Machine Learning

Article	Citations
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods	470
Learning from positive and unlabeled data: a survey	223
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis	152
Evaluating time series forecasting models: an empirical study on performance estimation methods	100
HIVE-COTE 2.0: a new meta ensemble for time series classification	96
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19	96
Regularisation of neural networks by enforcing Lipschitz continuity	86
LoRAS: an oversampling approach for imbalanced datasets	67
F*: an interpretable transformation of the F-measure	58
High-dimensional Bayesian optimization using low-dimensional feature spaces	53
OWL2Vec*: embedding of OWL ontologies	50
Bonsai: diverse and shallow trees for extreme multi-label classification	48
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics	46
How to measure uncertainty in uncertainty sampling for active learning	45
Imbalanced regression and extreme value prediction	42
Density-based weighting for imbalanced regression	42
Loss aware post-training quantization	42
The voice of optimization	39
Engineering problems in machine learning systems	37
Interpretable clustering: an optimization approach	33
Double random forest	33
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	32
TRU-NET: a deep learning approach to high resolution prediction of rainfall	32
Spatial dependence between training and test sets: another pitfall of classification accuracy assessment in remote sensing	31
Stronger data poisoning attacks break data sanitization defenses	31

Global optimization based on active preference learning with radial basis functions	27
Semi-supervised semantic segmentation in Earth Observation: the MiniFrance suite, dataset analysis and multi-task network study	26
Conditional variance penalties and domain shift robustness	26
Transforming variables to central normality	23
A deep reinforcement learning framework for continuous intraday market bidding	23
Special issue on feature engineering editorial	22
CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19	22
Tensor Q-rank: new data dependent definition of tensor rank	20
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	20
Boosting Poisson regression models with telematics car driving data	20
Boost image captioning with knowledge reasoning	20
Propositionalization and embeddings: two sides of the same coin	20
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks	19
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions	19
Learning programs by learning from failures	19
Embed2Detect: temporally clustered embedded words for event detection in social media	18
An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations	18
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	17
Scenic: a language for scenario specification and data generation	17
Beneficial and harmful explanatory machine learning	17
Inductive logic programming at 30	16
Incorporating symbolic domain knowledge into graph neural networks	15
Large-scale pinball twin support vector machines	15
Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation	15
Satellite derived bathymetry using deep learning	14
Conditional t-SNE: more informative t-SNE embeddings	14
Machine unlearning: linear filtration for logit-based classifiers	14
Bandit algorithms to personalize educational chatbots	13
Imputation of clinical covariates in time series	13
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models	13
End-to-end entity-aware neural machine translation	13
Testing conditional independence in supervised learning algorithms	13
Statistical hierarchical clustering algorithm for outlier detection in evolving data streams	12
Sparse classification: a scalable discrete optimization perspective	12
Ensembles of extremely randomized predictive clustering trees for predicting structured outputs	12
On the sample complexity of actor-critic method for reinforcement learning with function approximation	11
SAED: self-attentive energy disaggregation	11
Embedding-based Silhouette community detection	11
Toward optimal probabilistic active learning using a Bayesian approach	11
DAFS: a domain aware few shot generative model for event detection	11
Fully convolutional open set segmentation	11
A network-based positive and unlabeled learning approach for fake news detection	10
Optimal survival trees	10
A study of BERT for context-aware neural machine translation	10
Grounded action transformation for sim-to-real reinforcement learning	10
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping	10
Graph-based semi-supervised learning via improving the quality of the graph dynamically	10
Forecasting directional bitcoin price returns using aspect-based sentiment analysis on online text data	10
Importance sampling in reinforcement learning with an estimated behavior policy	10
Traditional and context-specific spam detection in low resource settings	10

Optimal policy trees	9
Classifier calibration: a survey on how to assess and improve predicted class probabilities	9
Beyond confusion matrix: learning from multiple annotators with awareness of instance features	9
RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification	9
Robust classification via MOM minimization	9
Receiver operating characteristic (ROC) curves: equivalences, beta model, and minimum distance estimation	9
VEST: automatic feature engineering for forecasting	9
Weakly supervised change detection using guided anisotropic diffusion	9
SPEED: secure, PrivatE, and efficient deep learning	9
Global optimization of objective functions represented by ReLU networks	9
Embedding to reference t-SNE space addresses batch effects in single-cell classification	9
A review on instance ranking problems in statistical learning	9
