Machine Learning

Article	Citations
Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods	621
Challenges of real-world reinforcement learning: definitions, benchmarks and analysis	212
HIVE-COTE 2.0: a new meta ensemble for time series classification	138
Evaluating time series forecasting models: an empirical study on performance estimation methods	132
Regularisation of neural networks by enforcing Lipschitz continuity	110
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19	108
F*: an interpretable transformation of the F-measure	83
LoRAS: an oversampling approach for imbalanced datasets	78
High-dimensional Bayesian optimization using low-dimensional feature spaces	69
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics	68
How to measure uncertainty in uncertainty sampling for active learning	67
Density-based weighting for imbalanced regression	65
OWL2Vec*: embedding of OWL ontologies	64
Imbalanced regression and extreme value prediction	56
Loss aware post-training quantization	51
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	50
Stronger data poisoning attacks break data sanitization defenses	47
Spatial dependence between training and test sets: another pitfall of classification accuracy assessment in remote sensing	44
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	40
TRU-NET: a deep learning approach to high resolution prediction of rainfall	38
Special issue on feature engineering editorial	36
Semi-supervised semantic segmentation in Earth Observation: the MiniFrance suite, dataset analysis and multi-task network study	32
Global optimization based on active preference learning with radial basis functions	32
Scenic: a language for scenario specification and data generation	30
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	29

Conditional variance penalties and domain shift robustness	29
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions	28
A deep reinforcement learning framework for continuous intraday market bidding	27
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks	26
Tensor Q-rank: new data dependent definition of tensor rank	26
CPAS: the UK’s national machine learning-based hospital capacity planning system for COVID-19	26
Boost image captioning with knowledge reasoning	25
Transforming variables to central normality	25
Machine unlearning: linear filtration for logit-based classifiers	25
Boosting Poisson regression models with telematics car driving data	25
Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation	24
Learning programs by learning from failures	24
Inductive logic programming at 30	23
An empirical comparison between stochastic and deterministic centroid initialisation for K-means variations	22
Classifier calibration: a survey on how to assess and improve predicted class probabilities	21
Embed2Detect: temporally clustered embedded words for event detection in social media	21
Conditional t-SNE: more informative t-SNE embeddings	21
The class imbalance problem in deep learning	19
Testing conditional independence in supervised learning algorithms	19
Beneficial and harmful explanatory machine learning	19
Bandit algorithms to personalize educational chatbots	18
BT-Unet: A self-supervised learning framework for biomedical image segmentation using barlow twins with U-net models	18
A network-based positive and unlabeled learning approach for fake news detection	17
Incorporating symbolic domain knowledge into graph neural networks	17
Large-scale pinball twin support vector machines	17
Imputation of clinical covariates in time series	16
Statistical hierarchical clustering algorithm for outlier detection in evolving data streams	16
DAFS: a domain aware few shot generative model for event detection	16
Optimal survival trees	16
On the sample complexity of actor-critic method for reinforcement learning with function approximation	16
Satellite derived bathymetry using deep learning	15
Grounded action transformation for sim-to-real reinforcement learning	15
End-to-end entity-aware neural machine translation	15
Fully convolutional open set segmentation	15
Sparse classification: a scalable discrete optimization perspective	14
Wavelet-packets for deepfake image analysis and detection	14
Domain adversarial neural networks for domain generalization: when it works and how to improve	14
Embedding to reference t-SNE space addresses batch effects in single-cell classification	14
Optimal policy trees	14
Forecasting directional bitcoin price returns using aspect-based sentiment analysis on online text data	14
Global optimization of objective functions represented by ReLU networks	13
SAED: self-attentive energy disaggregation	13
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mapping	13
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	13
Can language models automate data wrangling?	13
Beyond confusion matrix: learning from multiple annotators with awareness of instance features	13
Graph-based semi-supervised learning via improving the quality of the graph dynamically	12
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification	12
Importance sampling in reinforcement learning with an estimated behavior policy	12
A study of BERT for context-aware neural machine translation	12

STUDD: a student–teacher method for unsupervised concept drift detection	12
WEASEL 2.0: a random dilated dictionary transform for fast, accurate and memory constrained time series classification	12
Receiver operating characteristic (ROC) curves: equivalences, beta model, and minimum distance estimation	12
DIMBA: discretely masked black-box attack in single object tracking	11
RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification	11
Joint optimization of an autoencoder for clustering and embedding	11
Toward optimal probabilistic active learning using a Bayesian approach	11
Efficient fair principal component analysis	11
Deep learning and multivariate time series for cheat detection in video games	11
