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Journal Articles
- 2023
[j24]Azim Ahmadzadeh
, Dustin J. Kempton, Petrus C. Martens, Rafal A. Angryk:
Contingency Space: A Semimetric Space for Classification Evaluation. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 1501-1513 (2023)- 2022
- [j23]Ruizhe Ma, Rafal A. Angryk, Rafal Scherer:
Special issue on deep learning for time series data. Neural Comput. Appl. 34(16): 13147-13148 (2022) - [j22]Yang Chen, Dustin J. Kempton, Azim Ahmadzadeh, Junzhi Wen, Anli Ji, Rafal A. Angryk:
CGAN-based synthetic multivariate time-series generation: a solution to data scarcity in solar flare forecasting. Neural Comput. Appl. 34(16): 13339-13353 (2022) - 2021
- [j21]Berkay Aydin, Soukaina Filali Boubrahimi, Ahmet Küçük, Bita Nezamdoust, Rafal A. Angryk:
Spatiotemporal event sequence discovery without thresholds. GeoInformatica 25(1): 149-177 (2021) - 2020
- [j20]Marcin Korytkowski, Roman Senkerik, Magdalena M. Scherer, Rafal A. Angryk, Miroslaw Kordos, Agnieszka Siwocha:
Efficient Image Retrieval by Fuzzy Rules from Boosting and Metaheuristic. J. Artif. Intell. Soft Comput. Res. 10(1): 57-69 (2020) - [j19]Azim Ahmadzadeh, Kankana Sinha, Berkay Aydin, Rafal A. Angryk:
MVTS-Data Toolkit: A Python package for preprocessing multivariate time series data. SoftwareX 12: 100518 (2020) - 2019
- [j18]Shah Muhammad Hamdi, Yubao Wu, Rafal A. Angryk, Lisa Crystal Krishnamurthy, Robin D. Morris:
Identification of Discriminative Subnetwork from fMRI-Based Complete Functional Connectivity Networks. Int. J. Semantic Comput. 13(1): 25-44 (2019) - 2018
- [j17]Douglas E. Galarus, Rafal A. Angryk:
Beyond accuracy - A SMART approach to site-based spatio-temporal data quality assessment. Intell. Data Anal. 22(1): 21-43 (2018) - 2017
- [j16]Berkay Aydin, Ahmet Küçük, Rafal A. Angryk, Petrus C. Martens:
Measuring the Significance of Spatiotemporal Co-Occurrences. ACM Trans. Spatial Algorithms Syst. 3(3): 9:1-9:35 (2017) - 2016
- [j15]Berkay Aydin, Vijay Akkineni, Rafal A. Angryk:
Mining spatiotemporal co-occurrence patterns in non-relational databases. GeoInformatica 20(4): 801-828 (2016) - [j14]Tim Wylie, Michael A. Schuh, Rafal A. Angryk:
Enabling high-dimensional range queries using kNN indexing techniques: approaches and empirical results. J. Comb. Optim. 32(4): 1107-1132 (2016) - [j13]Ruizhe Ma, Xiangyue Jia, Jingwei Cheng, Rafal A. Angryk:
SPARQL queries on RDF with fuzzy constraints and preferences. J. Intell. Fuzzy Syst. 30(1): 183-195 (2016) - [j12]Karthik Ganesan Pillai, Rafal A. Angryk, Juan M. Banda, Dustin Kempton, Berkay Aydin, Petrus C. Martens:
Mining At Most Top-K% Spatiotemporal Co-occurrence Patterns in Datasets with Extended Spatial Representations. ACM Trans. Spatial Algorithms Syst. 2(3): 10:1-10:27 (2016) - 2015
- [j11]Michael A. Schuh, Juan M. Banda, Tim Wylie, Patrick McInerney, Karthik Ganesan Pillai, Rafal A. Angryk:
On visualization techniques for solar data mining. Astron. Comput. 10: 32-42 (2015) - [j10]Rafal A. Angryk, André Csillaghy, Petrus C. Martens:
Special Section: Management, Search and Analysis of Solar Astronomy Big Data. Astron. Comput. 13: 85 (2015) - [j9]Michael A. Schuh, Rafal A. Angryk, Petrus C. Martens:
Solar image parameter data from the SDO: Long-term curation and data mining. Astron. Comput. 13: 86-98 (2015) - [j8]Juan M. Banda, Rafal A. Angryk:
Regional content-based image retrieval for solar images: Traditional versus modern methods. Astron. Comput. 13: 108-116 (2015) - [j7]Dustin J. Kempton, Rafal A. Angryk:
Tracking Solar Events through Iterative Refinement. Astron. Comput. 13: 124-135 (2015) - [j6]Berkay Aydin, Dustin Kempton, Vijay Akkineni, Rafal A. Angryk, Karthik Ganesan Pillai:
Mining spatiotemporal co-occurrence patterns in solar datasets. Astron. Comput. 13: 136-144 (2015) - 2013
- [j5]Jacek M. Czerniak, Wojciech T. Dobrosielski, Rafal A. Angryk:
Comparison of two kinds of fuzzy arithmetic, LR and OFN, applied to fuzzy observation of the cofferdam water level. Comput. Sci. 14(3): 443-458 (2013) - [j4]Richard A. McAllister, Rafal A. Angryk:
