Machine Learning

Article	Citations
Automated imbalanced classification via layered learning	219
Adapting performance metrics for ordinal classification to interval scale: length matters	162
One-Stage Tree: end-to-end tree builder and pruner	121
Parameter identifiability of a deep feedforward ReLU neural network	90
Maximum causal entropy inverse constrained reinforcement learning	86
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	79
Semantic-enhanced graph neural networks with global context representation	68
Fairness seen as global sensitivity analysis	65
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics	64
Compositional scene modeling with global object-centric representations	55
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations	55
A review on instance ranking problems in statistical learning	54
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers	50
Learning to bid and rank together in recommendation systems	47
Spike2CGR: an efficient method for spike sequence classification using chaos game representation	38
The role of mutual information in variational classifiers	35
Robust reputation independence in ranking systems for multiple sensitive attributes	34
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	33
Masked autoencoder for multiagent trajectories	30
Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization	29
Invariant representation learning via decoupling style and spurious features	29
Differentially-private data synthetisation for efficient re-identification risk control	29
Towards accurate knowledge transfer via target-awareness representation disentanglement	28
Optimal survival trees	27
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	27

Chinese character recognition with radical-structured stroke trees	27
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios	26
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization	26
Efficient private SCO for heavy-tailed data via averaged clipping	25
Maintaining AUC and H-measure over time	25
Glacier: guided locally constrained counterfactual explanations for time series classification	24
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization	23
On the usefulness of the fit-on-test view on evaluating calibration of classifiers	23
Generalization bounds for learning under graph-dependence: a survey	23
A prompt-driven framework for multi-domain knowledge tracing	23
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation	22
GENs: generative encoding networks	22
Trimming stability selection increases variable selection robustness	21
FairSwiRL: fair semi-supervised classification with representation learning	21
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	21
A calibration test for evaluating set-based epistemic uncertainty representations	21
A flexible class of dependence-aware multi-label loss functions	20
Transfer learning with pre-trained conditional generative models	20
Responsible model deployment via model-agnostic uncertainty learning	19
Optimal transport for conditional domain matching and label shift	19
Correction to: efficient generator of mathematical expressions for symbolic regression	18
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics	18
Data-aware process discovery for malware detection: an empirical study	18
SPA: A poisoning attack framework for graph neural networks through searching and pairing	17
Progressive semantic learning for unsupervised skeleton-based action recognition	17
Aligning model outputs for class imbalanced non-IID federated learning	16
Feature ranking for semi-supervised learning	16
DIMBA: discretely masked black-box attack in single object tracking	16
The backbone method for ultra-high dimensional sparse machine learning	15
Autoreplicative random forests with applications to missing value imputation	15
Autoencoding slow representations for semi-supervised data-efficient regression	15
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	15
Dynamic datasets and market environments for financial reinforcement learning	15
Testing exchangeability in the batch mode with e-values and Markov alternatives	15
A taxonomy of weight learning methods for statistical relational learning	15
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	15
Offline reinforcement learning for learning to dispatch for job shop scheduling	15
Capturing the context-aware code change via dynamic control flow graph for commit message generation	15
A contrastive neural disentanglement approach for query performance prediction	15
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker	14
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations	14
Multi-agent reinforcement learning for fast-timescale demand response of residential loads	14
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks	14
Consensus–relevance kNN and covariate shift mitigation	14
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver	14
Probabilistic scoring lists for interpretable machine learning	14
Reducing classifier overconfidence against adversaries through graph algorithms	14
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning	14
Learning biologically-interpretable latent representations for gene expression data	14
TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring	13

Constrained regret minimization for multi-criterion multi-armed bandits	13
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity	13
Coresets for kernel clustering	13
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior	13
Imbalanced gradients: a subtle cause of overestimated adversarial robustness	13
A new formulation of Lipschitz constrained with functional gradient learning for GANs	13
