| Nome |
# |
|
Self-training for multi-target regression with tree ensembles, file dd9e0c6c-353b-1e9c-e053-3a05fe0a45ef
|
132
|
|
Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets, file dd9e0c6c-39db-1e9c-e053-3a05fe0a45ef
|
127
|
|
Spatial autocorrelation and entropy for renewable energy forecasting, file dd9e0c6c-4fb0-1e9c-e053-3a05fe0a45ef
|
121
|
|
CloFAST: closed sequential pattern mining using sparse and vertical id-lists, file dd9e0c6c-3b8b-1e9c-e053-3a05fe0a45ef
|
116
|
|
Introduction to the special issue on discovery science, file dd9e0c6a-ad22-1e9c-e053-3a05fe0a45ef
|
111
|
|
Spatially-Aware Autoencoders for Detecting Contextual Anomalies in Geo-Distributed Data, file dd9e0c6b-6ae2-1e9c-e053-3a05fe0a45ef
|
100
|
|
Semi-supervised trees for multi-target regression, file dd9e0c6c-3832-1e9c-e053-3a05fe0a45ef
|
96
|
|
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data, file dd9e0c6c-39e1-1e9c-e053-3a05fe0a45ef
|
77
|
|
DENCAST: distributed density-based clustering for multi-target regression, file dd9e0c66-9f9a-1e9c-e053-3a05fe0a45ef
|
71
|
|
Predictive modeling of PV energy production: How to set up the learning task for a better prediction?, file dd9e0c6c-1f26-1e9c-e053-3a05fe0a45ef
|
64
|
|
Multi-type clustering and classification from heterogeneous networks, file dd9e0c6c-7152-1e9c-e053-3a05fe0a45ef
|
64
|
|
Relational mining for discovering changes in evolving networks, file dd9e0c6b-fd2b-1e9c-e053-3a05fe0a45ef
|
57
|
|
Big Data Research in Italy: A Perspective, file dd9e0c64-33de-1e9c-e053-3a05fe0a45ef
|
55
|
|
ComiRNet: A web-based system for the analysis of miRNA-gene regulatory networks, file dd9e0c64-28bd-1e9c-e053-3a05fe0a45ef
|
52
|
|
Semi-Supervised Multi-View Learning for Gene Network Reconstruction, file dd9e0c64-315d-1e9c-e053-3a05fe0a45ef
|
49
|
|
Ensemble Learning for Multi-Type Classification in Heterogeneous Networks, file dd9e0c6a-ef0d-1e9c-e053-3a05fe0a45ef
|
47
|
|
Mining microscopic and macroscopic changes in network data streams, file dd9e0c6b-e306-1e9c-e053-3a05fe0a45ef
|
44
|
|
Exploiting Transfer Learning for the Reconstruction of the Human Gene Regulatory Network, file dd9e0c66-7989-1e9c-e053-3a05fe0a45ef
|
23
|
|
Self-training for multi-target regression with tree ensembles, file dd9e0c69-e97c-1e9c-e053-3a05fe0a45ef
|
14
|
|
Predictive modeling of PV energy production: How to set up the learning task for a better prediction?, file dd9e0c6a-04c8-1e9c-e053-3a05fe0a45ef
|
14
|
|
Relational mining for discovering changes in evolving networks, file dd9e0c64-2a25-1e9c-e053-3a05fe0a45ef
|
13
|
|
Semi-supervised trees for multi-target regression, file dd9e0c6a-562e-1e9c-e053-3a05fe0a45ef
|
11
|
|
Mining microscopic and macroscopic changes in network data streams, file dd9e0c69-cff7-1e9c-e053-3a05fe0a45ef
|
9
|
|
Ensemble Learning for Multi-Type Classification in Heterogeneous Networks, file dd9e0c6a-124e-1e9c-e053-3a05fe0a45ef
|
9
|
|
CloFAST: closed sequential pattern mining using sparse and vertical id-lists, file dd9e0c6a-1fcc-1e9c-e053-3a05fe0a45ef
|
9
|
|
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data, file dd9e0c65-ae53-1e9c-e053-3a05fe0a45ef
|
7
|
|
Multi-type clustering and classification from heterogeneous networks, file dd9e0c6a-2955-1e9c-e053-3a05fe0a45ef
|
7
|
|
Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets, file dd9e0c6a-149a-1e9c-e053-3a05fe0a45ef
|
6
|
|
Exploiting causality in gene network reconstruction based on graph embedding, file dd9e0c68-6c9e-1e9c-e053-3a05fe0a45ef
|
5
|
|
BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent, file dd9e0c6b-7251-1e9c-e053-3a05fe0a45ef
|
5
|
|
Network Reconstruction for the Identification of miRNA: mRNA Interaction Networks, file dd9e0c62-5bf8-1e9c-e053-3a05fe0a45ef
|
4
|
|
Discovering Novelty Patterns from the Ancient Christian Inscriptions of Rome, file dd9e0c65-13bc-1e9c-e053-3a05fe0a45ef
|
4
|
|
Simultaneous Process Drift Detection and Characterization with Pattern-Based Change Detectors, file dd9e0c69-a841-1e9c-e053-3a05fe0a45ef
|
4
|
|
