Machine Learning

Article	Citations
Automated imbalanced classification via layered learning	213
Learning to bid and rank together in recommendation systems	148
Adapting performance metrics for ordinal classification to interval scale: length matters	114
One-Stage Tree: end-to-end tree builder and pruner	96
Parameter identifiability of a deep feedforward ReLU neural network	81
Maximum causal entropy inverse constrained reinforcement learning	79
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	78
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	65
Semantic-enhanced graph neural networks with global context representation	61
The role of mutual information in variational classifiers	59
Fairness seen as global sensitivity analysis	53
Robust reputation independence in ranking systems for multiple sensitive attributes	50
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics	49
Compositional scene modeling with global object-centric representations	48
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations	43
A review on instance ranking problems in statistical learning	36
Spike2CGR: an efficient method for spike sequence classification using chaos game representation	34
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers	34
Masked autoencoder for multiagent trajectories	30
Invariant representation learning via decoupling style and spurious features	27
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization	27
Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization	27
Towards accurate knowledge transfer via target-awareness representation disentanglement	27
Differentially-private data synthetisation for efficient re-identification risk control	27
Maintaining AUC and H-measure over time	26

Efficient private SCO for heavy-tailed data via averaged clipping	25
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	25
Glacier: guided locally constrained counterfactual explanations for time series classification	25
A prompt-driven framework for multi-domain knowledge tracing	24
On the usefulness of the fit-on-test view on evaluating calibration of classifiers	24
FairSwiRL: fair semi-supervised classification with representation learning	23
Optimal transport for conditional domain matching and label shift	23
Generalization bounds for learning under graph-dependence: a survey	23
A flexible class of dependence-aware multi-label loss functions	22
Transfer learning with pre-trained conditional generative models	21
Chinese character recognition with radical-structured stroke trees	21
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation	20
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	20
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization	20
GENs: generative encoding networks	20
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios	20
Optimal survival trees	19
Trimming stability selection increases variable selection robustness	19
Responsible model deployment via model-agnostic uncertainty learning	19
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	18
Correction to: efficient generator of mathematical expressions for symbolic regression	18
Progressive semantic learning for unsupervised skeleton-based action recognition	18
Offline reinforcement learning for learning to dispatch for job shop scheduling	16
Aligning model outputs for class imbalanced non-IID federated learning	16
DIMBA: discretely masked black-box attack in single object tracking	16
Dynamic datasets and market environments for financial reinforcement learning	16
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	15
A contrastive neural disentanglement approach for query performance prediction	15
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	15
Testing exchangeability in the batch mode with e-values and Markov alternatives	15
Feature ranking for semi-supervised learning	15
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	14
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker	14
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks	14
Multi-agent reinforcement learning for fast-timescale demand response of residential loads	14
A taxonomy of weight learning methods for statistical relational learning	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
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations	14
Capturing the context-aware code change via dynamic control flow graph for commit message generation	14
Reducing classifier overconfidence against adversaries through graph algorithms	14
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning	14
One transformer for all time series: representing and training with time-dependent heterogeneous tabular data	13
Coresets for kernel clustering	13
Imbalanced gradients: a subtle cause of overestimated adversarial robustness	13
Efficient and provable online reduced rank regression via online gradient descent	13

Probabilistic scoring lists for interpretable machine learning	13
Context-aware spatio-temporal event prediction via convolutional Hawkes processes	13
Event causality extraction through external event knowledge learning and polyhedral word embedding	13
Exploiting counter-examples for active learning with partial labels	13
Empirical Bayes linked matrix decomposition	13
Learning biologically-interpretable latent representations for gene expression data	13
An in-depth review and analysis of mode collapse in generative adversarial networks	13
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior	13
