Machine Learning

Article	Citations
Automated imbalanced classification via layered learning	188
One-Stage Tree: end-to-end tree builder and pruner	144
Learning to bid and rank together in recommendation systems	121
The role of mutual information in variational classifiers	83
Robust reputation independence in ranking systems for multiple sensitive attributes	72
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers	72
Maximum causal entropy inverse constrained reinforcement learning	72
Parameter identifiability of a deep feedforward ReLU neural network	65
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics	60
A review on instance ranking problems in statistical learning	59
Spike2CGR: an efficient method for spike sequence classification using chaos game representation	59
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	39
Adapting performance metrics for ordinal classification to interval scale: length matters	39
Fairness seen as global sensitivity analysis	38
Semantic-enhanced graph neural networks with global context representation	37
Compositional scene modeling with global object-centric representations	35
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations	32
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	31
A prompt-driven framework for multi-domain knowledge tracing	31
On the usefulness of the fit-on-test view on evaluating calibration of classifiers	31
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization	30
FairSwiRL: fair semi-supervised classification with representation learning	30
Maintaining AUC and H-measure over time	30
Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization	29
Transfer learning with pre-trained conditional generative models	29

Differentially-private data synthetisation for efficient re-identification risk control	29
A flexible class of dependence-aware multi-label loss functions	29
GENs: generative encoding networks	29
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	27
Towards accurate knowledge transfer via target-awareness representation disentanglement	26
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios	25
Trimming stability selection increases variable selection robustness	25
Masked autoencoder for multiagent trajectories	25
Glacier: guided locally constrained counterfactual explanations for time series classification	25
Efficient private SCO for heavy-tailed data via averaged clipping	23
A calibration test for evaluating set-based epistemic uncertainty representations	22
Optimal transport for conditional domain matching and label shift	22
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation	22
Optimal survival trees	21
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization	21
Responsible model deployment via model-agnostic uncertainty learning	20
Chinese character recognition with radical-structured stroke trees	20
Generalization bounds for learning under graph-dependence: a survey	20
Offline reinforcement learning for learning to dispatch for job shop scheduling	19
Invariant representation learning via decoupling style and spurious features	19
Correction to: efficient generator of mathematical expressions for symbolic regression	19
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	19
Data-aware process discovery for malware detection: an empirical study	18
Autoreplicative random forests with applications to missing value imputation	18
Progressive semantic learning for unsupervised skeleton-based action recognition	18
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	18
Rényi divergence in hidden Markov models	18
SPA: A poisoning attack framework for graph neural networks through searching and pairing	17
Feature ranking for semi-supervised learning	17
Dynamic datasets and market environments for financial reinforcement learning	17
DIMBA: discretely masked black-box attack in single object tracking	17
Aligning model outputs for class imbalanced non-IID federated learning	17
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics	17
Testing exchangeability in the batch mode with e-values and Markov alternatives	16
A contrastive neural disentanglement approach for query performance prediction	16
Autoencoding slow representations for semi-supervised data-efficient regression	16
The backbone method for ultra-high dimensional sparse machine learning	16
Event causality extraction through external event knowledge learning and polyhedral word embedding	15
Reducing classifier overconfidence against adversaries through graph algorithms	15
A taxonomy of weight learning methods for statistical relational learning	15
Learning biologically-interpretable latent representations for gene expression data	15
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks	15
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations	15
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker	15
Multi-agent reinforcement learning for fast-timescale demand response of residential loads	15
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver	15
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning	15
Capturing the context-aware code change via dynamic control flow graph for commit message generation	15
Consensus–relevance kNN and covariate shift mitigation	15
Adaptive differentiable trees for transparent learning on data streams	14

One transformer for all time series: representing and training with time-dependent heterogeneous tabular data	14
