Machine Learning

Papers
(The median citation count of Machine Learning is 1. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-05-01 to 2025-05-01.)
ArticleCitations
The role of mutual information in variational classifiers189
Automated imbalanced classification via layered learning113
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations113
Learning to bid and rank together in recommendation systems104
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics90
Adapting performance metrics for ordinal classification to interval scale: length matters89
Robust reputation independence in ranking systems for multiple sensitive attributes79
Fairness seen as global sensitivity analysis72
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers72
One-Stage Tree: end-to-end tree builder and pruner70
Multimodal deep learning for cetacean distribution modeling of fin whales (Balaenoptera physalus) in the western Mediterranean Sea60
Parameter identifiability of a deep feedforward ReLU neural network51
Compositional scene modeling with global object-centric representations51
Maximum causal entropy inverse constrained reinforcement learning50
Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives50
Spike2CGR: an efficient method for spike sequence classification using chaos game representation47
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations43
A review on instance ranking problems in statistical learning42
Semantic-enhanced graph neural networks with global context representation41
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting40
Invariant representation learning via decoupling style and spurious features39
Masked autoencoder for multiagent trajectories34
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios33
Optimal survival trees31
GENs: generative encoding networks30
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations30
Importance sampling in reinforcement learning with an estimated behavior policy29
FairSwiRL: fair semi-supervised classification with representation learning28
Chinese character recognition with radical-structured stroke trees28
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization27
A flexible class of dependence-aware multi-label loss functions27
Maintaining AUC and H-measure over time27
Responsible model deployment via model-agnostic uncertainty learning26
Optimal transport for conditional domain matching and label shift25
Towards accurate knowledge transfer via target-awareness representation disentanglement24
Learning any memory-less discrete semantics for dynamical systems represented by logic programs24
WINTENDED: WINdowed TENsor decomposition for Densification Event Detection in time-evolving networks23
Efficient private SCO for heavy-tailed data via averaged clipping23
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization23
Trimming stability selection increases variable selection robustness22
Glacier: guided locally constrained counterfactual explanations for time series classification21
Transfer learning with pre-trained conditional generative models21
A prompt-driven framework for multi-domain knowledge tracing20
On the usefulness of the fit-on-test view on evaluating calibration of classifiers20
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation20
Generalization bounds for learning under graph-dependence: a survey19
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events19
Dynamic datasets and market environments for financial reinforcement learning19
Correction to: efficient generator of mathematical expressions for symbolic regression19
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics19
DIMBA: discretely masked black-box attack in single object tracking19
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes19
Data-aware process discovery for malware detection: an empirical study18
Aligning model outputs for class imbalanced non-IID federated learning18
Feature ranking for semi-supervised learning17
Progressive semantic learning for unsupervised skeleton-based action recognition17
SPA: A poisoning attack framework for graph neural networks through searching and pairing17
Autoreplicative random forests with applications to missing value imputation17
The backbone method for ultra-high dimensional sparse machine learning17
Capturing the context-aware code change via dynamic control flow graph for commit message generation16
Testing exchangeability in the batch mode with e-values and Markov alternatives16
A contrastive neural disentanglement approach for query performance prediction16
Autoencoding slow representations for semi-supervised data-efficient regression15
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior15
A taxonomy of weight learning methods for statistical relational learning15
Reducing classifier overconfidence against adversaries through graph algorithms15
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker15
Consensus–relevance kNN and covariate shift mitigation15
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks14
Context-aware spatio-temporal event prediction via convolutional Hawkes processes14
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver14
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning14
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations14
Multi-agent reinforcement learning for fast-timescale demand response of residential loads14
Learning biologically-interpretable latent representations for gene expression data13
Probabilistic scoring lists for interpretable machine learning13
Targeted adversarial attacks on wind power forecasts13
Event causality extraction through external event knowledge learning and polyhedral word embedding13