VEST: automatic feature engineering for forecasting	11
Traditional and context-specific spam detection in low resource settings	11
Learning from self-discrepancy via multiple co-teaching for cross-domain person re-identification	10
Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems	10
Linear support vector regression with linear constraints	10
A review on instance ranking problems in statistical learning	10
Lead–lag detection and network clustering for multivariate time series with an application to the US equity market	10
An adaptive polyak heavy-ball method	10
Non-technical losses detection in energy consumption focusing on energy recovery and explainability	10
Relating instance hardness to classification performance in a dataset: a visual approach	10
Early classification of time series	10
SLISEMAP: supervised dimensionality reduction through local explanations	10
InfoGram and admissible machine learning	10
Improve generated adversarial imitation learning with reward variance regularization	9
Distance metric learning for graph structured data	9
Dual-domain graph convolutional networks for skeleton-based action recognition	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
Polynomial-based graph convolutional neural networks for graph classification	9
Scrutinizing XAI using linear ground-truth data with suppressor variables	9
SPEED: secure, PrivatE, and efficient deep learning	9
Online AutoML: an adaptive AutoML framework for online learning	9
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	9
Weakly supervised change detection using guided anisotropic diffusion	9
JGPR: a computationally efficient multi-target Gaussian process regression algorithm	9
Ada-boundary: accelerating DNN training via adaptive boundary batch selection	9
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	8
An instance-dependent simulation framework for learning with label noise	8
Multi-target prediction for dummies using two-branch neural networks	8
Beyond graph neural networks with lifted relational neural networks	8
Receiver operating characteristic (ROC) movies, universal ROC (UROC) curves, and coefficient of predictive ability (CPA)	8
IntelligentPooling: practical Thompson sampling for mHealth	8
Automatic discovery of interpretable planning strategies	8
An improved evolutionary wrapper-filter feature selection approach with a new initialisation scheme	8
Ordinal regression with explainable distance metric learning based on ordered sequences	8
Bimodal variational autoencoder for audiovisual speech recognition	8
Generation, augmentation, and alignment: a pseudo-source domain based method for source-free domain adaptation	8
Handling epistemic and aleatory uncertainties in probabilistic circuits	8
Deep multimodal representation learning for generalizable person re-identification	8
Unified SVM algorithm based on LS-DC loss	8
Considerations when learning additive explanations for black-box models	8
A generalized Weisfeiler-Lehman graph kernel	8
Efficient learning of large sets of locally optimal classification rules	8
SDANet: spatial deep attention-based for point cloud classification and segmentation	8
Optimal transport for conditional domain matching and label shift	8
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
Multiple clusterings of heterogeneous information networks	7
MLife: a lite framework for machine learning lifecycle initialization	7
Hybrid approaches to optimization and machine learning methods: a systematic literature review	7
Robust supervised topic models under label noise	7
Hierarchical optimal transport for unsupervised domain adaptation	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
Explainable online ensemble of deep neural network pruning for time series forecasting	7
Model selection in reconciling hierarchical time series	7
Multiscale principle of relevant information for hyperspectral image classification	7
Speeding-up one-versus-all training for extreme classification via mean-separating initialization	7
Skew Gaussian processes for classification	7
Active learning for data streams: a survey	7
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare	7
A decision-theoretic approach for model interpretability in Bayesian framework	7
Inclusion of domain-knowledge into GNNs using mode-directed inverse entailment	7
Automated adaptation strategies for stream learning	7
Understanding CNN fragility when learning with imbalanced data	7
Deep learning’s shallow gains: a comparative evaluation of algorithms for automatic music generation	7
Algorithm selection on a meta level	7
Unsupervised anomaly detection in multivariate time series with online evolving spiking neural networks	7
TSFuse: automated feature construction for multiple time series data	7
A survey of class-imbalanced semi-supervised learning	6
Learning subtree pattern importance for Weisfeiler-Lehman based graph kernels	6

Multi-label feature ranking with ensemble methods	6
Ensemble and continual federated learning for classification tasks	6
Online strongly convex optimization with unknown delays	6
Metrics and methods for robustness evaluation of neural networks with generative models	6
Spanning attack: reinforce black-box attacks with unlabeled data	6
Topic extraction from extremely short texts with variational manifold regularization	6
Adversarial learning for counterfactual fairness	6
Inductive learning of answer set programs for autonomous surgical task planning	6
Achieving adversarial robustness via sparsity	6
Naive automated machine learning	6
QuicK-means: accelerating inference for K-means by learning fast transforms	6
Robust federated learning under statistical heterogeneity via hessian-weighted aggregation	6
Binary classification with ambiguous training data	6
Protect privacy of deep classification networks by exploiting their generative power	6
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	6
