A semi-supervised model for knowledge graph embedding
Interactive visual data exploration with subjective feedback: an information-theoretic approach
A drift detection method based on dynamic classifier selection
Topical network embedding
Grafting for combinatorial binary model using frequent itemset mining
A comparative study of data-dependent approaches without learning in measuring similarities of data objects
Matching code and law: achieving algorithmic fairness with optimal transport
Deep multi-task learning for individuals origin–destination matrices estimation from census data
FastEE: Fast Ensembles of Elastic Distances for time series classification
Guided sampling for large graphs
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code
Counting frequent patterns in large labeled graphs: a hypergraph-based approach
Matrix profile goes MAD: variable-length motif and discord discovery in data series
struc2gauss: Structural role preserving network embedding via Gaussian embedding
An ultra-fast time series distance measure to allow data mining in more complex real-world deployments
TEAGS: time-aware text embedding approach to generate subgraphs
ABBA: adaptive Brownian bridge-based symbolic aggregation of time series
Efficient mining of the most significant patterns with permutation testing
A survey and benchmarking study of multitreatment uplift modeling
On normalization and algorithm selection for unsupervised outlier detection
SIAS-miner: mining subjectively interesting attributed subgraphs
Identifying exceptional (dis)agreement between groups
Mining relaxed functional dependencies from data
Parameterized low-rank binary matrix approximation
Integer programming ensemble of temporal relations classifiers
NegPSpan: efficient extraction of negative sequential patterns with embedding constraints
Relaxing the strong triadic closure problem for edge strength inference
MasterMovelets: discovering heterogeneous movelets for multiple aspect trajectory classification
Model-based exception mining for object-relational data
Robust and sparse multigroup classification by the optimal scoring approach
TS-CHIEF: a scalable and accurate forest algorithm for time series classification
An efficient K-means clustering algorithm for tall data
Discrete-time survival forests with Hellinger distance decision trees
Computing exact P-values for community detection
ptype: probabilistic type inference
ColluEagle: collusive review spammer detection using Markov random fields
Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions
Gaussian bandwidth selection for manifold learning and classification
Introducing time series snippets: a new primitive for summarizing long time series
Credible seed identification for large-scale structural network alignment
Visualizing image content to explain novel image discovery
Challenges in benchmarking stream learning algorithms with real-world data
MIDIA: exploring denoising autoencoders for missing data imputation
Bayesian mean-parameterized nonnegative binary matrix factorization
InceptionTime: Finding AlexNet for time series classification
DeepTable: a permutation invariant neural network for table orientation classification
Correction to: A unified view of density-based methods for semi-supervised clustering and classification
Introduction to the special issue of the ECML PKDD 2020 journal track
Delayed labelling evaluation for data streams
Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling
Fair-by-design matching
TEASER: early and accurate time series classification
Scalable attack on graph data by injecting vicious nodes
Treant: training evasion-aware decision trees
Large-scale network motif analysis using compression
ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels
Active learning for hierarchical multi-label classification
Deep soccer analytics: learning an action-value function for evaluating soccer players
Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations
CrawlSN: community-aware data acquisition with maximum willingness in online social networks