How to measure uncertainty in uncertainty sampling for active learning13
One transformer for all time series: representing and training with time-dependent heterogeneous tabular data13
Coresets for kernel clustering13
An in-depth review and analysis of mode collapse in generative adversarial networks13
Imbalanced gradients: a subtle cause of overestimated adversarial robustness13
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity12
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media12
Empirical Bayes linked matrix decomposition12
Attacking neural machine translations via hybrid attention learning12
Exploiting counter-examples for active learning with partial labels12
Ordinal regression with explainable distance metric learning based on ordered sequences12
Online AutoML: an adaptive AutoML framework for online learning12
Efficient and provable online reduced rank regression via online gradient descent12
Understanding prediction discrepancies in classification12
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events12
Constrained regret minimization for multi-criterion multi-armed bandits12
Large-scale pinball twin support vector machines11
Gradient boosted trees for evolving data streams11
Improving interpretability via regularization of neural activation sensitivity11
Transfer and share: semi-supervised learning from long-tailed data11
Weighted neural tangent kernel: a generalized and improved network-induced kernel11
An interpretable sample selection framework against numerical label noise11
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro11
Online binary classification from similar and dissimilar data11
Adversarial concept drift detection under poisoning attacks for robust data stream mining11
Fraud detection with natural language processing11
A new formulation of Lipschitz constrained with functional gradient learning for GANs11
Improving kernel online learning with a snapshot memory11
On the robustness of randomized classifiers to adversarial examples11
Quantitative Gaussian approximation of randomly initialized deep neural networks11
Testing conditional independence in supervised learning algorithms11
Scale-preserving automatic concept extraction (SPACE)11
Efficient federated unlearning under plausible deniability11
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution10
Robust matrix estimations meet Frank–Wolfe algorithm10
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation10
Troubleshooting image segmentation models with human-in-the-loop10
Calibrated explanations for regression10
Permutation-invariant linear classifiers10
Understanding generalization error of SGD in nonconvex optimization10
Empirical analysis of performance assessment for imbalanced classification10
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework10
Hitting the target: stopping active learning at the cost-based optimum10
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models10
Lifted model checking for relational MDPs10
An improved evolutionary wrapper-filter feature selection approach with a new initialisation scheme10
Byzantine-robust distributed sparse learning for M-estimation10
Joint optimization of an autoencoder for clustering and embedding10
How to be fair? A study of label and selection bias10
Pruning during training by network efficacy modeling10
Efficient fair principal component analysis9
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety9
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework9
InfoGram and admissible machine learning9
On the benefits of representation regularization in invariance based domain generalization9
Bandit algorithms to personalize educational chatbots9
Nrat: towards adversarial training with inherent label noise9
Jaccard-constrained dense subgraph discovery9
Online learning of network bottlenecks via minimax paths9
Fast linear model trees by PILOT9
Semi-supervised Latent Block Model with pairwise constraints9
Traditional and context-specific spam detection in low resource settings9
Achieving adversarial robustness via sparsity9
iSOUP-SymRF: Symbolic feature ranking with random forests in online multi-target regression and multi-label classification8
Correction to: A neural meta-model for predicting winter wheat crop yield8
Wasserstein dropout8
Information bottleneck and selective noise supervision for zero-shot learning8
Diverse and consistent multi-view networks for semi-supervised regression8
Distribution-free conformal joint prediction regions for neural marked temporal point processes8
Hierarchically structured task-agnostic continual learning8
Federated learning with superquantile aggregation for heterogeneous data8
Polynomial-based graph convolutional neural networks for graph classification8
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)8
Explaining short text classification with diverse synthetic exemplars and counter-exemplars8
CoMadOut—a robust outlier detection algorithm based on CoMAD8
DEFT: distilling entangled factors by preventing information diffusion8
A unified framework for online trip destination prediction7
A deep reinforcement learning framework for continuous intraday market bidding7
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +7
Unified convergence analysis for adaptive optimization with moving average estimator7
A parameter-less algorithm for tensor co-clustering7
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions7
Relational data embeddings for feature enrichment with background information7
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network7
Sanitized clustering against confounding bias7
Adaptive adapter routing for long-tailed class-incremental learning7