Abstracting for Dimensionality Reduction in Text Classification. Int. J. Intell. Syst. 28(2): 115-138 (2013) - 2010
- [j3]Rafal A. Angryk, Jacek M. Czerniak:
Heuristic algorithm for interpretation of multi-valued attributes in similarity-based fuzzy relational databases. Int. J. Approx. Reason. 51(8): 895-911 (2010) - 2007
- [j2]Rafal A. Angryk, Frederick E. Petry:
Attribute-oriented fuzzy generalization in proximity- and similarity-based relational database systems. Int. J. Intell. Syst. 22(7): 763-779 (2007) - 2001
- [j1]Rafal A. Angryk:
MICO, An Open Source CORBA Implementation. Parallel Distributed Comput. Pract. 4(3) (2001)
Conference and Workshop Papers
- 2024
- [c133]Chetraj Pandey, Temitope Adeyeha, Jinsu Hong, Rafal A. Angryk, Berkay Aydin:
Advancing Solar Flare Prediction Using Deep Learning with Active Region Patches. ECML/PKDD (10) 2024: 50-65 - 2023
- [c132]Chetraj Pandey, Anli Ji, Rafal A. Angryk, Berkay Aydin:
Towards Interpretable Solar Flare Prediction with Attention-based Deep Neural Networks. AIKE 2023: 83-90 - [c131]Chetraj Pandey, Rafal A. Angryk, Manolis K. Georgoulis, Berkay Aydin:
Explainable Deep Learning-Based Solar Flare Prediction with Post Hoc Attention for Operational Forecasting. DS 2023: 567-581 - [c130]Chetraj Pandey, Anli Ji, Trisha Nandakumar, Rafal A. Angryk, Berkay Aydin:
Exploring Deep Learning for Full-disk Solar Flare Prediction with Empirical Insights from Guided Grad-CAM Explanations. DSAA 2023: 1-10 - [c129]Yang Chen, Dustin J. Kempton, Rafal A. Angryk:
Examining Effects of Class Imbalance on Conditional GAN Training. ICAISC (1) 2023: 475-486 - [c128]Chetraj Pandey, Rafal A. Angryk, Berkay Aydin:
Unveiling the Potential of Deep Learning Models for Solar Flare Prediction in Near-Limb Regions. ICMLA 2023: 703-708 - [c127]Chetraj Pandey, Rafal A. Angryk, Berkay Aydin:
Explaining Full-Disk Deep Learning Model for Solar Flare Prediction Using Attribution Methods. ECML/PKDD (7) 2023: 72-89 - 2022
- [c126]Junzhi Wen, Md Reazul Islam, Azim Ahmadzadeh, Rafal A. Angryk:
Improving Solar Flare Prediction by Time Series Outlier Detection. ICAISC (2) 2022: 152-164 - [c125]Azim Ahmadzadeh, Rafal A. Angryk:
Measuring Class-Imbalance Sensitivity of Deterministic Performance Evaluation Metrics. ICIP 2022: 51-55 - [c124]Anli Ji, Junzhi Wen, Rafal A. Angryk, Berkay Aydin:
Solar Flare Forecasting with Deep Learning-based Time Series Classifiers. ICPR 2022: 2907-2913 - [c123]Azim Ahmadzadeh, Yang Chen, Krishna Rukmini Puthucode, Ruizhe Ma, Rafal A. Angryk:
TS-MIoU: A Time Series Similarity Metric Without Mapping. ECML/PKDD (6) 2022: 87-102 - 2021
- [c122]Chetraj Pandey, Rafal A. Angryk, Berkay Aydin:
Solar Flare Forecasting with Deep Neural Networks using Compressed Full-disk HMI Magnetograms. IEEE BigData 2021: 1725-1730 - [c121]Anli Ji, Akhil Arya, Dustin Kempton, Rafal A. Angryk, Manolis K. Georgoulis, Berkay Aydin:
A Modular Approach to Building Solar Energetic Particle Event Forecasting Systems. CogMI 2021: 106-115 - [c120]Ruizhe Ma, Rafal A. Angryk:
Tiered Clustering for Time Series Data. Deep-BDB 2021: 3-14 - [c119]Yang Chen, Dustin J. Kempton, Azim Ahmadzadeh, Rafal A. Angryk:
Towards Synthetic Multivariate Time Series Generation for Flare Forecasting. ICAISC (1) 2021: 296-307 - [c118]Azim Ahmadzadeh, Dustin J. Kempton, Yang Chen, Rafal A. Angryk:
Multiscale IOU: A Metric for Evaluation of Salient Object Detection with Fine Structures. ICIP 2021: 684-688 - [c117]Atharv Yeolekar, Sagar Patel, Shreejaa Talla, Krishna Rukmini Puthucode, Azim Ahmadzadeh, Viacheslav M. Sadykov, Rafal A. Angryk:
Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methods. ICDM (Workshops) 2021: 1067-1076 - [c116]Chetraj Pandey, Rafal A. Angryk, Berkay Aydin:
Deep Neural Networks Based Solar Flare Prediction Using Compressed Full-disk Line-of-sight Magnetograms. SIMBig 2021: 380-396 - 2020
- [c115]Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Ruizhe Ma, Rafal A. Angryk:
On the Mining of the Minimal Set of Time Series Data Shapelets. IEEE BigData 2020: 493-502 - [c114]Xumin Cai, Berkay Aydin, Anli Ji, Manolis K. Georgoulis, Rafal A. Angryk:
A Framework for Detecting Polarity Inversion Lines from Longitudinal Magnetograms. IEEE BigData 2020: 4175-4183 - [c113]Yang Chen, Anli Ji, Pavan Ajit Babajiyavar, Azim Ahmadzadeh, Rafal A. Angryk:
On The Effectiveness of Imaging of Time Series for Flare Forecasting Problem. IEEE BigData 2020: 4184-4191 - [c112]Mohammed Shoebuddin Habeeb, Berkay Aydin, Azim Ahmadzadeh, Manolis K. Georgoulis, Rafal A. Angryk:
Deep Neural Network-based Active Region Magnetogram Patch Super Resolution. IEEE BigData 2020: 4200-4207 - [c111]Maxwell Hostetter, Rafal A. Angryk:
First Steps Toward Synthetic Sample Generation for Machine Learning Based Flare Forecasting. IEEE BigData 2020: 4208-4217 - [c110]Anli Ji, Berkay Aydin, Manolis K. Georgoulis, Rafal A. Angryk:
All-Clear Flare Prediction Using Interval-based Time Series Classifiers. IEEE BigData 2020: 4218-4225 - [c109]Xumin Cai, Berkay Aydin, Saurabh Maydeo, Anli Ji, Rafal A. Angryk:
Local Outlier Detection for Multi-type Spatio-temporal Trajectories. IEEE BigData 2020: 4509-4518 - [c108]Mohammed Shoebuddin Habeeb, Berkay Aydin, Azim Ahmadzadeh, Manolis K. Georgoulis, Rafal A. Angryk:
Solar Line-of-Sight Magnetograms Super-Resolution Using Deep Neural Networks. IEEE BigData 2020: 4586-4593 - [c107]Xumin Cai, Berkay Aydin, Anli Ji, Rafal A. Angryk:
A Framework for Local Outlier Detection from Spatio-Temporal Trajectory Datasets. ICPR 2020: 5682-5689 - 2019
- [c106]Azim Ahmadzadeh, Maxwell Hostetter, Berkay Aydin, Manolis K. Georgoulis, Dustin J. Kempton, Sushant S. Mahajan, Rafal A. Angryk:
Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data. IEEE BigData 2019: 1423-1431 - [c105]Azim Ahmadzadeh, Sushant S. Mahajan, Dustin J. Kempton, Rafal A. Angryk, Shihao Ji:
Toward Filament Segmentation Using Deep Neural Networks. IEEE BigData 2019: 4932-4941 - [c104]Xumin Cai, Berkay Aydin, Manolis K. Georgoulis, Rafal A. Angryk:
An Application of Spatio-temporal Co-occurrence Analyses for Integrating Solar Active Region Data from Multiple Reporting Modules. IEEE BigData 2019: 4950-4959 - [c103]Maxwell Hostetter, Azim Ahmadzadeh, Berkay Aydin, Manolis K. Georgoulis, Dustin J. Kempton, Rafal A. Angryk:
Understanding the Impact of Statistical Time Series Features for Flare Prediction Analysis. IEEE BigData 2019: 4960-4966 - [c102]Ruizhe Ma, Azim Ahmadzadeh, Soukaina Filali Boubrahimi, Manolis K. Georgoulis, Rafal A. Angryk:
Solar Pre-Flare Classification with Time Series Profiling. IEEE BigData 2019: 4967-4976 - [c101]Shah Muhammad Hamdi, Soukaina Filali Boubrahimi, Rafal A. Angryk:
Tensor Decomposition-based Node Embedding. CIKM 2019: 2105-2108 - [c100]Ruizhe Ma, Azim Ahmadzadeh, Soukaïna Filali Boubrahimi, Rafal A. Angryk:
A Scalable Segmented Dynamic Time Warping for Time Series Classification. ICAISC (2) 2019: 407-419 - [c99]Shah Muhammad Hamdi, Rafal A. Angryk:
Interpretable Feature Learning of Graphs using Tensor Decomposition. ICDM 2019: 270-279 - [c98]Azim Ahmadzadeh, Berkay Aydin, Dustin J. Kempton, Maxwell Hostetter, Rafal A. Angryk, Manolis K. Georgoulis, Sushant S. Mahajan:
Rare-Event Time Series Prediction: A Case Study of Solar Flare Forecasting. ICMLA 2019: 1814-1820 - 2018
- [c97]Shah Muhammad Hamdi, Berkay Aydin, Soukaina Filali Boubrahimi, Rafal A. Angryk, Lisa Crystal Krishnamurthy, Robin D. Morris:
Biomarker Detection from fMRI-Based Complete Functional Connectivity Networks. AIKE 2018: 17-24 - [c96]Soukaina Filali Boubrahimi, Ruizhe Ma, Berkay Aydin, Rafal A. Angryk:
Neuro-Ensemble. AIKE 2018: 54-61 - [c95]Soukaina Filali Boubrahimi, Rafal A. Angryk:
Multivariate Time Series Nearest Neighbor Search: A Case Study on Solar Flare Prediction. AIKE 2018: 162-163 - [c94]Soukaina Filali Boubrahimi, Rafal A. Angryk:
Heuristics Significance of Neuro-Ensemble-based Time Series Classification. IEEE BigData 2018: 6-15 - [c93]Ruizhe Ma, Azim Ahmadzadeh, Soukaina Filali Boubrahimi, Rafal A. Angryk:
Segmentation of Time Series in Improving Dynamic Time Warping. IEEE BigData 2018: 3756-3761 - [c92]Shah Muhammad Hamdi, Yubao Wu, Soukaina Filali Boubrahimi, Rafal A. Angryk, Lisa Crystal Krishnamurthy, Robin D. Morris:
Tensor Decomposition for Neurodevelopmental Disorder Prediction. BI 2018: 339-348 - [c91]Ruizhe Ma, Soukaina Filali Boubrahimi, Rafal A. Angryk:
Time Series Distance Density Cluster with Statistical Preprocessing. DaWaK 2018: 371-381 - [c90]Soukaina Filali Boubrahimi, Ruizhe Ma, Rafal A. Angryk:
Neuro-Ensemble for Time Series Data Classification. DSAA 2018: 50-59 - [c89]Soukaina Filali Boubrahimi, Ruizhe Ma, Berkay Aydin, Shah Muhammad Hamdi, Rafal A. Angryk:
Scalable kNN Search Approximation for Time Series Data. ICPR 2018: 970-975 - 2017
- [c88]Azim Ahmadzadeh, Dustin J. Kempton, Michael A. Schuh, Rafal A. Angryk:
Improving the functionality of tamura directionality on solar images. IEEE BigData 2017: 2518-2526 - [c87]Sunitha Basodi, Berkay Aydin, Rafal A. Angryk:
Parallel computation of magnetic field parameters from HMI active region patches. IEEE BigData 2017: 2527-2532 - [c86]Soukaina Filali Boubrahimi, Berkay Aydin, Petrus C. Martens, Rafal A. Angryk:
On the prediction of >100 MeV solar energetic particle events using GOES satellite data. IEEE BigData 2017: 2533-2542 - [c85]Shah Muhammad Hamdi, Dustin Kempton, Ruizhe Ma, Soukaina Filali Boubrahimi, Rafal A. Angryk:
A time series classification-based approach for solar flare prediction. IEEE BigData 2017: 2543-2551 - [c84]Ahmet Küçük, Berkay Aydin, Rafal A. Angryk:
Multi-wavelength solar event detection using faster R-CNN. IEEE BigData 2017: 2552-2558 - [c83]Ruizhe Ma, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Rafal A. Angryk:
Solar flare prediction using multivariate time series decision trees. IEEE BigData 2017: 2569-2578 - [c82]Sajitha Naduvil-Vadukootu, Rafal A. Angryk, Pete Riley:
Evaluating Preprocessing Strategies for Time Series Prediction using Deep Learning Architectures. FLAIRS 2017: 520-525 - [c81]Michael A. Schuh, Dustin Kempton, Rafal A. Angryk:
A Region-Based Retrieval System for Heliophysics Imagery. FLAIRS 2017: 526-531 - [c80]Ahmet Küçük, Juan M. Banda, Rafal A. Angryk:
Solar Event Classification Using Deep Convolutional Neural Networks. ICAISC (1) 2017: 118-130 - [c79]Michal Knop, Tomasz Kapuscinski, Rafal A. Angryk:
Neural Video Compression Based on PVQ Algorithm. ICAISC (1) 2017: 544-551 - [c78]Mariusz Zebik, Marcin Korytkowski, Rafal A. Angryk, Rafal Scherer:
Convolutional Neural Networks for Time Series Classification. ICAISC (2) 2017: 635-642 - [c77]Ruizhe Ma, Rafal A. Angryk:
Distance and Density Clustering for Time Series Data. ICDM Workshops 2017: 25-32 - [c76]Berkay Aydin, Ahmet Küçük, Soukaina Filali Boubrahimi, Rafal A. Angryk:
Top-(R%, K) Spatiotemporal Event Sequence Mining. ICDM Workshops 2017: 250-257 - [c75]Sajitha Naduvil-Vadukootu, Berkay Aydin, Michael A. Schuh, Rafal A. Angryk:
Cultivating Evolving Region Trajectory Datasets. ICDM Workshops 2017: 274-279 - [c74]Ahmet Küçük, Berkay Aydin, Soukaina Filali Boubrahimi, Dustin Kempton, Rafal A. Angryk:
An Integrated Solar Database (ISD) with Extended Spatiotemporal Querying Capabilities. SSTD 2017: 405-410 - 2016
- [c73]Vijay Akkineni, Berkay Aydin, Sajitha Naduvil-Vadukootu, Rafal A. Angryk:
Predictive Spatio-Temporal Query Processor on Resilient Distributed Datasets. BDCloud-SocialCom-SustainCom 2016: 50-58 - [c72]Ahmet Küçük, Shah Muhammad Hamdi, Berkay Aydin, Michael A. Schuh, Rafal A. Angryk:
Pg-Trajectory: A PostgreSQL/PostGIS Based Data Model for Spatiotemporal Trajectories. BDCloud-SocialCom-SustainCom 2016: 81-88 - [c71]Soukaina Filali Boubrahimi, Berkay Aydin, Dustin Kempton, Sushant S. Mahajan, Rafal A. Angryk:
Filling the Gaps in Solar Big Data: Interpolation of Solar Filament Event Instances. BDCloud-SocialCom-SustainCom 2016: 97-104 - [c70]Rafal A. Angryk, Douglas E. Galarus:
The SMART approach to comprehensive quality assessment of site-based spatial-temporal data. IEEE BigData 2016: 2636-2645 - [c69]Berkay Aydin, Ahmet Küçük, Rafal A. Angryk:
Indexing spatiotemporal relations in solar event datasets. IEEE BigData 2016: 3140-3148 - [c68]Soukaina Filali Boubrahimi, Berkay Aydin, Dustin Kempton, Rafal A. Angryk:
Spatio-temporal interpolation methods for solar events metadata. IEEE BigData 2016: 3149-3157 - [c67]Dustin J. Kempton, Michael A. Schuh, Rafal A. Angryk:
Describing solar images with sparse coding for similarity search. IEEE BigData 2016: 3168-3176 - [c66]Ruizhe Ma, Rafal A. Angryk, Pete Riley:
A data-driven analysis of interplanetary coronal mass ejecta and magnetic flux ropes. IEEE BigData 2016: 3177-3186 - [c65]Michael A. Schuh, Rafal A. Angryk:
On the theory and practice of high-dimensional data indexing with iDistance. IEEE BigData 2016: 3593-3600 - [c64]Berkay Aydin, Rafal A. Angryk:
Discovering spatiotemporal event sequences. MobiGIS 2016: 46-55 - [c63]Douglas E. Galarus, Rafal A. Angryk:
A SMART approach to quality assessment of site-based spatio-temporal data. SIGSPATIAL/GIS 2016: 55:1-55:4 - [c62]Soukaina Filali Boubrahimi, Berkay Aydin, Dustin Kempton, Rafal A. Angryk:
SOLEV: a video generation framework for solar events from mixed data sources (demo paper). SIGSPATIAL/GIS 2016: 90:1-90:4 - [c61]Dustin J. Kempton, Michael A. Schuh, Rafal A. Angryk:
Towards Feature Selection for Appearance Models in Solar Event Tracking. ICAISC (2) 2016: 88-101 - [c60]Wojciech K. Mleczko, Robert K. Nowicki, Rafal A. Angryk:
Rough Restricted Boltzmann Machine - New Architecture for Incomplete Input Data. ICAISC (1) 2016: 114-125 - [c59]Michal Knop, Tomasz Kapuscinski, Wojciech K. Mleczko, Rafal A. Angryk:
Neural Video Compression Based on RBM Scene Change Detection Algorithm. ICAISC (2) 2016: 660-669 - [c58]Michal Lagiewka, Rafal Scherer, Rafal A. Angryk:
Color-Based Large-Scale Image Retrieval with Limited Hardware Resources. ICAISC (2) 2016: 689-699 - [c57]Berkay Aydin, Rafal A. Angryk:
A Graph-Based Approach to Spatiotemporal Event Sequence Mining. ICDM Workshops 2016: 1090-1097 - [c56]Shah Muhammad Hamdi, Berkay Aydin, Rafal A. Angryk:
A Pattern Growth-Based Approach for Mining Spatiotemporal Co-occurrence Patterns. ICDM Workshops 2016: 1125-1132 - [c55]Berkay Aydin, Rafal A. Angryk:
Spatiotemporal event sequence mining from evolving regions. ICPR 2016: 4172-4177 - 2015
- [c54]Berkay Aydin, Vijay Akkineni, Rafal A. Angryk:
Time-efficient significance measure for discovering spatiotemporal co-occurrences from data with unbalanced characteristics. SIGSPATIAL/GIS 2015: 80:1-80:4 - [c53]Berkay Aydin, Rafal A. Angryk:
Spatiotemporal Frequent Pattern Mining on Solar Data: Current Algorithms and Future Directions. ICDM Workshops 2015: 575-581 - [c52]Juan M. Banda, Rafal A. Angryk:
Unsupervised Learning Techniques for Detection of Regions of Interest in Solar Images. ICDM Workshops 2015: 582-588 - 2014
- [c51]Bob Wall, Rafal A. Angryk:
Storing Long-Lived Concurrent Schema and Data Versions in Relational Databases. ADBIS (2) 2014: 97-108 - [c50]Berkay Aydin, Dustin Kempton, Vijay Akkineni, Shaktidhar Reddy Gopavaram, Karthik Ganesan Pillai, Rafal A. Angryk:
Spatiotemporal indexing techniques for efficiently mining spatiotemporal co-occurrence patterns. IEEE BigData 2014: 1-10 - [c49]Juan M. Banda, Rafal A. Angryk:
Scalable solar image Retrieval with Lucene. IEEE BigData 2014: 11-17 - [c48]Dustin Kempton, Karthik Ganesan Pillai, Rafal A. Angryk:
Iterative refinement of multiple targets tracking of solar events. IEEE BigData 2014: 36-44 - [c47]Michael A. Schuh, Rafal A. Angryk:
Massive labeled solar image data benchmarks for automated feature recognition. IEEE BigData 2014: 53-60 - [c46]Michael A. Schuh, Tim Wylie, Chang Liu, Rafal A. Angryk:
Approximating High-Dimensional Range Queries with kNN Indexing Techniques. COCOON 2014: 369-380 - [c45]Berkay Aydin, Rafal A. Angryk, Karthik Ganesan Pillai:
ERMO-DG: Evolving Region Moving Object Dataset Generator. FLAIRS 2014 - [c44]Michael A. Schuh, Tim Wylie, Rafal A. Angryk:
Mitigating the Curse of Dimensionality for Exact kNN Retrieval. FLAIRS 2014 - [c43]Douglas E. Galarus, Rafal A. Angryk:
Quality control from the perspective of a near-real-time, spatial-temporal data aggregator and (re)distributor. SIGSPATIAL/GIS 2014: 389-392 - [c42]Juan M. Banda, Rafal A. Angryk:
Large-Scale Region-Based Multimedia Retrieval for Solar Images. ICAISC (1) 2014: 649-661 - [c41]Juan M. Banda, Rafal A. Angryk, Michael A. Schuh, Petrus C. Martens:
Image retrieval on compressed images: Can we tell the difference? IPTA 2014: 235-240 - 2013