Context-aware spatio-temporal event prediction via convolutional Hawkes processes	14
Coresets for kernel clustering	14
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior	14
Attacking neural machine translations via hybrid attention learning	13
Online AutoML: an adaptive AutoML framework for online learning	13
Probabilistic scoring lists for interpretable machine learning	13
Exploiting counter-examples for active learning with partial labels	13
Imbalanced gradients: a subtle cause of overestimated adversarial robustness	13
Efficient and provable online reduced rank regression via online gradient descent	13
Efficient and interpretable raw audio classification with diagonal state space models	13
Counterfactual ensembles for interpretable churn prediction: from real-world to privacy-preserving synthetic data	13
Pdarts: projected differentiable architecture search for seismic inversion	13
Mind the gap: from plausible to valid self-explanations in large language models	13
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	13
A new formulation of Lipschitz constrained with functional gradient learning for GANs	13
An in-depth review and analysis of mode collapse in generative adversarial networks	13
Constrained regret minimization for multi-criterion multi-armed bandits	13
TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring	13
Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing	12
Targeted adversarial attacks on wind power forecasts	12
Weighted neural tangent kernel: a generalized and improved network-induced kernel	12
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro	12
An interpretable sample selection framework against numerical label noise	12
On the robustness of randomized classifiers to adversarial examples	12
Understanding prediction discrepancies in classification	12
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media	12
Empirical Bayes linked matrix decomposition	12
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation	12
Gradient boosted trees for evolving data streams	12
Improving kernel online learning with a snapshot memory	12
Learning de-biased environment models for delivery incentive policy optimization on food delivery platforms	12
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity	12
Online binary classification from similar and dissimilar data	12
Robust matrix estimations meet Frank–Wolfe algorithm	12
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	12
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	11
Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions	11
Fraud detection with natural language processing	11
Correction to: Modeling PU learning using probabilistic logic programming	11
Scale-preserving automatic concept extraction (SPACE)	11
Quantitative Gaussian approximation of randomly initialized deep neural networks	11
Search or split: policy gradient with adaptive policy space	11
Improving interpretability via regularization of neural activation sensitivity	11
Adversarial concept drift detection under poisoning attacks for robust data stream mining	11
Empirical analysis of performance assessment for imbalanced classification	11
Transfer and share: semi-supervised learning from long-tailed data	11
Lifted model checking for relational MDPs	10
Permutation-invariant linear classifiers	10
Online learning of network bottlenecks via minimax paths	10
A unified view of forward and backward losses for learning from weak labels	10
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	10
Fast linear model trees by PILOT	10
Efficient fair principal component analysis	10
Efficient federated unlearning under plausible deniability	10
Pruning during training by network efficacy modeling	10
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models	10
InfoGram and admissible machine learning	10
Hitting the target: stopping active learning at the cost-based optimum	10
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	10
Semi-supervised Latent Block Model with pairwise constraints	10
Learning answer set programs with aggregates via sampling and genetic programming	9
How to be fair? A study of label and selection bias	9
Distribution-free conformal joint prediction regions for neural marked temporal point processes	9
Correction to: A neural meta-model for predicting winter wheat crop yield	9
Troubleshooting image segmentation models with human-in-the-loop	9
On the benefits of representation regularization in invariance based domain generalization	9
Wasserstein dropout	9
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?	9
Traditional and context-specific spam detection in low resource settings	9
Calibrated explanations for regression	9
DEFT: distilling entangled factors by preventing information diffusion	9
Jaccard-constrained dense subgraph discovery	9
Explaining recommendation system using counterfactual textual explanations	8
Adaptive collaborative minority oversampling for multi-class imbalanced classification	8
CoMadOut—a robust outlier detection algorithm based on CoMAD	8
Understanding transfer learning and gradient-based meta-learning techniques	8
Hierarchically structured task-agnostic continual learning	8
Generalized vec trick for fast learning of pairwise kernel models	8
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	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
Information bottleneck and selective noise supervision for zero-shot learning	8
Nrat: towards adversarial training with inherent label noise	8
