| ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning | 0 | 0.34 | 2022 |
| An eager splitting strategy for online decision trees in ensembles | 0 | 0.34 | 2022 |
| Smooth Perturbations for Time Series Adversarial Attacks | 0 | 0.34 | 2022 |
| DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images | 0 | 0.34 | 2022 |
| PROST: AlphaFold2-aware Sequence-Based Predictor to Estimate Protein Stability Changes upon Missense Mutations. | 0 | 0.34 | 2022 |
| Multi-modal temporal CNNs for live fuel moisture content estimation | 0 | 0.34 | 2022 |
| Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction | 0 | 0.34 | 2022 |
| MultiRocket: multiple pooling operators and transformations for fast and effective time series classification | 0 | 0.34 | 2022 |
| OCTID: a one-class learning-based Python package for tumor image detection | 0 | 0.34 | 2021 |
| Early abandoning and pruning for elastic distances including dynamic time warping | 1 | 0.36 | 2021 |
| Time Series Classification at Scale. | 0 | 0.34 | 2020 |
| Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information | 1 | 0.35 | 2020 |
| A novel selective naïve Bayes algorithm. | 0 | 0.34 | 2020 |
| TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification. | 0 | 0.34 | 2019 |
| A tutorial on statistically sound pattern discovery | 9 | 0.49 | 2019 |
| iProt-Sub: a comprehensive package for accurately mapping and predicting protease-specific substrates and cleavage sites. | 5 | 0.43 | 2019 |
| Positive-unlabelled learning of glycosylation sites in the human proteome. | 1 | 0.35 | 2019 |
| Survey of distance measures for quantifying concept drift and shift in numeric data | 2 | 0.36 | 2019 |
| Exploring Data Quantity Requirements for Domain Adaptation in the Classification of Satellite Image Time Series | 0 | 0.34 | 2019 |
| Adaptive online extreme learning machine by regulating forgetting factor by concept drift map. | 0 | 0.34 | 2019 |
| Mining Significant Crisp-Fuzzy Spatial Association Rules | 1 | 0.35 | 2018 |
| Efficient and Effective Accelerated Hierarchical Higher-Order Logistic Regression for Large Data Quantities. | 0 | 0.34 | 2018 |
| Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity. | 2 | 0.43 | 2018 |
| iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences. | 20 | 0.67 | 2018 |
| Efficient search of the best warping window for Dynamic Time Warping. | 2 | 0.37 | 2018 |
| On the Inter-relationships among Drift rate, Forgetting rate, Bias/variance profile and Error. | 0 | 0.34 | 2018 |
| Elastic bands across the path: A new framework and methods to lower bound DTW. | 2 | 0.37 | 2018 |
| Selective AnDE for large data learning: a low-bias memory constrained approach. | 5 | 0.43 | 2017 |
| Indexing and classifying gigabytes of time series under time warping. | 4 | 0.40 | 2017 |
| Specious rules: an efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining. | 2 | 0.37 | 2017 |
| A multiple test correction for streams and cascades of statistical hypothesis tests | 4 | 0.41 | 2016 |
| Skopus: Mining top-k sequential patterns under leverage. | 0 | 0.34 | 2016 |
| Mining significant association rules from uncertain data | 5 | 0.42 | 2016 |
| Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm. | 31 | 0.91 | 2016 |
| Scalable Learning of Bayesian Network Classifiers. | 1 | 0.35 | 2016 |
| Deep Broad Learning - Big Models for Big Data | 3 | 0.46 | 2015 |
| Scaling log-linear analysis to datasets with thousands of variables. | 3 | 0.42 | 2015 |
| Exact discovery of the most interesting sequential patterns | 0 | 0.34 | 2015 |
| GlycoMine: a machine learning-based approach for predicting N-, C- and O-linked glycosylation in the human proteome. | 20 | 0.76 | 2015 |
| Highly Scalable Attribute Selection for Averaged One-Dependence Estimators. | 4 | 0.41 | 2014 |
| Dynamic Time Warping Averaging of Time Series Allows Faster and More Accurate Classification | 51 | 1.64 | 2014 |
| Fast and Effective Single Pass Bayesian Learning. | 3 | 0.39 | 2013 |
| Panel: a data scientist's guide to making money from start-ups | 0 | 0.34 | 2013 |
| Efficient Discovery of the Most Interesting Associations | 16 | 0.75 | 2013 |
| Subsumption resolution: an efficient and effective technique for semi-naive Bayesian learning | 13 | 0.61 | 2012 |
| Discovering associations in high-dimensional data | 0 | 0.34 | 2012 |
| Feature-subspace aggregating: ensembles for stable and unstable learners | 21 | 0.94 | 2011 |
| ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010 | 162 | 17.18 | 2010 |
| EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes. | 2 | 0.37 | 2010 |
| Self-sufficient itemsets: An approach to screening potentially interesting associations between items | 28 | 1.07 | 2010 |