Empirical Bayes linked matrix decomposition	13
Context-aware spatio-temporal event prediction via convolutional Hawkes processes	13
An in-depth review and analysis of mode collapse in generative adversarial networks	13
One transformer for all time series: representing and training with time-dependent heterogeneous tabular data	13
Efficient and provable online reduced rank regression via online gradient descent	13
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media	13
Exploiting counter-examples for active learning with partial labels	13
Event causality extraction through external event knowledge learning and polyhedral word embedding	13
Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing	12
Mind the gap: from plausible to valid self-explanations in large language models	12
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro	12
Online AutoML: an adaptive AutoML framework for online learning	12
Understanding prediction discrepancies in classification	12
Targeted adversarial attacks on wind power forecasts	12
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	12
Scale-preserving automatic concept extraction (SPACE)	12
Efficient and interpretable raw audio classification with diagonal state space models	12
Attacking neural machine translations via hybrid attention learning	12
Improving kernel online learning with a snapshot memory	12
Large-scale pinball twin support vector machines	12
Online binary classification from similar and dissimilar data	11
An interpretable sample selection framework against numerical label noise	11
Weighted neural tangent kernel: a generalized and improved network-induced kernel	11
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation	11
Fraud detection with natural language processing	11
Transfer and share: semi-supervised learning from long-tailed data	11
Quantitative Gaussian approximation of randomly initialized deep neural networks	11
On the robustness of randomized classifiers to adversarial examples	11
Adversarial concept drift detection under poisoning attacks for robust data stream mining	11
Improving interpretability via regularization of neural activation sensitivity	11
Correction to: Modeling PU learning using probabilistic logic programming	11
Empirical analysis of performance assessment for imbalanced classification	10
Search or split: policy gradient with adaptive policy space	10
Lifted model checking for relational MDPs	10
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	10
Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions	10
Understanding generalization error of SGD in nonconvex optimization	10
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	10
Troubleshooting image segmentation models with human-in-the-loop	10
Efficient federated unlearning under plausible deniability	10
Robust matrix estimations meet Frank–Wolfe algorithm	10
Gradient boosted trees for evolving data streams	10
Calibrated explanations for regression	10
Permutation-invariant linear classifiers	9
Achieving adversarial robustness via sparsity	9
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models	9
Efficient fair principal component analysis	9
Online learning of network bottlenecks via minimax paths	9
Jaccard-constrained dense subgraph discovery	9
How to be fair? A study of label and selection bias	9
Pruning during training by network efficacy modeling	9
A unified view of forward and backward losses for learning from weak labels	9
Traditional and context-specific spam detection in low resource settings	9
On the benefits of representation regularization in invariance based domain generalization	9
Semi-supervised Latent Block Model with pairwise constraints	9
InfoGram and admissible machine learning	9
Understanding transfer learning and gradient-based meta-learning techniques	8
Relational data embeddings for feature enrichment with background information	8
Diverse and consistent multi-view networks for semi-supervised regression	8
Hitting the target: stopping active learning at the cost-based optimum	8
Correction to: A neural meta-model for predicting winter wheat crop yield	8
Federated learning with superquantile aggregation for heterogeneous data	8
iSOUP-SymRF: Symbolic feature ranking with random forests in online multi-target regression and multi-label classification	8
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network	8
Explaining recommendation system using counterfactual textual explanations	8
Learning answer set programs with aggregates via sampling and genetic programming	8
Fast linear model trees by PILOT	8
Explaining short text classification with diverse synthetic exemplars and counter-exemplars	8
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	8
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?	8
Time-aware tensor decomposition for sparse tensors	8
Information bottleneck and selective noise supervision for zero-shot learning	8
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	8
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	8

Wasserstein dropout	8
DEFT: distilling entangled factors by preventing information diffusion	8
Graph spring neural ODEs for link sign prediction	7
Hierarchically structured task-agnostic continual learning	7
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics	7
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	7
Dense subgraphs induced by edge labels	7
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +	7
Nrat: towards adversarial training with inherent label noise	7
Distribution-free conformal joint prediction regions for neural marked temporal point processes	7
Unified convergence analysis for adaptive optimization with moving average estimator	7