Using error decay prediction to overcome practical issues of deep active learning for named entity recognition	8
DIMBA: discretely masked black-box attack in single object tracking	8
Anomaly detection with inexact labels	8
Relating instance hardness to classification performance in a dataset: a visual approach	8
Deep learning and multivariate time series for cheat detection in video games	8
Unsupervised representation learning with Minimax distance measures	8
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	8
The class imbalance problem in deep learning	8
Lead–lag detection and network clustering for multivariate time series with an application to the US equity market	8
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification	8
Improve generated adversarial imitation learning with reward variance regularization	8
Early classification of time series	8
Linear support vector regression with linear constraints	8
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning	8
JGPR: a computationally efficient multi-target Gaussian process regression algorithm	8
An improved evolutionary wrapper-filter feature selection approach with a new initialisation scheme	7
Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP	7
Wavelet-packets for deepfake image analysis and detection	7
SDANet: spatial deep attention-based for point cloud classification and segmentation	7
On the benefits of representation regularization in invariance based domain generalization	7
Joint optimization of an autoencoder for clustering and embedding	7
Can language models automate data wrangling?	7
Stream-based active learning for sliding windows under the influence of verification latency	7
Automatic discovery of interpretable planning strategies	7
Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment	7
Efficient fair principal component analysis	7
Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification	7
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems	7
RADE: resource-efficient supervised anomaly detection using decision tree-based ensemble methods	7
Analyzing and repairing concept drift adaptation in data stream classification	7
Non-technical losses detection in energy consumption focusing on energy recovery and explainability	7
InfoGram and admissible machine learning	7
Handling epistemic and aleatory uncertainties in probabilistic circuits	6
Polynomial-based graph convolutional neural networks for graph classification	6
Transfer learning by mapping and revising boosted relational dependency networks	6
SLISEMAP: supervised dimensionality reduction through local explanations	6
Ada-boundary: accelerating DNN training via adaptive boundary batch selection	6
Dual-domain graph convolutional networks for skeleton-based action recognition	6
Model selection in reconciling hierarchical time series	6
A generalized Weisfeiler-Lehman graph kernel	6
Multi-label feature ranking with ensemble methods	6
Distance metric learning for graph structured data	6
Inductive learning of answer set programs for autonomous surgical task planning	6
An adaptive polyak heavy-ball method	6
STUDD: a student–teacher method for unsupervised concept drift detection	6
Beyond graph neural networks with lifted relational neural networks	6
Robust supervised topic models under label noise	6
Hierarchical optimal transport for unsupervised domain adaptation	6
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	6
Learning representations from dendrograms	6
Safety-constrained reinforcement learning with a distributional safety critic	6
Online AutoML: an adaptive AutoML framework for online learning	6
Multiscale principle of relevant information for hyperspectral image classification	6
MLife: a lite framework for machine learning lifecycle initialization	5
Skew Gaussian processes for classification	5
Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA)	5
TSFuse: automated feature construction for multiple time series data	5
Embedding and extraction of knowledge in tree ensemble classifiers	5
IntelligentPooling: practical Thompson sampling for mHealth	5
Scrutinizing XAI using linear ground-truth data with suppressor variables	5
Protect privacy of deep classification networks by exploiting their generative power	5
Automated adaptation strategies for stream learning	5
Ordinal regression with explainable distance metric learning based on ordered sequences	5
Multi-target prediction for dummies using two-branch neural networks	5
Bimodal variational autoencoder for audiovisual speech recognition	5
Generalizing universal adversarial perturbations for deep neural networks	5
Re-thinking model robustness from stability: a new insight to defend adversarial examples	5
Optimal transport for conditional domain matching and label shift	5

Time-aware tensor decomposition for sparse tensors	5
A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS)	5
Deep multimodal representation learning for generalizable person re-identification	5
Stateless neural meta-learning using second-order gradients	5
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation	5
Incremental predictive clustering trees for online semi-supervised multi-target regression	5
Concentration bounds for temporal difference learning with linear function approximation: the case of batch data and uniform sampling	5
Topic extraction from extremely short texts with variational manifold regularization	5
Considerations when learning additive explanations for black-box models	5
Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks	5
Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach	5
A decision-theoretic approach for model interpretability in Bayesian framework	5
CMD: controllable matrix decomposition with global optimization for deep neural network compression	5
