Machine Learning

Article	Citations
Automated imbalanced classification via layered learning	173
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers	137
Learning to bid and rank together in recommendation systems	105
The role of mutual information in variational classifiers	89
One-Stage Tree: end-to-end tree builder and pruner	81
Parameter identifiability of a deep feedforward ReLU neural network	70
Maximum causal entropy inverse constrained reinforcement learning	69
Robust reputation independence in ranking systems for multiple sensitive attributes	68
Semantic-enhanced graph neural networks with global context representation	59
Fairness seen as global sensitivity analysis	58
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics	56
Compositional scene modeling with global object-centric representations	53
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations	39
A review on instance ranking problems in statistical learning	37
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	35
Adapting performance metrics for ordinal classification to interval scale: length matters	34
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	34
Spike2CGR: an efficient method for spike sequence classification using chaos game representation	31
Masked autoencoder for multiagent trajectories	30
Towards accurate knowledge transfer via target-awareness representation disentanglement	30
Chinese character recognition with radical-structured stroke trees	29
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios	29
Maintaining AUC and H-measure over time	29
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	29
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization	29

Responsible model deployment via model-agnostic uncertainty learning	28
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	28
On the usefulness of the fit-on-test view on evaluating calibration of classifiers	27
A prompt-driven framework for multi-domain knowledge tracing	26
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization	25
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation	24
A flexible class of dependence-aware multi-label loss functions	24
FairSwiRL: fair semi-supervised classification with representation learning	24
Transfer learning with pre-trained conditional generative models	23
Optimal transport for conditional domain matching and label shift	22
GENs: generative encoding networks	22
Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization	22
Invariant representation learning via decoupling style and spurious features	22
Differentially-private data synthetisation for efficient re-identification risk control	21
A calibration test for evaluating set-based epistemic uncertainty representations	21
Generalization bounds for learning under graph-dependence: a survey	21
Efficient private SCO for heavy-tailed data via averaged clipping	21
Glacier: guided locally constrained counterfactual explanations for time series classification	19
Optimal survival trees	19
Trimming stability selection increases variable selection robustness	19
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics	18
Correction to: efficient generator of mathematical expressions for symbolic regression	18
Progressive semantic learning for unsupervised skeleton-based action recognition	18
Autoreplicative random forests with applications to missing value imputation	18
SPA: A poisoning attack framework for graph neural networks through searching and pairing	17
Feature ranking for semi-supervised learning	17
Offline reinforcement learning for learning to dispatch for job shop scheduling	17
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	17
DIMBA: discretely masked black-box attack in single object tracking	16
The backbone method for ultra-high dimensional sparse machine learning	16
Rényi divergence in hidden Markov models	16
Aligning model outputs for class imbalanced non-IID federated learning	16
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior	15
A contrastive neural disentanglement approach for query performance prediction	15
Autoencoding slow representations for semi-supervised data-efficient regression	15
TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring	15
Consensus–relevance kNN and covariate shift mitigation	15
Data-aware process discovery for malware detection: an empirical study	15
Testing exchangeability in the batch mode with e-values and Markov alternatives	15
Event causality extraction through external event knowledge learning and polyhedral word embedding	15
A taxonomy of weight learning methods for statistical relational learning	15
Reducing classifier overconfidence against adversaries through graph algorithms	15
Dynamic datasets and market environments for financial reinforcement learning	15
Capturing the context-aware code change via dynamic control flow graph for commit message generation	15
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver	15
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker	15
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations	15
Context-aware spatio-temporal event prediction via convolutional Hawkes processes	14
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks	14
Learning biologically-interpretable latent representations for gene expression data	14

One transformer for all time series: representing and training with time-dependent heterogeneous tabular data	14
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning	14
Multi-agent reinforcement learning for fast-timescale demand response of residential loads	14
Counterfactual ensembles for interpretable churn prediction: from real-world to privacy-preserving synthetic data	14
