Machine Learning

Article	Citations
Learning to bid and rank together in recommendation systems	224
The role of mutual information in variational classifiers	180
Robust reputation independence in ranking systems for multiple sensitive attributes	152
Maximum causal entropy inverse constrained reinforcement learning	92
Parameter identifiability of a deep feedforward ReLU neural network	89
Surrogate models of radiative transfer codes for atmospheric trace gas retrievals from satellite observations	83
Adapting performance metrics for ordinal classification to interval scale: length matters	74
Meta-learning for heterogeneous treatment effect estimation with closed-form solvers	70
Compositional scene modeling with global object-centric representations	66
Modelling spatiotemporal dynamics from Earth observation data with neural differential equations	63
Fairness seen as global sensitivity analysis	46
SETAR-Tree: a novel and accurate tree algorithm for global time series forecasting	41
Automated imbalanced classification via layered learning	41
Resolving power: a general approach to compare the distinguishing ability of threshold-free evaluation metrics	40
Spike2CGR: an efficient method for spike sequence classification using chaos game representation	39
Semantic-enhanced graph neural networks with global context representation	36
Correction to: Segmentation and feature extraction-based classification of pavement damages using hybrid computer vision and machine learning approaches	35
On the usefulness of the fit-on-test view on evaluating calibration of classifiers	34
Differentially-private data synthetisation for efficient re-identification risk control	33
Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization	33
Transfer learning with pre-trained conditional generative models	33
Masked autoencoder for multiagent trajectories	32
Towards accurate knowledge transfer via target-awareness representation disentanglement	32
GENs: generative encoding networks	32
Trimming stability selection increases variable selection robustness	31

Efficient private SCO for heavy-tailed data via averaged clipping	31
A calibration test for evaluating set-based epistemic uncertainty representations	28
LaMMOn: language model combined graph neural network for multi-target multi-camera tracking in online scenarios	28
Responsible model deployment via model-agnostic uncertainty learning	28
Glacier: guided locally constrained counterfactual explanations for time series classification	26
A flexible class of dependence-aware multi-label loss functions	25
Secure and fast asynchronous Vertical Federated Learning via cascaded hybrid optimization	25
FairSwiRL: fair semi-supervised classification with representation learning	25
An accelerated proximal algorithm for regularized nonconvex and nonsmooth bi-level optimization	25
A prompt-driven framework for multi-domain knowledge tracing	25
Chinese character recognition with radical-structured stroke trees	23
Generalization bounds for learning under graph-dependence: a survey	22
Invariant representation learning via decoupling style and spurious features	22
Extended UCB Policies for Multi-armed Bandit Problems	22
Multi-label image classification with multi-layered multi-perspective dynamic semantic representation	21
Optimal survival trees	21
Data-aware process discovery for malware detection: an empirical study	20
Correction to: efficient generator of mathematical expressions for symbolic regression	20
Rényi divergence in hidden Markov models	20
Progressive semantic learning for unsupervised skeleton-based action recognition	20
Offline reinforcement learning for learning to dispatch for job shop scheduling	20
SPA: A poisoning attack framework for graph neural networks through searching and pairing	19
The backbone method for ultra-high dimensional sparse machine learning	19
Aligning model outputs for class imbalanced non-IID federated learning	18
Dynamic datasets and market environments for financial reinforcement learning	18
Autoreplicative random forests with applications to missing value imputation	18
Feature ranking for semi-supervised learning	18
Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	18
Reducing classifier overconfidence against adversaries through graph algorithms	17
Testing exchangeability in the batch mode with e-values and Markov alternatives	17
Uncertainty Quantification in Pairwise Difference Learning for Classification	17
Capturing the context-aware code change via dynamic control flow graph for commit message generation	17
A contrastive neural disentanglement approach for query performance prediction	17
Artificial intelligence for laryngoscopy in vocal fold diseases: a review of dataset, technology, and ethics	17
Autoencoding slow representations for semi-supervised data-efficient regression	17
DIMBA: discretely masked black-box attack in single object tracking	17
Histogram approaches for imbalanced data streams regression	17
Context-aware spatio-temporal event prediction via convolutional Hawkes processes	16
Paf-tracker: a novel pre-frame auxiliary and fusion visual tracker	16
Event causality extraction through external event knowledge learning and polyhedral word embedding	16
TFAS: zero-shot NAS for general time-series analysis with time-frequency aware scoring	16
Learning biologically-interpretable latent representations for gene expression data	16
Pdarts: projected differentiable architecture search for seismic inversion	16
Correction to: Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations	16
