Lin Liu, Srecko Joksimovic:
Is it still fair? A comparative evaluation of fairness algorithms through the lens of covariate drift. 8 - Colin Beam:
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics. 9 - Jiacheng Ruan, Jingsheng Gao, Mingye Xie, Suncheng Xiang:
Learning multi-axis representation in frequency domain for medical image segmentation. 10 - Kuan-An Su, YiHao Su, Yun-Hsuan Lien, Yu-Shuen Wang:
Let the noise flow away: combating noisy labels using normalizing flows. 11 - Jin-Young Kim, Soonwoo Kwon, Hyojun Go, Yunsung Lee, Seungtaek Choi, Hyun-Gyoon Kim:
ScoreCL: augmentation-adaptive contrastive learning via score-matching function. 12 - Riccardo Cantini, Cristian Cosentino, Irene Kilanioti, Fabrizio Marozzo, Domenico Talia:
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media. 13 - Xiao Liu, Jun-Jie Huang, Wentao Zhao, Ziyue Wang, Zihan Chen, Yi Pan:
SPA: A poisoning attack framework for graph neural networks through searching and pairing. 14 - Li Wang, Wei Huang:
On the convergence analysis of over-parameterized variational autoencoders: a neural tangent kernel perspective. 15 - Wei-Yao Wang, Wei-Wei Du, Derek Xu, Wei Wang, Wen-Chih Peng:
A survey on self-supervised learning for non-sequential tabular data. 16 - Trung-Hoang Le, Hady W. Lauw:
Learning to rank aspects and opinions for comparative explanations. 17 - The Tien Mai:
Misclassification bounds for PAC-Bayesian sparse deep learning. 18 - Vu-Linh Nguyen, Haifei Zhang, Sébastien Destercke:
Credal ensembling in multi-class classification. 19 - Bram Janssens, Matthias Bogaert:
PerfoRank: cluster-based performance ranking for improved performance evaluation and estimation in professional cycling. 20 - Arun Kumar Sivapuram, Komuravelli Prashanth, Rama Krishna Sai S. Gorthi:
SA-LfV: self-annotated labeling from videos for object detection. 21 - Mouad Elaarabi, Domenico Borzacchiello, Philippe Le Bot, Yves Le Guennec, Sebastien Comas-Cardona:
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks. 22 - Xiaofeng Lin, Han Bao, Yan Cui, Koh Takeuchi, Hisashi Kashima:
Scalable individual treatment effect estimator for large graphs. 23 - Zitao Liu, Ying Zheng, Zhibo Yin, Jiahao Chen, Tianqiao Liu, Mi Tian, Weiqi Luo:
ArithmeticGPT: empowering small-size large language models with advanced arithmetic skills. 24 - Ayush K. Varshney, Vicenç Torra:
Efficient federated unlearning under plausible deniability. 25 - Xiaochen Zhang, Yunfeng Cai, Haoyi Xiong:
Knoop: practical enhancement of knockoff with over-parameterization for variable selection. 26 - Alberto García-Galindo, Marcos Lopez-De-Castro, Rubén Armañanzas:
Fair prediction sets through multi-objective hyperparameter optimization. 27
Volume 114, Number 2, February 2025
- Le Zhang, Qibin Hou, Yun Liu, Jia-Wang Bian, Xun Xu, Joey Tianyi Zhou, Ce Zhu:
Correction to: Deep negative correlation classification. 28 - S. Abilasha, Sahely Bhadra:
Warping resilient robust anomaly detection for multivariate time series. 29 - Muhammad Ali Chattha, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed:
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +. 30 - Xin Zhang, Deval Mehta, Yanan Hu, Chao Zhu, David Darby, Zhen Yu, Daniel Merlo, Melissa Gresle, Anneke van der Walt, Helmut Butzkueven, Zongyuan Ge:
Adaptive transformer modelling of density function for nonparametric survival analysis. 31 - Sabrina Khurshid, Mohammed Shahid Abdulla, Gourab Ghatak:
Optimizing sharpe ratio: risk-adjusted decision-making in multi-armed bandits. 32 - Yuchen Chen, Jing Lei:
De-biased two-sample U-statistics with application to conditional distribution testing. 33 - Aljaz Osojnik, Pance Panov, Saso Dzeroski:
