Machine Learning

Article	Citations
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods	653
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis	225
HIVE-COTE 2.0: a new meta ensemble for time series classification	143
Regularisation of neural networks by enforcing Lipschitz continuity	112
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19	110
F*: an interpretable transformation of the F-measure	84
LoRAS: an oversampling approach for imbalanced datasets	80
How to measure uncertainty in uncertainty sampling for active learning	71
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics	71
Density-based weighting for imbalanced regression	68
OWL2Vec*: embedding of OWL ontologies	67
Loss aware post-training quantization	55
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	51
Stronger data poisoning attacks break data sanitization defenses	48
Spatial dependence between training and test sets: another pitfall of classification accuracy assessment in remote sensing	45
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	41
TRU-NET: a deep learning approach to high resolution prediction of rainfall	38
Semi-supervised semantic segmentation in Earth Observation: the MiniFrance suite, dataset analysis and multi-task network study	37
Special issue on feature engineering editorial	36
Global optimization based on active preference learning with radial basis functions	33
Conditional variance penalties and domain shift robustness	30
Scenic: a language for scenario specification and data generation	30
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions	30
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	29
Machine unlearning: linear filtration for logit-based classifiers	29

A deep reinforcement learning framework for continuous intraday market bidding	28
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks	27
CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19	26
Boosting Poisson regression models with telematics car driving data	26
Transforming variables to central normality	26
Tensor Q-rank: new data dependent definition of tensor rank	26
Learning programs by learning from failures	24
Inductive logic programming at 30	24
Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation	24
An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations	23
Classifier calibration: a survey on how to assess and improve predicted class probabilities	22
Embed2Detect: temporally clustered embedded words for event detection in social media	22
Testing conditional independence in supervised learning algorithms	21
Conditional t-SNE: more informative t-SNE embeddings	21
The class imbalance problem in deep learning	20
Beneficial and harmful explanatory machine learning	19
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models	19
Bandit algorithms to personalize educational chatbots	18
Satellite derived bathymetry using deep learning	17
On the sample complexity of actor-critic method for reinforcement learning with function approximation	17
End-to-end entity-aware neural machine translation	17
A network-based positive and unlabeled learning approach for fake news detection	17
Large-scale pinball twin support vector machines	17
Incorporating symbolic domain knowledge into graph neural networks	17
Optimal survival trees	17
Imputation of clinical covariates in time series	16
DAFS: a domain aware few shot generative model for event detection	16
Grounded action transformation for sim-to-real reinforcement learning	15
Hybrid approaches to optimization and machine learning methods: a systematic literature review	15
Can language models automate data wrangling?	15
Fully convolutional open set segmentation	15
Sparse classification: a scalable discrete optimization perspective	14
Domain adversarial neural networks for domain generalization: when it works and how to improve	14
Wavelet-packets for deepfake image analysis and detection	14
Optimal policy trees	14
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping	14
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	14
Forecasting directional bitcoin price returns using aspect-based sentiment analysis on online text data	14
Embedding to reference t-SNE space addresses batch effects in single-cell classification	14
Beyond confusion matrix: learning from multiple annotators with awareness of instance features	13
A study of BERT for context-aware neural machine translation	13
Global optimization of objective functions represented by ReLU networks	13
SAED: self-attentive energy disaggregation	13
DIMBA: discretely masked black-box attack in single object tracking	12
Efficient fair principal component analysis	12
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification	12
WEASEL 2.0: a random dilated dictionary transform for fast, accurate and memory constrained time series classification	12
Graph-based semi-supervised learning via improving the quality of the graph dynamically	12
Relating instance hardness to classification performance in a dataset: a visual approach	12
Receiver operating characteristic (ROC) curves: equivalences, beta model, and minimum distance estimation	12

