Machine Learning

Article	Citations
The role of mutual information in variational classifiers	189
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations	113
Automated imbalanced classification via layered learning	113
Learning to bid and rank together in recommendation systems	104
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics	90
Adapting performance metrics for ordinal classification to interval scale: length matters	89
Robust reputation independence in ranking systems for multiple sensitive attributes	79
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers	72
Fairness seen as global sensitivity analysis	72
One-Stage Tree: end-to-end tree builder and pruner	70
Multimodal deep learning for cetacean distribution modeling of fin whales (Balaenoptera physalus) in the western Mediterranean Sea	60
Compositional scene modeling with global object-centric representations	51
Parameter identifiability of a deep feedforward ReLU neural network	51
Multi-objective multi-armed bandit with lexicographically ordered and satisficing objectives	50
Maximum causal entropy inverse constrained reinforcement learning	50
Spike2CGR: an efficient method for spike sequence classification using chaos game representation	47
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	43
A review on instance ranking problems in statistical learning	42
Semantic-enhanced graph neural networks with global context representation	41
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	40
Invariant representation learning via decoupling style and spurious features	39
Masked autoencoder for multiagent trajectories	34
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios	33
Optimal survival trees	31
Reinforcement learning for robotic manipulation using simulated locomotion demonstrations	30

GENs: generative encoding networks	30
Importance sampling in reinforcement learning with an estimated behavior policy	29
Chinese character recognition with radical-structured stroke trees	28
FairSwiRL: fair semi-supervised classification with representation learning	28
Maintaining AUC and H-measure over time	27
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization	27
A flexible class of dependence-aware multi-label loss functions	27
Responsible model deployment via model-agnostic uncertainty learning	26
Optimal transport for conditional domain matching and label shift	25
Towards accurate knowledge transfer via target-awareness representation disentanglement	24
Learning any memory-less discrete semantics for dynamical systems represented by logic programs	24
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization	23
WINTENDED: WINdowed TENsor decomposition for Densification Event Detection in time-evolving networks	23
Efficient private SCO for heavy-tailed data via averaged clipping	23
Trimming stability selection increases variable selection robustness	22
Transfer learning with pre-trained conditional generative models	21
Glacier: guided locally constrained counterfactual explanations for time series classification	21
On the usefulness of the fit-on-test view on evaluating calibration of classifiers	20
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation	20
A prompt-driven framework for multi-domain knowledge tracing	20
Dynamic datasets and market environments for financial reinforcement learning	19
Correction to: efficient generator of mathematical expressions for symbolic regression	19
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics	19
DIMBA: discretely masked black-box attack in single object tracking	19
A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with Skew Gaussian Processes	19
Generalization bounds for learning under graph-dependence: a survey	19
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	19
Aligning model outputs for class imbalanced non-IID federated learning	18
Data-aware process discovery for malware detection: an empirical study	18
Autoreplicative random forests with applications to missing value imputation	17
The backbone method for ultra-high dimensional sparse machine learning	17
Feature ranking for semi-supervised learning	17
Progressive semantic learning for unsupervised skeleton-based action recognition	17
SPA: A poisoning attack framework for graph neural networks through searching and pairing	17
A contrastive neural disentanglement approach for query performance prediction	16
Capturing the context-aware code change via dynamic control flow graph for commit message generation	16
Testing exchangeability in the batch mode with e-values and Markov alternatives	16
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker	15
Consensus–relevance kNN and covariate shift mitigation	15
Autoencoding slow representations for semi-supervised data-efficient regression	15
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior	15
A taxonomy of weight learning methods for statistical relational learning	15
Reducing classifier overconfidence against adversaries through graph algorithms	15
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning	14
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations	14
Multi-agent reinforcement learning for fast-timescale demand response of residential loads	14
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks	14
Context-aware spatio-temporal event prediction via convolutional Hawkes processes	14
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver	14
Event causality extraction through external event knowledge learning and polyhedral word embedding	13