- [c40]Karthik Ganesan Pillai, Rafal A. Angryk, Juan M. Banda, Tim Wylie, Michael A. Schuh:
Spatiotemporal Co-occurrence Rules. ADBIS (2) 2013: 27-35 - [c39]Juan M. Banda, Michael A. Schuh, Tim Wylie, Patrick McInerney, Rafal A. Angryk:
When Too Similar Is Bad: A Practical Example of the Solar Dynamics Observatory Content-Based Image-Retrieval System. ADBIS (2) 2013: 87-95 - [c38]Juan M. Banda, Michael A. Schuh, Rafal A. Angryk, Karthik Ganesan Pillai, Patrick McInerney:
Big Data New Frontiers: Mining, Search and Management of Massive Repositories of Solar Image Data and Solar Events. ADBIS (2) 2013: 151-158 - [c37]Michael A. Schuh, Tim Wylie, Rafal A. Angryk:
Improving the Performance of High-Dimensional kNN Retrieval through Localized Dataspace Segmentation and Hybrid Indexing. ADBIS 2013: 344-357 - [c36]Michael A. Schuh, Tim Wylie, Juan M. Banda, Rafal A. Angryk:
A Comprehensive Study of iDistance Partitioning Strategies for kNN Queries and High-Dimensional Data Indexing. BNCOD 2013: 238-252 - [c35]Karthik Ganesan Pillai, Liessman Sturlaugson, Juan M. Banda, Rafal A. Angryk:
Extending High-Dimensional Indexing Techniques Pyramid and iMinMax(θ): Lessons Learned. BNCOD 2013: 253-267 - [c34]Tim Wylie, Michael A. Schuh, John W. Sheppard, Rafal A. Angryk:
Cluster Analysis for Optimal Indexing. FLAIRS 2013 - [c33]Douglas E. Galarus, Rafal A. Angryk:
Mining robust neighborhoods for quality control of sensor data. IWGS 2013: 86-95 - [c32]Karthik Ganesan Pillai, Rafal A. Angryk, Berkay Aydin:
A filter-and-refine approach to mine spatiotemporal co-occurrences. SIGSPATIAL/GIS 2013: 104-113 - [c31]Juan M. Banda, Chang Liu, Rafal A. Angryk:
Region-Based Querying of Solar Data Using Descriptor Signatures. ICDM Workshops 2013: 1-7 - [c30]Patrick M. McInerney, Juan M. Banda, Rafal A. Angryk:
On Using SIFT Descriptors for Image Parameter Evaluation. ICDM Workshops 2013: 32-39 - [c29]Michael A. Schuh, Rafal A. Angryk, Karthik Ganesan Pillai, Juan M. Banda, Petrus C. Martens:
A large-scale solar image dataset with labeled event regions. ICIP 2013: 4349-4353 - 2012
- [c28]Juan M. Banda, Rafal A. Angryk, Petrus C. Martens:
Quantitative Comparison of Linear and Non-linear Dimensionality Reduction Techniques for Solar Image Archives. FLAIRS 2012 - [c27]Douglas E. Galarus, Rafal A. Angryk, John W. Sheppard:
Automated Weather Sensor Quality Control. FLAIRS 2012 - [c26]Michael A. Schuh, Rafal A. Angryk, John W. Sheppard:
Evolving Kernel Functions with Particle Swarms and Genetic Programming. FLAIRS 2012 - [c25]Karthik Ganesan Pillai, Rafal A. Angryk, Juan M. Banda, Michael A. Schuh, Tim Wylie:
Spatio-temporal Co-occurrence Pattern Mining in Data Sets with Evolving Regions. ICDM Workshops 2012: 805-812 - 2011
- [c24]Bob Wall, Rafal A. Angryk:
Minimal data sets vs. synchronized data copies in a schema and data versioning system. PIKM@CIKM 2011: 67-74 - [c23]Juan M. Banda, Rafal A. Angryk, Petrus C. Martens:
On the surprisingly accurate transfer of image parameters between medical and solar images. ICIP 2011: 3669-3672 - [c22]Rafal A. Angryk, Mahmud Shahriar Hossain, Brandon Norick:
Semantically-Guided Clustering of Text Documents via Frequent Subgraphs Discovery. ISMIS 2011: 407-417 - 2010
- [c21]Juan M. Banda, Rafal A. Angryk:
Usage of Dissimilarity Measures and Multidimensional Scaling for Large Scale Solar Data Analysis. CIDU 2010: 189-203 - [c20]Juan M. Banda, Rafal A. Angryk:
Selection of Image Parameters as the First Step towards Creating a CBIR System for the Solar Dynamics Observatory. DICTA 2010: 528-534 - [c19]Juan M. Banda, Rafal A. Angryk:
An Experimental Evaluation of Popular Image Parameters for Monochromatic Solar Image Categorization. FLAIRS 2010 - [c18]Atanu Roy, Chandrima Sarkar, Rafal A. Angryk:
Using Taxonomies to Perform Aggregated Querying over Imprecise Data. ICDM Workshops 2010: 989-996 - 2009
- [c17]Richard A. McAllister, Rafal A. Angryk:
An Abstraction-Based Data Model for Information Retrieval. Australasian Conference on Artificial Intelligence 2009: 567-576 - [c16]Juan M. Banda, Rafal A. Angryk:
On the effectiveness of fuzzy clustering as a data discretization technique for large-scale classification of solar images. FUZZ-IEEE 2009: 2019-2024 - 2008