The flowing nature matters: feature learning from the control flow graph of source code for bug localization	6
Generating contrastive explanations for inductive logic programming based on a near miss approach	5
Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach	5
Generating probabilistic safety guarantees for neural network controllers	5
Coefficient tree regression: fast, accurate and interpretable predictive modeling	5
Learning from interpretation transition using differentiable logic programming semantics	5
Nested aggregation of experts using inducing points for approximated Gaussian process regression	5
Inverse reinforcement learning in contextual MDPs	5
Optimal data collection design in machine learning: the case of the fixed effects generalized least squares panel data model	5
Byzantine-robust distributed sparse learning for M-estimation	5
Troubleshooting image segmentation models with human-in-the-loop	5
Clustered and deep echo state networks for signal noise reduction	5
Bayesian optimization with approximate set kernels	5
MODES: model-based optimization on distributed embedded systems	5
Analysis of regularized least-squares in reproducing kernel Kreĭn spaces	5
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	5
Generalizing universal adversarial perturbations for deep neural networks	5
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	5
Time-aware tensor decomposition for sparse tensors	5
CMD: controllable matrix decomposition with global optimization for deep neural network compression	5
Libsignal: an open library for traffic signal control	5
Pruning convolutional neural networks via filter similarity analysis	5
Distillation of weighted automata from recurrent neural networks using a spectral approach	5
Interpreting machine-learning models in transformed feature space with an application to remote-sensing classification	5
Lipschitzness is all you need to tame off-policy generative adversarial imitation learning	5
Multiway p-spectral graph cuts on Grassmann manifolds	5
Explaining classifiers by constructing familiar concepts	5
Re-thinking model robustness from stability: a new insight to defend adversarial examples	5
Estimation of multidimensional item response theory models with correlated latent variables using variational autoencoders	5
Federated learning with superquantile aggregation for heterogeneous data	5
Embedding and extraction of knowledge in tree ensemble classifiers	5
Stateless neural meta-learning using second-order gradients	5
Incremental predictive clustering trees for online semi-supervised multi-target regression	5
Partially observable environment estimation with uplift inference for reinforcement learning based recommendation	5
An extended DEIM algorithm for subset selection and class identification	5
Are LSTMs good few-shot learners?	5
Concentration bounds for temporal difference learning with linear function approximation: the case of batch data and uniform sampling	5
ReliefE: feature ranking in high-dimensional spaces via manifold embeddings	4
An accurate, scalable and verifiable protocol for federated differentially private averaging	4
Chinese character recognition with radical-structured stroke trees	4
Tensor decision trees for continual learning from drifting data streams	4
Hyperparameter importance and optimization of quantum neural networks across small datasets	4
Recursive tree grammar autoencoders	4
3DVerifier: efficient robustness verification for 3D point cloud models	4
Hitting the target: stopping active learning at the cost-based optimum	4
Diametrical Risk Minimization: theory and computations	4
Order preserving hierarchical agglomerative clustering	4
Explainable reinforcement learning (XRL): a systematic literature review and taxonomy	4
Machine learning with a reject option: a survey	4
Gaussian processes with skewed Laplace spectral mixture kernels for long-term forecasting	4
Heterogeneous graph embedding with single-level aggregation and infomax encoding	4
The backbone method for ultra-high dimensional sparse machine learning	4
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	4
Greedy structure learning from data that contain systematic missing values	4
Sampled Gromov Wasserstein	4
Can metafeatures help improve explanations of prediction models when using behavioral and textual data?	4
Adversarial concept drift detection under poisoning attacks for robust data stream mining	4
Fairness seen as global sensitivity analysis	4
Efficient Weingarten map and curvature estimation on manifolds	4
Incremental permutation feature importance (iPFI): towards online explanations on data streams	4
Few-shot learning for spatial regression via neural embedding-based Gaussian processes	4
MAGMA: inference and prediction using multi-task Gaussian processes with common mean	4
Aliasing and adversarial robust generalization of CNNs	4
Feature ranking for semi-supervised learning	4
Information bottleneck and selective noise supervision for zero-shot learning	4
SVRG meets AdaGrad: painless variance reduction	4
Randomized approximate class-specific kernel spectral regression analysis for large-scale face verification	4
Symbolic DNN-Tuner	4
Semi-Lipschitz functions and machine learning for discrete dynamical systems on graphs	4
Online learning of network bottlenecks via minimax paths	4
Robust generative adversarial network	4
Machine truth serum: a surprisingly popular approach to improving ensemble methods	4
State-based episodic memory for multi-agent reinforcement learning	4
High-dimensional correlation matrix estimation for general continuous data with Bagging technique	4
Parametric non-parallel support vector machines for pattern classification	4
Kernel machines for current status data	4
Semi-supervised Latent Block Model with pairwise constraints	3
Adaptive infinite dropout for noisy and sparse data streams	3
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	3
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	3