Spatiotemporal-view member preference contrastive representation learning for group recommendation7
On metafeatures’ ability of implicit concept identification7
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics7
Understanding transfer learning and gradient-based meta-learning techniques7
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?7
Generalized vec trick for fast learning of pairwise kernel models7
Black-box Bayesian adversarial attack with transferable priors7
Dense subgraphs induced by edge labels7
Gradient descent fails to learn high-frequency functions and modular arithmetic7
A framework for training larger networks for deep Reinforcement learning7
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics7
Generalizing universal adversarial perturbations for deep neural networks7
Time-aware tensor decomposition for sparse tensors7
Explaining recommendation system using counterfactual textual explanations7
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency6
MLife: a lite framework for machine learning lifecycle initialization6
Tree-based dynamic classifier chains6
Multi-target prediction for dummies using two-branch neural networks6
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting6
The class imbalance problem in deep learning6
Stress detection with encoding physiological signals and convolutional neural network6
Hellinger distance decision trees for PU learning in imbalanced data sets6
Bayesian mixture variational autoencoders for multi-modal learning6
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance6
State-novelty guided action persistence in deep reinforcement learning6
A generalized Weisfeiler-Lehman graph kernel6
Improve generated adversarial imitation learning with reward variance regularization6
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning6
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders6
In-game soccer outcome prediction with offline reinforcement learning6
Temporal ensemble of multiple patterns’ instances for continuous prediction of events6
Ranking-preserved generative label enhancement6
Gradient-based causal discovery with latent variables6
When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression6
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams6
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows6
Estimation of multidimensional item response theory models with correlated latent variables using variational autoencoders6
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning5
Automotive fault nowcasting with machine learning and natural language processing5
Recurrent segmentation meets block models in temporal networks5
Dynamic weighted ensemble for diarrhoea incidence predictions5
Efficient SVDD sampling with approximation guarantees for the decision boundary5
Deep learning and multivariate time series for cheat detection in video games5
CaCOM: customizing text-to-image diffusion models in the wild via continual active selection5
Meta-interpretive learning as metarule specialisation5
Persian offensive language detection5
Sandbox: safeguarded multi-label learning through safe optimal transport5
Towards enabling learnware to handle heterogeneous feature spaces5
Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting5
DOC$$^3$$: deep one class classification using contradictions5
GVFs in the real world: making predictions online for water treatment5
Model selection in reconciling hierarchical time series5
Exposing and explaining fake news on-the-fly5
Learning with risks based on M-location5
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings5
MapFlow: latent transition via normalizing flow for unsupervised domain adaptation5
Sparse classification: a scalable discrete optimization perspective5
Information-theoretic regularization for learning global features by sequential VAE5
Efficient Weingarten map and curvature estimation on manifolds5
Active learning algorithm through the lens of rejection arguments5
STUDD: a student–teacher method for unsupervised concept drift detection4
Automated adaptation strategies for stream learning4
Fast spectral analysis for approximate nearest neighbor search4
Sparse and smooth additive isotonic model in high-dimensional settings4
Naive automated machine learning4
Drop-in efficient self-attention approximation method4
Correction to: Conformal load prediction with transductive graph autoencoders4
Neural network structure simplification by assessing evolution in node weight magnitude4
Inverse reinforcement learning in contextual MDPs4
Can metafeatures help improve explanations of prediction models when using behavioral and textual data?4
Boundary-restricted metric learning4
Inductive learning of answer set programs for autonomous surgical task planning4
Composite score for anomaly detection in imbalanced real-world industrial dataset4
Gentle local robustness implies generalization4
Uncover the balanced geometry in long-tailed contrastive language-image pretraining4
A comparison of proximity-based methods for detecting temporal anomalies in business processes4
Contrastive counterfactual visual explanations with overdetermination4
Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo4
Multiclass optimal classification trees with SVM-splits4
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio4
Deep Errors-in-Variables using a diffusion model4
Graph-based semi-supervised learning via improving the quality of the graph dynamically4
Margin distribution and structural diversity guided ensemble pruning4
The flowing nature matters: feature learning from the control flow graph of source code for bug localization4
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models4
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