Coefficient tree regression: fast, accurate and interpretable predictive modeling	5
WEASEL 2.0: a random dilated dictionary transform for fast, accurate and memory constrained time series classification	5
The flowing nature matters: feature learning from the control flow graph of source code for bug localization	5
Explainable online ensemble of deep neural network pruning for time series forecasting	5
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning	5
Unified SVM algorithm based on LS-DC loss	5
Binary classification with ambiguous training data	5
Greedy structure learning from data that contain systematic missing values	4
3DVerifier: efficient robustness verification for 3D point cloud models	4
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	4
High-dimensional correlation matrix estimation for general continuous data with Bagging technique	4
Efficient Weingarten map and curvature estimation on manifolds	4
Efficient learning of large sets of locally optimal classification rules	4
Generating contrastive explanations for inductive logic programming based on a near miss approach	4
Domain adversarial neural networks for domain generalization: when it works and how to improve	4
Nested aggregation of experts using inducing points for approximated Gaussian process regression	4
Inverse reinforcement learning in contextual MDPs	4
Optimal data collection design in machine learning: the case of the fixed effects generalized least squares panel data model	4
Co-eye: a multi-resolution ensemble classifier for symbolically approximated time series	4
Understanding CNN fragility when learning with imbalanced data	4
Analysis of regularized least-squares in reproducing kernel Kreĭn spaces	4
Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels	4
Explaining classifiers by constructing familiar concepts	4
Fairness seen as global sensitivity analysis	4
Multiple clusterings of heterogeneous information networks	4
Metrics and methods for robustness evaluation of neural networks with generative models	4
Bayesian optimization with approximate set kernels	4
An instance-dependent simulation framework for learning with label noise	4
Clustered and deep echo state networks for signal noise reduction	4
Spanning attack: reinforce black-box attacks with unlabeled data	4
MODES: model-based optimization on distributed embedded systems	4
Generating probabilistic safety guarantees for neural network controllers	4
Tensor decision trees for continual learning from drifting data streams	3
Adaptive infinite dropout for noisy and sparse data streams	3
Semi-supervised Latent Block Model with pairwise constraints	3
Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification	3
Sampled Gromov Wasserstein	3
Few-shot learning for spatial regression via neural embedding-based Gaussian processes	3
Predicting rice phenotypes with meta and multi-target learning	3
Gaussian processes with skewed Laplace spectral mixture kernels for long-term forecasting	3
ReliefE: feature ranking in high-dimensional spaces via manifold embeddings	3
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	3
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	3
Dealing with the unevenness: deeper insights in graph-based attack and defense	3
Can metafeatures help improve explanations of prediction models when using behavioral and textual data?	3
Probabilistic inductive constraint logic	3
Semi-Lipschitz functions and machine learning for discrete dynamical systems on graphs	3
A survey of class-imbalanced semi-supervised learning	3
Learning with mitigating random consistency from the accuracy measure	3
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation	3
ZipLine: an optimized algorithm for the elastic bulk synchronous parallel model	3
Root-finding approaches for computing conformal prediction set	3
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare	3
Online strongly convex optimization with unknown delays	3
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	3
QuicK-means: accelerating inference for K-means by learning fast transforms	3
Randomized approximate class-specific kernel spectral regression analysis for large-scale face verification	3
Large scale multi-label learning using Gaussian processes	3
Multiway p-spectral graph cuts on Grassmann manifolds	3
Algorithm selection on a meta level	3
Speeding-up one-versus-all training for extreme classification via mean-separating initialization	3
Top program construction and reduction for polynomial time Meta-Interpretive learning	2
Improving deep label noise learning with dual active label correction	2
Machine truth serum: a surprisingly popular approach to improving ensemble methods	2
Recursive tree grammar autoencoders	2
Parameter identifiability of a deep feedforward ReLU neural network	2
Information bottleneck and selective noise supervision for zero-shot learning	2
WINTENDED: WINdowed TENsor decomposition for Densification Event Detection in time-evolving networks	2
SVRG meets AdaGrad: painless variance reduction	2
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	2
Troubleshooting image segmentation models with human-in-the-loop	2
Achieving adversarial robustness via sparsity	2
One-Stage Tree: end-to-end tree builder and pruner	2
Learning system parameters from turing patterns	2
Ensemble and continual federated learning for classification tasks	2
Federated learning with superquantile aggregation for heterogeneous data	2
Learning from interpretation transition using differentiable logic programming semantics	2
Online learning of network bottlenecks via minimax paths	2
Hitting the target: stopping active learning at the cost-based optimum	2
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	2
Generalized vec trick for fast learning of pairwise kernel models	2
Symbolic DNN-Tuner	2