Relational data embeddings for feature enrichment with background information	8
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network	8
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics	7
On metafeatures’ ability of implicit concept identification	7
Toward practical human-interpretable explanations	7
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +	7
Adaptive adapter routing for long-tailed class-incremental learning	7
Spatiotemporal-view member preference contrastive representation learning for group recommendation	7
Polynomial-based graph convolutional neural networks for graph classification	7
Explaining short text classification with diverse synthetic exemplars and counter-exemplars	7
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows	7
Unified convergence analysis for adaptive optimization with moving average estimator	7
Dense subgraphs induced by edge labels	7
Temporal ensemble of multiple patterns’ instances for continuous prediction of events	7
SafeGen: safeguarding privacy and fairness through a genetic method	7
Diverse and consistent multi-view networks for semi-supervised regression	7
A unified framework for online trip destination prediction	7
In-game soccer outcome prediction with offline reinforcement learning	7
ALM-PU: positive and unlabeled learning with constrained optimization	7
Hellinger distance decision trees for PU learning in imbalanced data sets	7
Black-box Bayesian adversarial attack with transferable priors	7
Graph spring neural ODEs for link sign prediction	7
The class imbalance problem in deep learning	6
Sanitized clustering against confounding bias	6
Generalizing universal adversarial perturbations for deep neural networks	6
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting	6
A new adaptive gradient method with gradient decomposition	6
A comparison of latent space modeling techniques in a plain-vanilla autoencoder setting	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
A framework for training larger networks for deep Reinforcement learning	6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression	6
Tree-based dynamic classifier chains	6
Leveraging differentiable NAS and abstract genetic algorithms for optimizing on-mobile VSR performance	6
Recurrent segmentation meets block models in temporal networks	6
Ranking-preserved generative label enhancement	6
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance	6
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	6
Gradient descent fails to learn high-frequency functions and modular arithmetic	6
Stress detection with encoding physiological signals and convolutional neural network	6
Sandbox: safeguarded multi-label learning through safe optimal transport	6
Tight mixed-integer optimization formulations for prescriptive trees	6
Gradient-based causal discovery with latent variables	6
Improving text processing via adversarial low-rank adaptation	6
Towards enabling learnware to handle heterogeneous feature spaces	5
MapFlow: latent transition via normalizing flow for unsupervised domain adaptation	5
Learning with risks based on M-location	5
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models	5
Improve generated adversarial imitation learning with reward variance regularization	5
Jensen–Tsallis divergence for supervised classification under data imbalance	5
Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse	5
Exposing and explaining fake news on-the-fly	5
Causality from bottom to top: a survey	5
Solving imbalanced learning with outlier detection and features reduction	5
Improving graph neural networks through feature importance learning	5
CaCOM: customizing text-to-image diffusion models in the wild via continual active selection	5
Persian offensive language detection	5
Efficient SVDD sampling with approximation guarantees for the decision boundary	5
Bayesian mixture variational autoencoders for multi-modal learning	5
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings	5
Automotive fault nowcasting with machine learning and natural language processing	5
Multi-target prediction for dummies using two-branch neural networks	5
Meta-interpretive learning as metarule specialisation	5
STUDD: a student–teacher method for unsupervised concept drift detection	5
Model selection in reconciling hierarchical time series	5
GVFs in the real world: making predictions online for water treatment	5
End-to-end entity-aware neural machine translation	5
HFIA: a parasitic feature inference attack and gradient-based defense strategy in SplitNN-based vertical federated learning	5
Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting	5
Understanding CNN fragility when learning with imbalanced data	5
DPG: a model to build feature subspace against adversarial patch attack	5
Bridging XAI and spectral analysis to investigate the inductive biases of deep graph networks	5
A generalized Weisfeiler-Lehman graph kernel	5
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency	5
Dual-domain graph convolutional networks for skeleton-based action recognition	5
Active learning algorithm through the lens of rejection arguments	5
Sparse classification: a scalable discrete optimization perspective	5
DOC$$^3$$: deep one class classification using contradictions	5
Dynamic weighted ensemble for diarrhoea incidence predictions	5
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning	5
Conformal load prediction with transductive graph autoencoders	5