Conformal prediction for regression models with asymmetrically distributed errors: application to aircraft navigation during landing maneuver	16
Counterfactual ensembles for interpretable churn prediction: from real-world to privacy-preserving synthetic data	16
Coresets for kernel clustering	16
An in-depth review and analysis of mode collapse in generative adversarial networks	15
Multi-agent reinforcement learning for fast-timescale demand response of residential loads	15
Probabilistic scoring lists for interpretable machine learning	15

Consensus–relevance kNN and covariate shift mitigation	15
LEAP: Linear equations for classifier accuracy prediction under prior probability shift	15
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks	15
Connecting weighted automata, tensor networks and recurrent neural networks through spectral learning	15
One transformer for all time series: representing and training with time-dependent heterogeneous tabular data	15
Adaptive differentiable trees for transparent learning on data streams	15
Correction to: Exploiting sparsity and statistical dependence in multivariate data fusion: an application to misinformation detection for high-impact events	14
A new formulation of Lipschitz constrained with functional gradient learning for GANs	14
Efficient and interpretable raw audio classification with diagonal state space models	14
Attacking neural machine translations via hybrid attention learning	14
Mind the gap: from plausible to valid self-explanations in large language models	14
Constrained regret minimization for multi-criterion multi-armed bandits	14
Imbalanced gradients: a subtle cause of overestimated adversarial robustness	14
On the Discrepancy between Kleinberg’s Clustering Axioms and k-Means Clustering Algorithm Behavior	14
Targeted adversarial attacks on wind power forecasts	13
Efficient and provable online reduced rank regression via online gradient descent	13
Empirical Bayes linked matrix decomposition	13
Achieving collective welfare in multi-agent reinforcement learning via suggestion sharing	13
Unmasking deception: a topic-oriented multimodal approach to uncover false information on social media	13
Understanding prediction discrepancies in classification	13
Applied machine learning to the determination of biochar hydrogen sulfide adsorption capacity	13
Exploiting counter-examples for active learning with partial labels	13
Least-squares temporal difference with expected eligibility traces	12
Improving kernel online learning with a snapshot memory	12
Learning de-biased environment models for delivery incentive policy optimization on food delivery platforms	12
Panda: partially approximate newton methods for distributed minimax optimization with unbalanced dimensions	12
Adversarial concept drift detection under poisoning attacks for robust data stream mining	12
Beyond What’s Normal: Bimodal and Heaviside Alternatives to Gaussian Process Regression	12
Forecasting short-term passenger flow via CBGC-SCI: an in-depth comparative study on Shenzhen Metro	12
Improving interpretability via regularization of neural activation sensitivity	12
Correction to: Modeling PU learning using probabilistic logic programming	12
NaCL: noise-robust cross-domain contrastive learning for unsupervised domain adaptation	12
Online AutoML: an adaptive AutoML framework for online learning	12
Robust matrix estimations meet Frank–Wolfe algorithm	12
Scale-preserving automatic concept extraction (SPACE)	12
Online binary classification from similar and dissimilar data	12
Search or split: policy gradient with adaptive policy space	11
On the robustness of randomized classifiers to adversarial examples	11
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework	11
Enhancing Low-Degree Graph Neural Networks via Joint Training and Improved Message Passing	11
Transfer and share: semi-supervised learning from long-tailed data	11
Empirical analysis of performance assessment for imbalanced classification	11
An interpretable sample selection framework against numerical label noise	11
Quantitative Gaussian approximation of randomly initialized deep neural networks	11
Low-Rank Fully-Connected Tensor Network Learning for Tensor-on-Tensor Regression	11
Fast linear model trees by PILOT	10
How to be fair? A study of label and selection bias	10
Gradient boosted trees for evolving data streams	10
Lifted model checking for relational MDPs	10
A deep learning approach using natural language processing and time-series forecasting towards enhanced food safety	10
Troubleshooting image segmentation models with human-in-the-loop	10
Distilling ensemble of explanations for weakly-supervised pre-training of image segmentation models	10
Efficient federated unlearning under plausible deniability	10
Fraud detection with natural language processing	10
InfoGram and admissible machine learning	10
A unified view of forward and backward losses for learning from weak labels	10
Traditional and context-specific spam detection in low resource settings	10
Weighted neural tangent kernel: a generalized and improved network-induced kernel	10
$${{\mathrm {Latent}}Out}$$: an unsupervised deep anomaly detection approach exploiting latent space distribution	10
Permutation-invariant linear classifiers	10
Online learning of network bottlenecks via minimax paths	9
Hitting the target: stopping active learning at the cost-based optimum	9
Calibrated explanations for regression	9
Efficient fair principal component analysis	9