Targeted adversarial attacks on wind power forecasts	13
Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing	12
Scale-preserving automatic concept extraction (SPACE)	12
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity	12
Online AutoML: an adaptive AutoML framework for online learning	12
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media	12
Constrained regret minimization for multi-criterion multi-armed bandits	12
Attacking neural machine translations via hybrid attention learning	12
Large-scale pinball twin support vector machines	12
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	12
Improving kernel online learning with a snapshot memory	12
A new formulation of Lipschitz constrained with functional gradient learning for GANs	12
Understanding prediction discrepancies in classification	12
On the robustness of randomized classifiers to adversarial examples	12
Efficient and interpretable raw audio classification with diagonal state space models	12
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro	12
Online binary classification from similar and dissimilar data	11
Improving interpretability via regularization of neural activation sensitivity	11
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	11
An interpretable sample selection framework against numerical label noise	11
Weighted neural tangent kernel: a generalized and improved network-induced kernel	11
Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions	11
Robust matrix estimations meet Frank–Wolfe algorithm	11
Transfer and share: semi-supervised learning from long-tailed data	11
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation	11
Understanding generalization error of SGD in nonconvex optimization	11
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	10
Testing conditional independence in supervised learning algorithms	10
Gradient boosted trees for evolving data streams	10
Correction to: Modeling PU learning using probabilistic logic programming	10
Adversarial concept drift detection under poisoning attacks for robust data stream mining	10
Empirical analysis of performance assessment for imbalanced classification	10
Efficient federated unlearning under plausible deniability	10
Search or split: policy gradient with adaptive policy space	10
Quantitative Gaussian approximation of randomly initialized deep neural networks	10
Fraud detection with natural language processing	10
Troubleshooting image segmentation models with human-in-the-loop	9
Permutation-invariant linear classifiers	9
Traditional and context-specific spam detection in low resource settings	9
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	9
Hitting the target: stopping active learning at the cost-based optimum	9
Jaccard-constrained dense subgraph discovery	9
Online learning of network bottlenecks via minimax paths	9
Lifted model checking for relational MDPs	9
Calibrated explanations for regression	9
Pruning during training by network efficacy modeling	9
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models	9
Semi-supervised Latent Block Model with pairwise constraints	8
Information bottleneck and selective noise supervision for zero-shot learning	8
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?	8
Time-aware tensor decomposition for sparse tensors	8
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	8
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	8
On the benefits of representation regularization in invariance based domain generalization	8
Fast linear model trees by PILOT	8
Diverse and consistent multi-view networks for semi-supervised regression	8
DEFT: distilling entangled factors by preventing information diffusion	8
Understanding transfer learning and gradient-based meta-learning techniques	8
Wasserstein dropout	8
Learning answer set programs with aggregates via sampling and genetic programming	8
Efficient fair principal component analysis	8
How to be fair? A study of label and selection bias	8
Explaining short text classification with diverse synthetic exemplars and counter-exemplars	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
InfoGram and admissible machine learning	8
Achieving adversarial robustness via sparsity	8
Correction to: A neural meta-model for predicting winter wheat crop yield	8
CoMadOut—a robust outlier detection algorithm based on CoMAD	7
Nrat: towards adversarial training with inherent label noise	7
Explaining recommendation system using counterfactual textual explanations	7

Learning to rank anomalies: scalar performance criteria and maximization of rank statistics	7
Spatiotemporal-view member preference contrastive representation learning for group recommendation	7
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows	7
Dense subgraphs induced by edge labels	7
Hierarchically structured task-agnostic continual learning	7
Relational data embeddings for feature enrichment with background information	7
On metafeatures’ ability of implicit concept identification	7
A unified framework for online trip destination prediction	7
Adaptive adapter routing for long-tailed class-incremental learning	7
Temporal ensemble of multiple patterns’ instances for continuous prediction of events	7
Generalizing universal adversarial perturbations for deep neural networks	7
Generalized vec trick for fast learning of pairwise kernel models	7
Distribution-free conformal joint prediction regions for neural marked temporal point processes	7
Polynomial-based graph convolutional neural networks for graph classification	7
