A survey of community detection methods in multilayer networks
A survey of deep network techniques all classifiers can adopt
Online summarization of dynamic graphs using subjective interestingness for sequential data
Recency-based sequential pattern mining in multiple event sequences
For real: a thorough look at numeric attributes in subgroup discovery
The network-untangling problem: from interactions to activity timelines
An exemplar-based clustering using efficient variational message passing
Natural language techniques supporting decision modelers
Mining explainable local and global subgraph patterns with surprising densities
SMILE: a feature-based temporal abstraction framework for event-interval sequence classification
Homophily outlier detection in non-IID categorical data
Mining full, inner and tail periodic patterns with perfect, imperfect and asynchronous periodicity simultaneously
Widening: using parallel resources to improve model quality
Streaming changepoint detection for transition matrices
Correction to: Streaming changepoint detection for transition matrices
Pseudoinverse graph convolutional networks
Fast computation of Katz index for efficient processing of link prediction queries
A deep multimodal model for bug localization
Extending greedy feature selection algorithms to multiple solutions
Efficient set-valued prediction in multi-class classification
Smoothed dilated convolutions for improved dense prediction
Relational Learning Analysis of Social Politics using Knowledge Graph Embedding
What’s in a name? – gender classification of names with character based machine learning models
Handling imbalance in hierarchical classification problems using local classifiers approaches
Correlations between random projections and the bivariate normal
An overlap sensitive neural network for class imbalanced data
CrashNet: an encoder–decoder architecture to predict crash test outcomes
Guest editorial: Special issue on mining for health
Adversarial balancing-based representation learning for causal effect inference with observational data
Affinity analysis for studying physicians’ prescription behavior.
Feature extraction from unequal length heterogeneous EHR time series via dynamic time warping and tensor decomposition
Predictive modeling of infant mortality
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
Detecting singleton spams in reviews via learning deep anomalous temporal aspect-sentiment patterns
Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data
Social explorative attention based recommendation for content distribution platforms
User preference and embedding learning with implicit feedback for recommender systems
A framework for deep constrained clustering
Learning tractable probabilistic models for moral responsibility and blame
Mining communities and their descriptions on attributed graphs: a survey
Deep graph similarity learning: a survey
Detecting virtual concept drift of regressors without ground truth values
ForestDSH: a universal hash design for discrete probability distributions
Recurring concept memory management in data streams: exploiting data stream concept evolution to improve performance and transparency
FuseRec: fusing user and item homophily modeling with temporal recommender systems
Time series motifs discovery under DTW allows more robust discovery of conserved structure
Word-class embeddings for multiclass text classification
Dataset2Vec: learning dataset meta-features
Sparse randomized shortest paths routing with Tsallis divergence regularization
Time series extrinsic regression
Multi-label learning with missing and completely unobserved labels
Sequential recommendation with metric models based on frequent sequences
Tackling ordinal regression problem for heterogeneous data: sparse and deep multi-task learning approaches
Boosting house price predictions using geo-spatial network embedding
Social media as author-audience games
Isolation kernel: the X factor in efficient and effective large scale online kernel learning
Implicit consensus clustering from multiple graphs
A Lagrangian-based score for assessing the quality of pairwise constraints in semi-supervised clustering
Time series clustering in linear time complexity
Chebyshev approaches for imbalanced data streams regression models
Continuous treatment effect estimation via generative adversarial de-confounding
Characterizing attitudinal network graphs through frustration cloud
Introduction to the special issue of the ECML PKDD 2021 journal track
BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent
Early abandoning and pruning for elastic distances including dynamic time warping
MultiETSC: automated machine learning for early time series classification
CURIE: a cellular automaton for concept drift detection
VFC-SMOTE: very fast continuous synthetic minority oversampling for evolving data streams
Unsupervised domain adaptation with non-stochastic missing data
Effective social post classifiers on top of search interfaces
Fake review detection on online E-commerce platforms: a systematic literature review
AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series
Hyperbolic node embedding for temporal networks
TSK-Streams: learning TSK fuzzy systems for regression on data streams
An alternating nonmonotone projected Barzilai–Borwein algorithm of nonnegative factorization of big matrices
Data-driven detection of counterpressing in professional football
Differentially Private Distance Learning in Categorical Data
Structure learning for relational logistic regression: an ensemble approach
Attention based adversarially regularized learning for network embedding
Selego: robust variate selection for accurate time series forecasting
Link prediction in dynamic networks using random dot product graphs
K-plex cover pooling for graph neural networks