iSOUP-SymRF: Symbolic feature ranking with random forests in online multi-target regression and multi-label classification. 34 - Pavlin G. Policar, Blaz Zupan:
Uncovering temporal patterns in visualizations of high-dimensional data. 35 - Jianan Yang, Jimin Tan, Haobo Wang, Gang Chen, Sai Wu, Junbo Zhao:
Shift guided active learning. 36 - Ruimeng Li, Yuanhao Pu, Zhaoyi Li, Chenwang Wu, Hong Xie, Defu Lian:
Invariant representation learning via decoupling style and spurious features. 37 - Dennis Fassmeyer, Moritz Cordes, Ulf Brefeld:
Interactive sequential generative models for team sports. 38 - Yun-Hsuan Lien, Chia-Tung Lian, Yu-Shuen Wang:
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows. 39 - Tonglin Chen, Yinxuan Huang, Zhimeng Shen, Jinghao Huang, Bin Li, Xiangyang Xue:
Learning global object-centric representations via disentangled slot attention. 40 - Giulia Binotto, Rosario Delgado:
Adapting performance metrics for ordinal classification to interval scale: length matters. 41 - Zi-Hao Qiu, Quanqi Hu, Yongjian Zhong, Wei-Wei Tu, Lijun Zhang, Tianbao Yang:
Optimal large-scale stochastic optimization of NDCG surrogates for deep learning. 42 - Gaoxia Jiang, Wenjian Wang:
An interpretable sample selection framework against numerical label noise. 43 - Yannick Rudolph, Ulf Brefeld:
Masked autoencoder for multiagent trajectories. 44 - Jianshu Hu, Paul Weng, Yutong Ban:
State-novelty guided action persistence in deep reinforcement learning. 45 - Haotian Ni, Tian-Zuo Wang, Hong Tao, Xiuqi Huang, Chenping Hou:
Gradient-based causal discovery with latent variables. 46 - Davide Rigoni, Nicolò Navarin, Alessandro Sperduti:
RGCVAE: relational graph conditioned variational autoencoder for molecule design. 47 - Fabian Wunderlich, Henrik Biermann, Weiran Yang, Manuel Bassek, Dominik Raabe, Nico Elbert, Daniel Memmert, Marc Garnica Caparrós:
Assessing machine learning and data imputation approaches to handle the issue of data sparsity in sports forecasting. 48 - Chang Wan, Ke Fan, Xinwei Sun, Yanwei Fu, Minglu Li, Yunliang Jiang, Zhonglong Zheng:
A new formulation of Lipschitz constrained with functional gradient learning for GANs. 49 - Jiaqi Zhang, Yiqin Wang, Meng Wang, Beilun Wang:
Sparse and smooth additive isotonic model in high-dimensional settings. 50
Volume 114, Number 3, March 2025
- Georgios I. Liapis, Sophia Tsoka, Lazaros G. Papageorgiou:
Interpretable optimisation-based approach for hyper-box classification. 51 - Lizhen Lin, Bayan Saparbayeva, Michael Minyi Zhang, David B. Dunson:
Accelerated algorithms for convex and non-convex optimization on manifolds. 52 - Anni Yu, Qing-Long Zhang, Lu Rao, Yu-Bin Yang:
SA-CAM: Semantic-aware visual explanations for deep convolutional networks. 53 - Rui Luo, Nicolò Colombo:
Conformal load prediction with transductive graph autoencoders. 54 - Jonas Hanselle, Stefan Heid, Johannes Fürnkranz, Eyke Hüllermeier:
Probabilistic scoring lists for interpretable machine learning. 55 - Phuong Mai Dinh, Duc-Trong Le, Tuan-Anh Hoang, Dung Duy Le:
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings. 56 - Julia A. Meister, Khuong An Nguyen:
Conformalised data synthesis. 57 - Zhongyi Han, Gongxu Luo, Hao Sun, Yaqian Li, Bo Han, Mingming Gong, Kun Zhang, Tongliang Liu:
Alignclip: navigating the misalignments for robust vision-language generalization. 58 - Wei Xiao, Qifeng Zhou:
PT4Rec: a universal prompt-tuning framework for graph contrastive learning-based recommendations. 59 - Bang Giang Le, Viet Cuong Ta:
Toward finding strong pareto optimal policies in multi-agent reinforcement learning. 60 - Shaocong Ma, James Diffenderfer, Bhavya Kailkhura, Yi Zhou:
Deep learning of PDE correction and mesh adaption without automatic differentiation. 61 - Caihong Mu, Haikun Yu, Lang Qin, Yi Liu:
Dual-view data augmentation at subgraph level and graph contrastive learning for sequential recommendation. 62 - Zhuoran Zhao, Hao Qin, Ming Kong, Luyuan Chen, Di Xie, Jiang Zhu, Qiang Zhu:
Semantic-aware contrastive learning via multi-prompt alignment. 63 - Hao Qin, Luyuan Chen, Ming Kong, Zhuoran Zhao, Xianzhou Zeng, Mengxu Lu, Qiang Zhu:
Progressive semantic learning for unsupervised skeleton-based action recognition. 64 - Abbas Saleminezhad, Negar Arabzadeh, Radin Hamidi Rad, Soosan Beheshti, Ebrahim Bagheri:
Robust query performance prediction for dense retrievers via adaptive disturbance generation. 65 - Ke Niu, Haiyang Yu, Xuelin Qian, Teng Fu, Bin Li, Xiangyang Xue:
Synthesizing efficient data with diffusion models for person re-identification pre-training. 66 - Lefei Zhang, Geng Yu, Jiangchao Yao, Yew-Soon Ong, Ivor W. Tsang, James T. Kwok:
Sandbox: safeguarded multi-label learning through safe optimal transport. 67 - Zhi-Hong Qi, Da-Wei Zhou, Yiran Yao, Han-Jia Ye, De-Chuan Zhan:
Adaptive adapter routing for long-tailed class-incremental learning. 68 - Jianan Yang, Yanming Zhang, Haobo Wang, Gang Chen, Sai Wu, Junbo Zhao:
CaCOM: customizing text-to-image diffusion models in the wild via continual active selection. 69 - Qizao Wang, Xuelin Qian, Bin Li, Xiangyang Xue:
Distribution aligned semantics adaption for lifelong person re-identification. 70 - Tengjie Li, Shikui Tu, Lei Xu:
SketchMLP: effectively utilize rasterized images and drawing sequences for sketch recognition. 71 - Yann Claes, Vân Anh Huynh-Thu, Pierre Geurts:
Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting. 72 - Omid Shokrollahi, Ruthvik Penumatcha, Faezeh Ensan, Zeinab Noorian:
Schema-tune: noise-driven bias mitigation in transformer-based language models. 73 - Xuran Meng, Yuan Cao, Difan Zou:
Per-example gradient regularization improves learning signals from noisy data. 74 - Yuqing Liang, Meixuan He, Jinlan Liu, Dongpo Xu:
Convergence of Adam for non-convex objectives: relaxed hyperparameters and non-ergodic case. 75 - Xiang Li, Xinxi Jiang, Qifeng Zhou:
Commonsense knowledge enhanced event graph representation learning for script event prediction. 76 - Chi Zhang, Zhen Chen, Peipei Xu, Geyong Min, Wenjie Ruan:
Verification on out-of-distribution detectors under natural perturbations. 77 - Mehran Ghaziasgar, Hossein Mahvash Mohammadi, Peyman Adibi:
A new geometry-aware non-euclidean distance metric. 78 - Yangtao Zhou, Qingshan Li, Hua Chu, Jianan Li, Biaobiao Wei, Shuai Zhang, Jialong Han:
Spatiotemporal-view member preference contrastive representation learning for group recommendation. 79 - Rahul Bordoloi, Clémence Réda, Orell Trautmann, Saptarshi Bej, Olaf Wolkenhauer:
Multivariate functional linear discriminant analysis for partially-observed time series. 80 - Fuhao Shi, Shaohua Wan, Shengli Wu, Hui Wei, Hu Lu:
Deep contrastive coordinated multi-view consistency clustering. 81 - Pascal Rink, Werner Brannath:
Post-selection confidence bounds for prediction performance. 82 - Yundong Li, Yizheng Ge, Chen Lin, Guan Wang:
Unsupervised variational domain adaptation. 83 - Esla Timothy Anzaku, Haohan Wang, Ajiboye Babalola, Arnout Van Messem, Wesley De Neve:
Re-assessing accuracy degradation: a framework for understanding DNN behavior on similar-but-non-identical test datasets. 84 - Felix Q. Weitkämper:
Scaling the weight parameters in Markov logic networks and relational logistic regression models. 85
Volume 114, Number 4, April 2025
- Jeonghoon Kim, Chao Huang, Xin Liu:
An empirical study on impact of label noise on synthetic tabular data generation. 90 - Daniele Meli, Paolo Fiorini:
Inductive learning of robot task knowledge from raw data and online expert feedback. 91 - Alejandro Moreo, Pablo González, Juan José del Coz:
Kernel density estimation for multiclass quantification. 92 - Jiahao Xie, Chao Zhang, Zebang Shen, Hui Qian:
Efficient projection-free online convex optimization using stochastic gradients. 93 - Yali Du, Ying Li, Yi-Fan Ma, Ming Li:
Capturing the context-aware code change via dynamic control flow graph for commit message generation. 94 - Shirui Wang, Bohan Xie, Ling Ding, Jianting Chen, Yang Xiang:
Reinforced logical reasoning over KGs for interpretable recommendation system. 95 - Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima:
Transfer learning with pre-trained conditional generative models. 96 - A. Baskar, Ashwin Srinivasan, Michael Bain, Enrico W. Coiera:
A model for intelligible interaction between agents that predict and explain. 97 - Thanh Tuan Nguyen, Thanh Phuong Nguyen:
Nettop: A light-weight network of orthogonal-plane features for image recognition. 98 - Vladimir Vovk:
Testing exchangeability in the batch mode with e-values and Markov alternatives. 99 - Tuwe Löfström, Helena Löfström, Ulf Johansson, Cecilia Sönströd, Rudy Matela:
Calibrated explanations for regression. 100 - Boshko Koloski, Nada Lavrac, Blaz Skrlj:
HorNets: learning from discrete and continuous signals with routing neural networks. 101 - Nicole Mücke, Ingo Steinwart:
Empirical risk minimization in the interpolating regime with application to neural network learning. 102 - Mattijs Baert, Pietro Mazzaglia, Sam Leroux, Pieter Simoens:
Maximum causal entropy inverse constrained reinforcement learning. 103 - Jingwei Li, Chengbao Liu, Xiwei Bai, Jie Tan, Jiaqi Chu, Yudong Wang:
Compression and restoration: exploring elasticity in continual test-time adaptation. 104 - Markus Kängsepp, Kaspar Valk, Meelis Kull:
On the usefulness of the fit-on-test view on evaluating calibration of classifiers. 105 - Zhihan Zhou, Yushi Ye, Feng Hong, Peisen Zhao, Jiangchao Yao, Ya Zhang, Qi Tian, Yanfeng Wang:
Uncover the balanced geometry in long-tailed contrastive language-image pretraining. 106 - Josua Faller, Jörg Martin, Clemens Elster:
Deep Errors-in-Variables using a diffusion model. 107 - Monty-Maximilian Zühlke, Daniel Kudenko:
TCR: topologically consistent reweighting for XGBoost in regression tasks. 108 - Sara Salamat, Negar Arabzadeh, Shirin Seyedsalehi, Amin Bigdeli, Morteza Zihayat, Ebrahim Bagheri:
A contrastive neural disentanglement approach for query performance prediction. 109 - Mario Mallea, Ricardo Ñanculef, Mauricio Araya:
Intramodal consistency in triplet-based cross-modal learning for image retrieval. 110 - Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner, Marc Höftmann, Eric Upschulte, Sebastian Konietzny, Maike Behrendt, Stefan Harmeling:
A survey on self-supervised methods for visual representation learning. 111 - Marius Köppel, Alexander Segner, Martin Wagener, Lukas Pensel, Andreas Karwath, Stefan Kramer:
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance. 112 - Shishir Adhikari, Elena Zheleva:
Inferring individual direct causal effects under heterogeneous peer influence. 113 - Massimiliano Altieri, Michelangelo Ceci, Roberto Corizzo:
An end-to-end explainability framework for spatio-temporal predictive modeling. 114 - Stanislav Minsker, Shunan Yao:
Generalized median of means principle for Bayesian inference. 115 - Laurens Sluijterman, Eric Cator, Tom Heskes:
Likelihood-ratio-based confidence intervals for neural networks. 116 - Rustem Takhanov, Maxat Tezekbayev, Artur Pak, Arman Bolatov, Zhenisbek Assylbekov:
Gradient descent fails to learn high-frequency functions and modular arithmetic. 117
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