Hellinger distance decision trees for PU learning in imbalanced data sets	7
Sanitized clustering against confounding bias	7
Adaptive adapter routing for long-tailed class-incremental learning	7
A unified framework for online trip destination prediction	7
Polynomial-based graph convolutional neural networks for graph classification	7
Generalized vec trick for fast learning of pairwise kernel models	7
On metafeatures’ ability of implicit concept identification	7
Spatiotemporal-view member preference contrastive representation learning for group recommendation	7
In-game soccer outcome prediction with offline reinforcement learning	7
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows	7
Temporal ensemble of multiple patterns’ instances for continuous prediction of events	7
CoMadOut—a robust outlier detection algorithm based on CoMAD	7
ALM-PU: positive and unlabeled learning with constrained optimization	6
A framework for training larger networks for deep Reinforcement learning	6
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	6
Gradient-based causal discovery with latent variables	6
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings	6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression	6
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting	6
Stress detection with encoding physiological signals and convolutional neural network	6
Toward practical human-interpretable explanations	6
Gradient descent fails to learn high-frequency functions and modular arithmetic	6
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance	6
MLife: a lite framework for machine learning lifecycle initialization	6
Recurrent segmentation meets block models in temporal networks	6
Improve generated adversarial imitation learning with reward variance regularization	6
The class imbalance problem in deep learning	6
Black-box Bayesian adversarial attack with transferable priors	6
Generalizing universal adversarial perturbations for deep neural networks	6
Bayesian mixture variational autoencoders for multi-modal learning	6
Sandbox: safeguarded multi-label learning through safe optimal transport	6
State-novelty guided action persistence in deep reinforcement learning	6
When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days	6
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	6
Ranking-preserved generative label enhancement	5
Tight mixed-integer optimization formulations for prescriptive trees	5
Multi-target prediction for dummies using two-branch neural networks	5
Active learning algorithm through the lens of rejection arguments	5
Improving graph neural networks through feature importance learning	5
Machine unlearning: linear filtration for logit-based classifiers	5
Persian offensive language detection	5
Meta-interpretive learning as metarule specialisation	5
Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting	5
Dynamic weighted ensemble for diarrhoea incidence predictions	5
HFIA: a parasitic feature inference attack and gradient-based defense strategy in SplitNN-based vertical federated learning	5
Learning with risks based on M-location	5
A generalized Weisfeiler-Lehman graph kernel	5
Leveraging differentiable NAS and abstract genetic algorithms for optimizing on-mobile VSR performance	5
Automotive fault nowcasting with machine learning and natural language processing	5
Improving text processing via adversarial low-rank adaptation	5
DOC$$^3$$: deep one class classification using contradictions	5
Dual-domain graph convolutional networks for skeleton-based action recognition	5
MapFlow: latent transition via normalizing flow for unsupervised domain adaptation	5
Sparse classification: a scalable discrete optimization perspective	5
CaCOM: customizing text-to-image diffusion models in the wild via continual active selection	5
Towards enabling learnware to handle heterogeneous feature spaces	5
DPG: a model to build feature subspace against adversarial patch attack	5
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency	5
A comparison of latent space modeling techniques in a plain-vanilla autoencoder setting	5
A new adaptive gradient method with gradient decomposition	5
Tree-based dynamic classifier chains	5
Efficient SVDD sampling with approximation guarantees for the decision boundary	5
Model selection in reconciling hierarchical time series	5
Exposing and explaining fake news on-the-fly	5
Jensen–Tsallis divergence for supervised classification under data imbalance	5
Deep learning and multivariate time series for cheat detection in video games	5
Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse	5
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning	5
Fast spectral analysis for approximate nearest neighbor search	4
Deep Errors-in-Variables using a diffusion model	4
Contrastive counterfactual visual explanations with overdetermination	4
Boundary-restricted metric learning	4
Gentle local robustness implies generalization	4
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio	4
Learning from crowds with sparse and imbalanced annotations	4
The flowing nature matters: feature learning from the control flow graph of source code for bug localization	4
Margin distribution and structural diversity guided ensemble pruning	4
Drop-in efficient self-attention approximation method	4
Differentiable learning of matricized DNFs and its application to Boolean networks	4
Sparse and smooth additive isotonic model in high-dimensional settings	4
A study of BERT for context-aware neural machine translation	4
Fedflow: a personalized federated learning framework for passenger flow prediction	4
Naive automated machine learning	4
Explaining neural networks without access to training data	4