Probabilistic scoring lists for interpretable machine learning	14
Imbalanced gradients: a subtle cause of overestimated adversarial robustness	13
Efficient and interpretable raw audio classification with diagonal state space models	13
Empirical Bayes linked matrix decomposition	13
Coresets for kernel clustering	13
Exploiting counter-examples for active learning with partial labels	13
A new formulation of Lipschitz constrained with functional gradient learning for GANs	13
Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing	13
Understanding prediction discrepancies in classification	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
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity	13
Mind the gap: from plausible to valid self-explanations in large language models	13
Targeted adversarial attacks on wind power forecasts	13
Online binary classification from similar and dissimilar data	12
Scale-preserving automatic concept extraction (SPACE)	12
Improving kernel online learning with a snapshot memory	12
Online AutoML: an adaptive AutoML framework for online learning	12
Efficient and provable online reduced rank regression via online gradient descent	12
Fraud detection with natural language processing	12
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media	12
Attacking neural machine translations via hybrid attention learning	12
On the robustness of randomized classifiers to adversarial examples	12
An interpretable sample selection framework against numerical label noise	12
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	12
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro	12
Transfer and share: semi-supervised learning from long-tailed data	11
Weighted neural tangent kernel: a generalized and improved network-induced kernel	11
Efficient federated unlearning under plausible deniability	11
Gradient boosted trees for evolving data streams	11
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation	11
Correction to: Modeling PU learning using probabilistic logic programming	11
Search or split: policy gradient with adaptive policy space	11
Empirical analysis of performance assessment for imbalanced classification	11
Improving interpretability via regularization of neural activation sensitivity	11
Robust matrix estimations meet Frank–Wolfe algorithm	11
Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions	11
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	11
Large-scale pinball twin support vector machines	10
Fast linear model trees by PILOT	10
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models	10
Semi-supervised Latent Block Model with pairwise constraints	10
Quantitative Gaussian approximation of randomly initialized deep neural networks	10
Lifted model checking for relational MDPs	10
Permutation-invariant linear classifiers	10
Online learning of network bottlenecks via minimax paths	10
Calibrated explanations for regression	10
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	10
InfoGram and admissible machine learning	10
Adversarial concept drift detection under poisoning attacks for robust data stream mining	10
Pruning during training by network efficacy modeling	10
Jaccard-constrained dense subgraph discovery	10
How to be fair? A study of label and selection bias	9
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	9
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	9
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	9
On the benefits of representation regularization in invariance based domain generalization	9
Learning answer set programs with aggregates via sampling and genetic programming	9
Troubleshooting image segmentation models with human-in-the-loop	9
Hitting the target: stopping active learning at the cost-based optimum	9
Correction to: A neural meta-model for predicting winter wheat crop yield	9
Achieving adversarial robustness via sparsity	9
A unified view of forward and backward losses for learning from weak labels	9
Explaining short text classification with diverse synthetic exemplars and counter-exemplars	9
Efficient fair principal component analysis	9
Traditional and context-specific spam detection in low resource settings	9
Distribution-free conformal joint prediction regions for neural marked temporal point processes	8
iSOUP-SymRF: Symbolic feature ranking with random forests in online multi-target regression and multi-label classification	8
Understanding transfer learning and gradient-based meta-learning techniques	8
SafeGen: safeguarding privacy and fairness through a genetic method	8
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network	8
Diverse and consistent multi-view networks for semi-supervised regression	8
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?	8
Relational data embeddings for feature enrichment with background information	8
Federated learning with superquantile aggregation for heterogeneous data	8
DEFT: distilling entangled factors by preventing information diffusion	8

Wasserstein dropout	8
Graph spring neural ODEs for link sign prediction	8
CoMadOut—a robust outlier detection algorithm based on CoMAD	8
ALM-PU: positive and unlabeled learning with constrained optimization	7
Information bottleneck and selective noise supervision for zero-shot learning	7
Generalized vec trick for fast learning of pairwise kernel models	7
A unified framework for online trip destination prediction	7
Hierarchically structured task-agnostic continual learning	7
Sanitized clustering against confounding bias	7
Toward practical human-interpretable explanations	7
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	7
Polynomial-based graph convolutional neural networks for graph classification	7