How to measure uncertainty in uncertainty sampling for active learning	13
One transformer for all time series: representing and training with time-dependent heterogeneous tabular data	13
Coresets for kernel clustering	13
An in-depth review and analysis of mode collapse in generative adversarial networks	13
Imbalanced gradients: a subtle cause of overestimated adversarial robustness	13
Learning biologically-interpretable latent representations for gene expression data	13
Probabilistic scoring lists for interpretable machine learning	13
Targeted adversarial attacks on wind power forecasts	13
Online AutoML: an adaptive AutoML framework for online learning	12
Efficient and provable online reduced rank regression via online gradient descent	12
Understanding prediction discrepancies in classification	12
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	12
Constrained regret minimization for multi-criterion multi-armed bandits	12
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity	12
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media	12
Empirical Bayes linked matrix decomposition	12
Attacking neural machine translations via hybrid attention learning	12
Exploiting counter-examples for active learning with partial labels	12
Ordinal regression with explainable distance metric learning based on ordered sequences	12
A new formulation of Lipschitz constrained with functional gradient learning for GANs	11
Improving kernel online learning with a snapshot memory	11
On the robustness of randomized classifiers to adversarial examples	11
Quantitative Gaussian approximation of randomly initialized deep neural networks	11
Testing conditional independence in supervised learning algorithms	11
Scale-preserving automatic concept extraction (SPACE)	11
Efficient federated unlearning under plausible deniability	11
Large-scale pinball twin support vector machines	11
Gradient boosted trees for evolving data streams	11
Improving interpretability via regularization of neural activation sensitivity	11
Transfer and share: semi-supervised learning from long-tailed data	11
Weighted neural tangent kernel: a generalized and improved network-induced kernel	11
An interpretable sample selection framework against numerical label noise	11
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro	11
Online binary classification from similar and dissimilar data	11
Adversarial concept drift detection under poisoning attacks for robust data stream mining	11
Fraud detection with natural language processing	11
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models	10
Lifted model checking for relational MDPs	10
An improved evolutionary wrapper-filter feature selection approach with a new initialisation scheme	10
Byzantine-robust distributed sparse learning for M-estimation	10
Joint optimization of an autoencoder for clustering and embedding	10
How to be fair? A study of label and selection bias	10
Pruning during training by network efficacy modeling	10
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	10
Robust matrix estimations meet Frank–Wolfe algorithm	10
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation	10
Troubleshooting image segmentation models with human-in-the-loop	10
Calibrated explanations for regression	10
Permutation-invariant linear classifiers	10
Understanding generalization error of SGD in nonconvex optimization	10
Empirical analysis of performance assessment for imbalanced classification	10
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	10
Hitting the target: stopping active learning at the cost-based optimum	10
Jaccard-constrained dense subgraph discovery	9
Online learning of network bottlenecks via minimax paths	9
Fast linear model trees by PILOT	9
Semi-supervised Latent Block Model with pairwise constraints	9
Traditional and context-specific spam detection in low resource settings	9
Achieving adversarial robustness via sparsity	9
Efficient fair principal component analysis	9
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	9
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	9
InfoGram and admissible machine learning	9
On the benefits of representation regularization in invariance based domain generalization	9
Bandit algorithms to personalize educational chatbots	9
Nrat: towards adversarial training with inherent label noise	9
Federated learning with superquantile aggregation for heterogeneous data	8
Polynomial-based graph convolutional neural networks for graph classification	8
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	8
Explaining short text classification with diverse synthetic exemplars and counter-exemplars	8
CoMadOut—a robust outlier detection algorithm based on CoMAD	8
DEFT: distilling entangled factors by preventing information diffusion	8
iSOUP-SymRF: Symbolic feature ranking with random forests in online multi-target regression and multi-label classification	8
Correction to: A neural meta-model for predicting winter wheat crop yield	8
Wasserstein dropout	8
Information bottleneck and selective noise supervision for zero-shot learning	8
Diverse and consistent multi-view networks for semi-supervised regression	8
Distribution-free conformal joint prediction regions for neural marked temporal point processes	8
Hierarchically structured task-agnostic continual learning	8
Understanding transfer learning and gradient-based meta-learning techniques	7

Cost-sensitive classification with cost uncertainty: do we need surrogate losses?	7
Generalized vec trick for fast learning of pairwise kernel models	7
Black-box Bayesian adversarial attack with transferable priors	7
Dense subgraphs induced by edge labels	7
Gradient descent fails to learn high-frequency functions and modular arithmetic	7
A framework for training larger networks for deep Reinforcement learning	7
On metafeatures’ ability of implicit concept identification	7
Generalizing universal adversarial perturbations for deep neural networks	7
Time-aware tensor decomposition for sparse tensors	7
Explaining recommendation system using counterfactual textual explanations	7
A unified framework for online trip destination prediction	7
A deep reinforcement learning framework for continuous intraday market bidding	7
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +	7
Unified convergence analysis for adaptive optimization with moving average estimator	7
A parameter-less algorithm for tensor co-clustering	7
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics	7
A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessions	7
Relational data embeddings for feature enrichment with background information	7
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network	7
Sanitized clustering against confounding bias	7
Adaptive adapter routing for long-tailed class-incremental learning	7
Spatiotemporal-view member preference contrastive representation learning for group recommendation	7
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics	7
Stress detection with encoding physiological signals and convolutional neural network	6
Hellinger distance decision trees for PU learning in imbalanced data sets	6
Bayesian mixture variational autoencoders for multi-modal learning	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
A generalized Weisfeiler-Lehman graph kernel	6
Improve generated adversarial imitation learning with reward variance regularization	6
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	6
Quick and robust feature selection: the strength of energy-efficient sparse training for autoencoders	6
In-game soccer outcome prediction with offline reinforcement learning	6
Temporal ensemble of multiple patterns’ instances for continuous prediction of events	6
Ranking-preserved generative label enhancement	6
Gradient-based causal discovery with latent variables	6
When are they coming? Understanding and forecasting the timeline of arrivals at the FC Barcelona stadium on match days	6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression	6
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	6
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows	6
Estimation of multidimensional item response theory models with correlated latent variables using variational autoencoders	6
Learning an adaptive forwarding strategy for mobile wireless networks: resource usage vs. latency	6
MLife: a lite framework for machine learning lifecycle initialization	6
Tree-based dynamic classifier chains	6
Multi-target prediction for dummies using two-branch neural networks	6
A systematic approach for learning imbalanced data: enhancing zero-inflated models through boosting	6
The class imbalance problem in deep learning	6