Conditional density estimation and simulation through optimal transport
Scalable Bayesian preference learning for crowds
Learning from positive and unlabeled data: a survey
Classification using proximity catch digraphs
Distributed block-diagonal approximation methods for regularized empirical risk minimization
On cognitive preferences and the plausibility of rule-based models
An empirical analysis of binary transformation strategies and base algorithms for multi-label learning
Correction to: Efficient feature selection using shrinkage estimators
Double random forest
Classification with costly features as a sequential decision-making problem
Anomaly detection with inexact labels
Robust classification via MOM minimization
Correction to: Robust classification via MOM minimization
Discovering subjectively interesting multigraph patterns
Foreword: special issue for the journal track of the 12th Asian conference on machine learning (ACML 2020)
Learning with mitigating random consistency from the accuracy measure
Robust high dimensional expectation maximization algorithm via trimmed hard thresholding
Boost image captioning with knowledge reasoning
Fast and accurate pseudoinverse with sparse matrix reordering and incremental approach
Spanning attack: reinforce black-box attacks with unlabeled data
Binary classification with ambiguous training data
Online Bayesian max-margin subspace learning for multi-view classification and regression
An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat
On some graph-based two-sample tests for high dimension, low sample size data
Predictive spreadsheet autocompletion with constraints
A bad arm existence checking problem: How to utilize asymmetric problem structure?
A survey on semi-supervised learning
Analysis of Hannan consistent selection for Monte Carlo tree search in simultaneous move games
Rankboost\(+\): an improvement to Rankboost
Combining Bayesian optimization and Lipschitz optimization
Provable accelerated gradient method for nonconvex low rank optimization
Sum–product graphical models
Kappa Updated Ensemble for drifting data stream mining
Reflections on reciprocity in research
Guest editors’ introduction: special issue on Inductive Logic Programming (ILP 2019)
Learning higher-order logic programs
Logical reduction of metarules
Constructing generative logical models for optimisation problems using domain knowledge
Inductive general game playing
Transfer learning by mapping and revising boosted relational dependency networks
Propositionalization and embeddings: two sides of the same coin
Guest Editorial: Special issue on Discovery Science
Effective approximation of parametrized closure systems over transactional data streams
Feature ranking for multi-target regression
Ranking by inspiration: a network science approach
Exploiting causality in gene network reconstruction based on graph embedding
Foreword: special issue for the journal track of the 11th Asian Conference on Machine Learning (ACML 2019)
Joint consensus and diversity for multi-view semi-supervised classification
Gradient descent optimizes over-parameterized deep ReLU networks
Skill-based curiosity for intrinsically motivated reinforcement learning
Principled analytic classifier for positive-unlabeled learning via weighted integral probability metric
Handling concept drift via model reuse
Communication-efficient distributed multi-task learning with matrix sparsity regularization
Rank minimization on tensor ring: an efficient approach for tensor decomposition and completion
Multi-label optimal margin distribution machine
Few-shot learning with adaptively initialized task optimizer: a practical meta-learning approach
High-dimensional model recovery from random sketched data by exploring intrinsic sparsity
Model-based kernel sum rule: kernel Bayesian inference with probabilistic models
Sparse hierarchical regression with polynomials
Improved graph-based SFA: information preservation complements the slowness principle
Joint maximization of accuracy and information for learning the structure of a Bayesian network classifier
Editorial: Machine learning for safety–critical applications in engineering
Engineering problems in machine learning systems
Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP
In memory of Tom Fawcett
Guest editors’ introduction to the special issue on Discovery Science
Evaluating time series forecasting models: an empirical study on performance estimation methods
Co-eye: a multi-resolution ensemble classifier for symbolically approximated time series
Unsupervised representation learning with Minimax distance measures
Bonsai: diverse and shallow trees for extreme multi-label classification
Incremental predictive clustering trees for online semi-supervised multi-target regression
Multi-label feature ranking with ensemble methods
Embedding-based Silhouette community detection
Predicting rice phenotypes with meta and multi-target learning
Ensembles of extremely randomized predictive clustering trees for predicting structured outputs
Introduction to the special issue of the ECML PKDD 2020 journal track
Active deep Q-learning with demonstration
Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication
Using error decay prediction to overcome practical issues of deep active learning for named entity recognition
Learning representations from dendrograms
Imbalanced regression and extreme value prediction
Ada-boundary: accelerating DNN training via adaptive boundary batch selection
A decision-theoretic approach for model interpretability in Bayesian framework
Skew Gaussian processes for classification
Weak approximation of transformed stochastic gradient MCMC
High-dimensional Bayesian optimization using low-dimensional feature spaces
Fast greedy \(\mathcal {C}\)-bound minimization with guarantees