Integrating genome-scale metabolic modelling and transfer learning for human gene regulatory network reconstruction, file dd9e0c6b-7258-1e9c-e053-3a05fe0a45ef
|
4
|
|
null, file dd9e0c62-7529-1e9c-e053-3a05fe0a45ef
|
3
|
|
JKarma: A Highly-Modular Framework for Pattern-Based Change Detection on Evolving Data, file dd9e0c69-b336-1e9c-e053-3a05fe0a45ef
|
3
|
|
Spatial autocorrelation and entropy for renewable energy forecasting, file dd9e0c6a-4b5a-1e9c-e053-3a05fe0a45ef
|
3
|
|
ECHAD: Embedding-Based Change Detection from Multivariate Time Series in Smart Grids, file dd9e0c6a-534b-1e9c-e053-3a05fe0a45ef
|
3
|
|
Mining emotion-aware sequential rules at user-level from micro-blogs, file 8d8575b7-688f-45f8-a03f-ecc20926e26c
|
2
|
|
Transductive Relational Classification in the Co-training Paradigm, file dd9e0c64-2790-1e9c-e053-3a05fe0a45ef
|
2
|
|
Integrating microRNA target predictions for the discovery of gene regulatory networks: a semi-supervised ensemble learning approach, file dd9e0c6a-0591-1e9c-e053-3a05fe0a45ef
|
2
|
|
PRILJ: an efficient two-step method based on embedding and clustering for the identification of regularities in legal case judgments, file dd9e0c6b-61e8-1e9c-e053-3a05fe0a45ef
|
2
|
|
Anomaly Detection for Public Transport and Air Pollution Analysis, file 1b4023c0-4b63-4289-81a8-7ff2fb427485
|
1
|
|
Distributed Heterogeneous Transfer Learning for Link Prediction in the Positive Unlabeled Setting, file 2f91fcee-4335-4909-b175-6f60851a0f69
|
1
|
|
Relational tree ensembles and feature rankings, file b6bfe7ae-e028-40b1-a03f-d4bbe229f7e2
|
1
|
|
Network Regression with Predictive Clustering Trees, file dd9e0c62-49a5-1e9c-e053-3a05fe0a45ef
|
1
|
|
Ranking Sentences for Keyphrase Extraction: A Relational Data Mining Approach, file dd9e0c62-5bf7-1e9c-e053-3a05fe0a45ef
|
1
|
|
A Grid-based Multi-Relational Approach to Process Mining, file dd9e0c62-70f8-1e9c-e053-3a05fe0a45ef
|
1
|
|
Transductive learning for spatial regression with co-training, file dd9e0c62-748c-1e9c-e053-3a05fe0a45ef
|
1
|
|
Relational learning of disjunctive patterns in spatial networks, file dd9e0c62-7cb1-1e9c-e053-3a05fe0a45ef
|
1
|
|
Big data techniques for renewable energy market, file dd9e0c62-7fac-1e9c-e053-3a05fe0a45ef
|
1
|
|
Multi-Relational Model Tree Induction Tightly-Coupled with a Relational Database, file dd9e0c63-96a6-1e9c-e053-3a05fe0a45ef
|
1
|
|
Recent advances in mining patterns from complex data, file dd9e0c63-9894-1e9c-e053-3a05fe0a45ef
|
1
|
|
Dealing with spatial autocorrelation in gene flow modeling, file dd9e0c63-9922-1e9c-e053-3a05fe0a45ef
|
1
|
|
Dealing with Spatial Autocorrelation when Learning Predictive Clustering
Trees, file dd9e0c63-9fdd-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c64-9fd2-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c65-2e19-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c65-f08e-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c66-9f9d-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c69-9d8e-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c69-b4e1-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c69-e4b0-1e9c-e053-3a05fe0a45ef
|
1
|
|
Multi-aspect renewable energy forecasting, file dd9e0c69-f5ae-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c69-f6e1-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c69-f6e2-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c69-f6e4-1e9c-e053-3a05fe0a45ef
|
1
|
|
Semi-supervised classification trees, file dd9e0c6a-07d3-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6a-16b6-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6a-3ee0-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6a-4c3a-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6a-5080-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6a-5081-1e9c-e053-3a05fe0a45ef
|
1
|
|
null, file dd9e0c6a-5085-1e9c-e053-3a05fe0a45ef
|
1
|
|
Effectively and efficiently supporting roll-up and drill-down OLAP operations over continuous dimensions via hierarchical clustering, file dd9e0c6a-56c5-1e9c-e053-3a05fe0a45ef
|
1
|
| Totale |
1.583 |