Semi-supervised Latent Block Model with pairwise constraints	9
On the benefits of representation regularization in invariance based domain generalization	9
LLiMe: enhancing text classifier explanations with large language models	9
Learning answer set programs with aggregates via sampling and genetic programming	9
Jaccard-constrained dense subgraph discovery	9
Pruning during training by network efficacy modeling	9
Wasserstein dropout	8
Graph spring neural ODEs for link sign prediction	8
Explaining recommendation system using counterfactual textual explanations	8
CoMadOut—a robust outlier detection algorithm based on CoMAD	8
Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework	8
DEFT: distilling entangled factors by preventing information diffusion	8
Cost-sensitive classification with cost uncertainty: do we need surrogate losses?	8
iSOUP-SymRF: Symbolic feature ranking with random forests in online multi-target regression and multi-label classification	8
Federated learning with superquantile aggregation for heterogeneous data	8
Temporal Graph Network Framework for Quantifying Pass Reception Probabilities Against Defensive Structures	8

Correction to: A neural meta-model for predicting winter wheat crop yield	8
Understanding transfer learning and gradient-based meta-learning techniques	8
SafeGen: safeguarding privacy and fairness through a genetic method	8
Distribution-free conformal joint prediction regions for neural marked temporal point processes	8
Correction to: Extracting automata from recurrent neural networks using queries and counterexamples (extended version)	8
Adaptive collaborative minority oversampling for multi-class imbalanced classification	7
Learning to rank anomalies: scalar performance criteria and maximization of rank statistics	7
Black-box Bayesian adversarial attack with transferable priors	7
Temporal ensemble of multiple patterns’ instances for continuous prediction of events	7
Gradient descent fails to learn high-frequency functions and modular arithmetic	7
ALM-PU: positive and unlabeled learning with constrained optimization	7
Efficient quantification on large-scale networks	7
Relational data embeddings for feature enrichment with background information	7
Generalized vec trick for fast learning of pairwise kernel models	7
A unified framework for online trip destination prediction	7
Unified convergence analysis for adaptive optimization with moving average estimator	7
Sanitized clustering against confounding bias	7
Addressing data dependency in neural networks: introducing the Knowledge Enhanced Neural Network (KENN) for time series forecasting +	7
Dense subgraphs induced by edge labels	7
Hierarchically structured task-agnostic continual learning	7
Adaptive adapter routing for long-tailed class-incremental learning	7
Nrat: towards adversarial training with inherent label noise	7
Information bottleneck and selective noise supervision for zero-shot learning	7
Explaining short text classification with diverse synthetic exemplars and counter-exemplars	7
Diverse and consistent multi-view networks for semi-supervised regression	7
Spatiotemporal-view member preference contrastive representation learning for group recommendation	7
ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flows	7
A framework for training larger networks for deep Reinforcement learning	7
Toward practical human-interpretable explanations	7
DISTFormer: Enhance 3D Human Pose Estimation via Dual Inverse-Order Spatial-Temporal Transformer	7
DPQ: dynamic pseudo-mean mixed-precision quantization for pruned neural network	7
Recurrent segmentation meets block models in temporal networks	6
Hellinger distance decision trees for PU learning in imbalanced data sets	6
On metafeatures’ ability of implicit concept identification	6
In-game soccer outcome prediction with offline reinforcement learning	6
Ranking-preserved generative label enhancement	6
State-novelty guided action persistence in deep reinforcement learning	6
Bayesian mixture variational autoencoders for multi-modal learning	6
Tight mixed-integer optimization formulations for prescriptive trees	6
Leveraging differentiable NAS and abstract genetic algorithms for optimizing on-mobile VSR performance	6
Variable selection for both outcomes and predictors: sparse multivariate principal covariates regression	6
The class imbalance problem in deep learning	6
Stress detection with encoding physiological signals and convolutional neural network	6
Sandbox: safeguarded multi-label learning through safe optimal transport	6
Towards efficient pareto-optimal utility-fairness between groups in repeated rankings	6
Automotive fault nowcasting with machine learning and natural language processing	6
A new adaptive gradient method with gradient decomposition	6
A comparison of latent space modeling techniques in a plain-vanilla autoencoder setting	6
Pairwise learning to rank by neural networks revisited: reconstruction, theoretical analysis and practical performance	6
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning	6
Generalizing universal adversarial perturbations for deep neural networks	6
ROSE: robust online self-adjusting ensemble for continual learning on imbalanced drifting data streams	6
Gradient-based causal discovery with latent variables	6
Bridging XAI and spectral analysis to investigate the inductive biases of deep graph networks	6
Boolean matrix logic programming for active learning of gene functions in genome-scale metabolic network models	6
Improving text processing via adversarial low-rank adaptation	6