Graph spring neural ODEs for link sign prediction	7
Unified convergence analysis for adaptive optimization with moving average estimator	7
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +	7
Hellinger distance decision trees for PU learning in imbalanced data sets	7
Gradient descent fails to learn high-frequency functions and modular arithmetic	7
Stress detection with encoding physiological signals and convolutional neural network	6
Gradient-based causal discovery with latent variables	6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression	6
The class imbalance problem in deep learning	6
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	6
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	6
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency	6
Ranking-preserved generative label enhancement	6
When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days	6
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting	6
Sanitized clustering against confounding bias	6
In-game soccer outcome prediction with offline reinforcement learning	6
Black-box Bayesian adversarial attack with transferable priors	6
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance	6
State-novelty guided action persistence in deep reinforcement learning	6
Improve generated adversarial imitation learning with reward variance regularization	6
Recurrent segmentation meets block models in temporal networks	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
Bayesian mixture variational autoencoders for multi-modal learning	6
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings	6
DOC$$^3$$: deep one class classification using contradictions	5
Deep learning and multivariate time series for cheat detection in video games	5
Meta-interpretive learning as metarule specialisation	5
Dual-domain graph convolutional networks for skeleton-based action recognition	5
MapFlow: latent transition via normalizing flow for unsupervised domain adaptation	5
Jensen–Tsallis divergence for supervised classification under data imbalance	5
End-to-end entity-aware neural machine translation	5
Efficient SVDD sampling with approximation guarantees for the decision boundary	5
STUDD: a student–teacher method for unsupervised concept drift detection	5
Towards enabling learnware to handle heterogeneous feature spaces	5
Leveraging differentiable NAS and abstract genetic algorithms for optimizing on-mobile VSR performance	5
Tight mixed-integer optimization formulations for prescriptive trees	5
Tree-based dynamic classifier chains	5
Sandbox: safeguarded multi-label learning through safe optimal transport	5
Conformal load prediction with transductive graph autoencoders	5
Sparse classification: a scalable discrete optimization perspective	5
Exposing and explaining fake news on-the-fly	5
Optimal policy trees	5
Perfect counterfactuals in imperfect worlds: modelling noisy implementation of actions in sequential algorithmic recourse	5
HFIA: a parasitic feature inference attack and gradient-based defense strategy in SplitNN-based vertical federated learning	5
Active learning algorithm through the lens of rejection arguments	5
A stochastic approach to handle resource constraints as knapsack problems in ensemble pruning	5
MLife: a lite framework for machine learning lifecycle initialization	5
Multi-target prediction for dummies using two-branch neural networks	5
A generalized Weisfeiler-Lehman graph kernel	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
GVFs in the real world: making predictions online for water treatment	5
Persian offensive language detection	5
Improving graph neural networks through feature importance learning	5
Improving text processing via adversarial low-rank adaptation	5
DPG: a model to build feature subspace against adversarial patch attack	5
Hybrid additive modeling with partial dependence for supervised regression and dynamical systems forecasting	5
Dynamic weighted ensemble for diarrhoea incidence predictions	5
Learning with risks based on M-location	5
A new adaptive gradient method with gradient decomposition	5
Automotive fault nowcasting with machine learning and natural language processing	5
A brain-inspired algorithm for training highly sparse neural networks	4
Fast spectral analysis for approximate nearest neighbor search	4
Learning from crowds with sparse and imbalanced annotations	4
Sparse and smooth additive isotonic model in high-dimensional settings	4
Boundary-restricted metric learning	4
Gentle local robustness implies generalization	4
Composite score for anomaly detection in imbalanced real-world industrial dataset	4
Speeding up neural network robustness verification via algorithm configuration and an optimised mixed integer linear programming solver portfolio	4
GS2P: a generative pre-trained learning to rank model with over-parameterization for web-scale search	4
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models	4
Drop-in efficient self-attention approximation method	4
Lead–lag detection and network clustering for multivariate time series with an application to the US equity market	4
Classification with costly features in hierarchical deep sets	4
Differentiable learning of matricized DNFs and its application to Boolean networks	4
Deep Errors-in-Variables using a diffusion model	4
Decentralized Bayesian learning with Metropolis-adjusted Hamiltonian Monte Carlo	4
Margin distribution and structural diversity guided ensemble pruning	4
Naive automated machine learning	4