Importance sampling in reinforcement learning with an estimated behavior policy	12
STUDD: a student–teacher method for unsupervised concept drift detection	12
Lead–lag detection and network clustering for multivariate time series with an application to the US equity market	11
Toward optimal probabilistic active learning using a Bayesian approach	11
Traditional and context-specific spam detection in low resource settings	11
Joint optimization of an autoencoder for clustering and embedding	11
VEST: automatic feature engineering for forecasting	11
Deep learning and multivariate time series for cheat detection in video games	11
RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification	11
Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification	10
An adaptive polyak heavy-ball method	10
SLISEMAP: supervised dimensionality reduction through local explanations	10
Linear support vector regression with linear constraints	10
Scrutinizing XAI using linear ground-truth data with suppressor variables	10
Early classification of time series	10
InfoGram and admissible machine learning	10
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems	10
A review on instance ranking problems in statistical learning	10
Polynomial-based graph convolutional neural networks for graph classification	10
Non-technical losses detection in energy consumption focusing on energy recovery and explainability	10
Online AutoML: an adaptive AutoML framework for online learning	9
Improve generated adversarial imitation learning with reward variance regularization	9
Active learning for data streams: a survey	9
Optimal transport for conditional domain matching and label shift	9
Dual-domain graph convolutional networks for skeleton-based action recognition	9
SPEED: secure, PrivatE, and efficient deep learning	9
Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation	9
Handling epistemic and aleatory uncertainties in probabilistic circuits	9
Distance metric learning for graph structured data	9
Safety-constrained reinforcement learning with a distributional safety critic	9
Stream-based active learning for sliding windows under the influence of verification latency	9
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	9
Analyzing and repairing concept drift adaptation in data stream classification	9
Weakly supervised change detection using guided anisotropic diffusion	9
JGPR: a computationally efficient multi-target Gaussian process regression algorithm	9
An instance-dependent simulation framework for learning with label noise	8
Unified SVM algorithm based on LS-DC loss	8
A generalized Weisfeiler-Lehman graph kernel	8
Beyond graph neural networks with lifted relational neural networks	8
IntelligentPooling: practical Thompson sampling for mHealth	8
SDANet: spatial deep attention-based for point cloud classification and segmentation	8
An improved evolutionary wrapper-filter feature selection approach with a new initialisation scheme	8
Understanding CNN fragility when learning with imbalanced data	8
Considerations when learning additive explanations for black-box models	8
Bimodal variational autoencoder for audiovisual speech recognition	8
Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA)	8
Automatic discovery of interpretable planning strategies	8
Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment	8
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	8
Ordinal regression with explainable distance metric learning based on ordered sequences	8
Multi-target prediction for dummies using two-branch neural networks	8
Efficient learning of large sets of locally optimal classification rules	8
Algorithm selection on a meta level	8
Deep multimodal representation learning for generalizable person re-identification	8
Speeding-up one-versus-all training for extreme classification via mean-separating initialization	7
Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks	7
A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS)	7
On the benefits of representation regularization in invariance based domain generalization	7
Model selection in reconciling hierarchical time series	7
Multiscale principle of relevant information for hyperspectral image classification	7
Robust supervised topic models under label noise	7
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare	7
TSFuse: automated feature construction for multiple time series data	7
Multiple clusterings of heterogeneous information networks	7
Machine learning with a reject option: a survey	7
Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation	7
Hierarchical optimal transport for unsupervised domain adaptation	7
RADE: resource-efficient supervised anomaly detection using decision tree-based ensemble methods	7
Explainable online ensemble of deep neural network pruning for time series forecasting	7
Automated adaptation strategies for stream learning	7
MLife: a lite framework for machine learning lifecycle initialization	7
Metrics and methods for robustness evaluation of neural networks with generative models	6
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning	6
Binary classification with ambiguous training data	6
Explaining classifiers by constructing familiar concepts	6
Federated learning with superquantile aggregation for heterogeneous data	6
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	6
Ensemble and continual federated learning for classification tasks	6
Online strongly convex optimization with unknown delays	6
Bayesian optimization with approximate set kernels	6

QuicK-means: accelerating inference for K-means by learning fast transforms	6
Targeted adversarial attacks on wind power forecasts	6
Concentration bounds for temporal difference learning with linear function approximation: the case of batch data and uniform sampling	6
Topic extraction from extremely short texts with variational manifold regularization	6
Adversarial learning for counterfactual fairness	6
Protect privacy of deep classification networks by exploiting their generative power	6
Learning from interpretation transition using differentiable logic programming semantics	6
Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification	6
Inductive learning of answer set programs for autonomous surgical task planning	6
The flowing nature matters: feature learning from the control flow graph of source code for bug localization	6
Byzantine-robust distributed sparse learning for M-estimation	6
A survey of class-imbalanced semi-supervised learning	6
Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels	6
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation	6
Generalizing universal adversarial perturbations for deep neural networks	6
Chinese character recognition with radical-structured stroke trees	6
Time-aware tensor decomposition for sparse tensors	6
Achieving adversarial robustness via sparsity	6
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	6
Naive automated machine learning	6
Optimal data collection design in machine learning: the case of the fixed effects generalized least squares panel data model	5
Inverse reinforcement learning in contextual MDPs	5
Clustered and deep echo state networks for signal noise reduction	5
Multiway p-spectral graph cuts on Grassmann manifolds	5
MODES: model-based optimization on distributed embedded systems	5
Generating probabilistic safety guarantees for neural network controllers	5
Embedding and extraction of knowledge in tree ensemble classifiers	5
CMD: controllable matrix decomposition with global optimization for deep neural network compression	5
Troubleshooting image segmentation models with human-in-the-loop	5
Adversarial concept drift detection under poisoning attacks for robust data stream mining	5
FFNSL: Feed-Forward Neural-Symbolic Learner	5
Robust generative adversarial network	5
Generating contrastive explanations for inductive logic programming based on a near miss approach	5
Estimation of multidimensional item response theory models with correlated latent variables using variational autoencoders	5
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	5
Coefficient tree regression: fast, accurate and interpretable predictive modeling	5
Are LSTMs good few-shot learners?	5
Stateless neural meta-learning using second-order gradients	5
Pruning convolutional neural networks via filter similarity analysis	5
Distillation of weighted automata from recurrent neural networks using a spectral approach	5
An extended DEIM algorithm for subset selection and class identification	5
Analysis of regularized least-squares in reproducing kernel Kreĭn spaces	5
Re-thinking model robustness from stability: a new insight to defend adversarial examples	5
Information bottleneck and selective noise supervision for zero-shot learning	5
Nested aggregation of experts using inducing points for approximated Gaussian process regression	5
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation	5