Explaining recommendation system using counterfactual textual explanations	7
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics	7
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows	7
Hellinger distance decision trees for PU learning in imbalanced data sets	7
Black-box Bayesian adversarial attack with transferable priors	7
In-game soccer outcome prediction with offline reinforcement learning	7
Unified convergence analysis for adaptive optimization with moving average estimator	7
Nrat: towards adversarial training with inherent label noise	7
On metafeatures’ ability of implicit concept identification	7
Spatiotemporal-view member preference contrastive representation learning for group recommendation	7
Adaptive adapter routing for long-tailed class-incremental learning	7
Dense subgraphs induced by edge labels	7
Gradient descent fails to learn high-frequency functions and modular arithmetic	6
Gradient-based causal discovery with latent variables	6
Tree-based dynamic classifier chains	6
State-novelty guided action persistence in deep reinforcement learning	6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression	6
Bayesian mixture variational autoencoders for multi-modal learning	6
Stress detection with encoding physiological signals and convolutional neural network	6
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	6
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +	6
When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days	6
MLife: a lite framework for machine learning lifecycle initialization	6
Recurrent segmentation meets block models in temporal networks	6
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings	6
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	6
Temporal ensemble of multiple patterns’ instances for continuous prediction of events	6
A framework for training larger networks for deep Reinforcement learning	6
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance	6
Tight mixed-integer optimization formulations for prescriptive trees	6
Sandbox: safeguarded multi-label learning through safe optimal transport	6
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting	6
The class imbalance problem in deep learning	6
Generalizing universal adversarial perturbations for deep neural networks	6
Improving text processing via adversarial low-rank adaptation	5
A comparison of latent space modeling techniques in a plain-vanilla autoencoder setting	5
CaCOM: customizing text-to-image diffusion models in the wild via continual active selection	5
DOC$$^3$$: deep one class classification using contradictions	5
Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse	5
Deep learning and multivariate time series for cheat detection in video games	5
Evaluating soccer match prediction models: a deep learning approach and feature optimization for gradient-boosted trees	5
DPG: a model to build feature subspace against adversarial patch attack	5
Persian offensive language detection	5
Active learning algorithm through the lens of rejection arguments	5
Learning with risks based on M-location	5
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency	5
Leveraging differentiable NAS and abstract genetic algorithms for optimizing on-mobile VSR performance	5
End-to-end entity-aware neural machine translation	5
Dual-domain graph convolutional networks for skeleton-based action recognition	5
Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting	5
Conformal load prediction with transductive graph autoencoders	5
Improving graph neural networks through feature importance learning	5
Meta-interpretive learning as metarule specialisation	5
Improve generated adversarial imitation learning with reward variance regularization	5
MapFlow: latent transition via normalizing flow for unsupervised domain adaptation	5
Towards enabling learnware to handle heterogeneous feature spaces	5
Multi-target prediction for dummies using two-branch neural networks	5
Ranking-preserved generative label enhancement	5
A new adaptive gradient method with gradient decomposition	5
A generalized Weisfeiler-Lehman graph kernel	5
Sparse classification: a scalable discrete optimization perspective	5
HFIA: a parasitic feature inference attack and gradient-based defense strategy in SplitNN-based vertical federated learning	5
Dynamic weighted ensemble for diarrhoea incidence predictions	5
Understanding CNN fragility when learning with imbalanced data	5
Exposing and explaining fake news on-the-fly	5
Efficient SVDD sampling with approximation guarantees for the decision boundary	5
GVFs in the real world: making predictions online for water treatment	5
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning	5
Automotive fault nowcasting with machine learning and natural language processing	5
Fast spectral analysis for approximate nearest neighbor search	4
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio	4
Contrastive counterfactual visual explanations with overdetermination	4
Learning from crowds with sparse and imbalanced annotations	4
Positive-unlabeled classification under class-prior shift: a prior-invariant approach based on density ratio estimation	4
Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	4
A class sensitivity feature guided T-type generative model for noisy label classification	4
Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo	4
Deep Errors-in-Variables using a diffusion model	4
Differentiable learning of matricized DNFs and its application to Boolean networks	4
Sparse and smooth additive isotonic model in high-dimensional settings	4
Naive automated machine learning	4
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models	4
A brain-inspired algorithm for training highly sparse neural networks	4