- [c15]Monika Akbar, Rafal A. Angryk:
Frequent pattern-growth approach for document organization. ONISW 2008: 77-82 - [c14]Robbie Lamb, Rafal A. Angryk, Piet Martiens:
An example based image retrieval system for the TRACE repository. ICPR 2008: 1-4 - 2007
- [c13]Debzani Deb, Rafal A. Angryk:
Distributed Document Clustering Using Word-clusters. CIDM 2007: 376-383 - [c12]Mahmud Shahriar Hossain, Rafal A. Angryk:
GDClust: A Graph-Based Document Clustering Technique. ICDM Workshops 2007: 417-422 - [c11]Mahmud Shahriar Hossain, Rafal A. Angryk:
Algorithm for Interpretation of Multi-valued Taxonomic Attributes in Similarity-Based Fuzzy Databases. IFSA (2) 2007: 23-35 - [c10]Mahmud Shahriar Hossain, Monika Akbar, Rafal A. Angryk:
Sense based organization of descriptive data. SMC 2007: 468-473 - [c9]Shen Wan, Rafal A. Angryk:
Measuring semantic similarity using wordnet-based context vectors. SMC 2007: 908-913 - 2006
- [c8]Debzani Deb, M. Muztaba Fuad, Rafal A. Angryk:
Distributed hierarchical document clustering. ACST 2006: 328-333 - [c7]Jacob Dolan, Rafal A. Angryk:
Automated Generalization of Fuzzy Concept Hierarchies for Attribute-Oriented Induction Purposes. Databases and Applications 2006: 66-74 - [c6]Rafal A. Angryk:
Similarity-driven Defuzzification of Fuzzy Tuples for Entropy-based Data Classification Purposes. FUZZ-IEEE 2006: 414-422 - [c5]Rafal A. Angryk:
On Interpretation of Non-atomic Values and Induction of Decision Rules in Fuzzy Relational Databases. ICAISC 2006: 170-181 - 2005
- [c4]Rafal A. Angryk, Frederick E. Petry:
Mining Multi-Level Associations with Fuzzy Hierarchies. FUZZ-IEEE 2005: 785-790 - 2004
- [c3]Rafal A. Angryk, Costin Barbu:
Fuzzy Induction in Dynamic User Profiling for Information Filtering. AAAI 2004: 946-947 - [c2]Costin Barbu, Rafal A. Angryk, Frederick E. Petry, Marin Simina:
Information filtering via fuzzy hierarchical induction. SMC (4) 2004: 3576-3581 - 2002
- [c1]Rafal A. Angryk, Violetta Galant, Minor Gordon, Marcin Paprzycki:
Travel Support System - an Agent-Biased Framework. International Conference on Internet Computing 2002: 719-725
Parts in Books or Collections
- 2008
- [p2]Bob Wall, Neal Richter, Rafal A. Angryk:
Generating Concept Hierarchies from User Queries. Data Mining: Foundations and Practice 2008: 423-441 - 2006
- [p1]Rafal A. Angryk, Frederick E. Petry:
Knowledge Discovery in Fuzzy Databases Using Attribute-Oriented Induction. Foundations and Novel Approaches in Data Mining 2006: 169-196
Editorship
- 2016
- [e1]Zhipeng Cai, Rafal A. Angryk, Wen-Zhan Song, Yingshu Li, Xiaojun Cao, Anu G. Bourgeois, Guangchun Luo, Liang Cheng, Bhaskar Krishnamachari:
2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom), BDCloud-SocialCom-SustainCom 2016, Atlanta, GA, USA, October 8-10, 2016. IEEE Computer Society 2016, ISBN 978-1-5090-3936-4 [contents]
Data and Artifacts
- 2022
- [d1]Anli Ji, Nigar Khasayeva, Xumin Cai, Manolis K. Georgoulis, Petrus C. Martens, Rafal A. Angryk, Berkay Aydin:
Magnetic Polarity Inversion Line Detection and Analysis Tool. Zenodo, 2022
Informal and Other Publications
- 2024
- [i22]Yang Chen, Dustin J. Kempton, Rafal A. Angryk:
FFAD: A Novel Metric for Assessing Generated Time Series Data Utilizing Fourier Transform and Auto-encoder. CoRR abs/2403.06576 (2024) - [i21]Junzhi Wen, Rafal A. Angryk:
Class-Based Time Series Data Augmentation to Mitigate Extreme Class Imbalance for Solar Flare Prediction. CoRR abs/2405.20590 (2024) - [i20]Chetraj Pandey, Temitope Adeyeha, Jinsu Hong, Rafal A. Angryk, Berkay Aydin:
Advancing Solar Flare Prediction using Deep Learning with Active Region Patches. CoRR abs/2406.11054 (2024) - [i19]Chetraj Pandey, Anli Ji, Jinsu Hong, Rafal A. Angryk, Berkay Aydin:
Embedding Ordinality to Binary Loss Function for Improving Solar Flare Forecasting. CoRR abs/2408.11768 (2024) - 2023
- [i18]Chetraj Pandey, Rafal A. Angryk, Berkay Aydin:
Explaining Full-disk Deep Learning Model for Solar Flare Prediction using Attribution Methods. CoRR abs/2307.15878 (2023) - [i17]Chetraj Pandey, Rafal A. Angryk, Manolis K. Georgoulis, Berkay Aydin:
Explainable Deep Learning-based Solar Flare Prediction with post hoc Attention for Operational Forecasting. CoRR abs/2308.02682 (2023) - [i16]Chetraj Pandey, Anli Ji, Trisha Nandakumar, Rafal A. Angryk, Berkay Aydin:
Exploring Deep Learning for Full-disk Solar Flare Prediction with Empirical Insights from Guided Grad-CAM Explanations. CoRR abs/2308.15712 (2023) - [i15]Chetraj Pandey, Anli Ji, Rafal A. Angryk, Berkay Aydin:
Towards Interpretable Solar Flare Prediction with Attention-based Deep Neural Networks. CoRR abs/2309.04558 (2023) - [i14]Chetraj Pandey, Rafal A. Angryk, Berkay Aydin:
Unveiling the Potential of Deep Learning Models for Solar Flare Prediction in Near-Limb Regions. CoRR abs/2309.14483 (2023) - 2022
- [i13]Junzhi Wen, Md Reazul Islam, Azim Ahmadzadeh, Rafal A. Angryk:
Improving Solar Flare Prediction by Time Series Outlier Detection. CoRR abs/2206.07197 (2022) - [i12]Azim Ahmadzadeh, Rafal A. Angryk:
Measuring Class-Imbalance Sensitivity of Deterministic Performance Evaluation Metrics. CoRR abs/2206.09981 (2022) - [i11]Chetraj Pandey, Anli Ji, Rafal A. Angryk, Manolis K. Georgoulis, Berkay Aydin:
Towards Coupling Full-disk and Active Region-based Flare Prediction for Operational Space Weather Forecasting. CoRR abs/2209.07406 (2022) - 2021
- [i10]Azim Ahmadzadeh, Berkay Aydin, Manolis K. Georgoulis, Dustin J. Kempton, Sushant S. Mahajan, Rafal A. Angryk:
How to Train Your Flare Prediction Model: Revisiting Robust Sampling of Rare Events. CoRR abs/2103.07542 (2021) - [i9]Anli Ji, Berkay Aydin, Manolis K. Georgoulis, Rafal A. Angryk:
All-Clear Flare Prediction Using Interval-based Time Series Classifiers. CoRR abs/2105.01202 (2021) - [i8]Yang Chen, Dustin J. Kempton, Azim Ahmadzadeh, Rafal A. Angryk:
Towards Synthetic Multivariate Time Series Generation for Flare Forecasting. CoRR abs/2105.07532 (2021) - [i7]Azim Ahmadzadeh, Dustin J. Kempton, Yang Chen, Rafal A. Angryk:
Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures. CoRR abs/2105.14572 (2021) - [i6]Atharv Yeolekar, Sagar Patel, Shreejaa Talla, Krishna Rukmini Puthucode, Azim Ahmadzadeh, Viacheslav M. Sadykov, Rafal A. Angryk:
Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 Methods. CoRR abs/2109.14770 (2021) - 2020
- [i5]Gelu Nita, Manolis K. Georgoulis, Irina Kitiashvili, Viacheslav Sadykov, Enrico Camporeale, Alexander Kosovichev, Haimin Wang, Vincent Oria, Jason T. L. Wang, Rafal A. Angryk, Berkay Aydin, Azim Ahmadzadeh, Xiaoli Bai, Timothy Bastian, Soukaina Filali Boubrahimi, Bin Chen, Alisdair Davey, Sheldon Fereira, Gregory Fleishman, Dale Gary, Andrew Gerrard, Gregory Hellbourg, Katherine Herbert, Jack Ireland, Egor Illarionov, Natsuha Kuroda, Qin Li, Chang Liu, Yuexin Liu, Hyomin Kim, Dustin Kempton, Ruizhe Ma, Petrus C. Martens, Ryan M. McGranaghan, Edward Semones, John T. Stefan, Andrey Stejko, Yaireska Collado-Vega, Meiqi Wang, Yan Xu, Sijie Yu:
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations. CoRR abs/2006.12224 (2020) - 2019
- [i4]Azim Ahmadzadeh, Dustin J. Kempton, Rafal A. Angryk:
A Curated Image Parameter Dataset from Solar Dynamics Observatory Mission. CoRR abs/1906.01062 (2019) - [i3]Azim Ahmadzadeh, Maxwell Hostetter, Berkay Aydin, Manolis K. Georgoulis, Dustin J. Kempton, Sushant S. Mahajan, Rafal A. Angryk:
Challenges with Extreme Class-Imbalance and Temporal Coherence: A Study on Solar Flare Data. CoRR abs/1911.09061 (2019) - [i2]Azim Ahmadzadeh, Sushant S. Mahajan, Dustin J. Kempton, Rafal A. Angryk, Shihao Ji:
Toward Filament Segmentation Using Deep Neural Networks. CoRR abs/1912.02743 (2019) - 2011
- [i1]Mahmud Shahriar Hossain, Rafal A. Angryk:
Heuristic Algorithm for Interpretation of Non-Atomic Categorical Attributes in Similarity-based Fuzzy Databases - Scalability Evaluation. CoRR abs/1103.5795 (2011)
Coauthor Index
[j21] [j19] [j16] [j15] [j12] [j6] [c133] [c132] [c131] [c130] [c128] [c127] [c124] [c122] [c121] [c116] [c114] [c112] [c110] [c109] [c108] [c107] [c106] [c104] [c103] [c98] [c97] [c96] [c89] [c87] [c86] [c84] [c76] [c75] [c74] [c73] [c72] [c71] [c69] [c68] [c64] [c62] [c57] [c56] [c55] [c54] [c53] [c50] [c45] [c32] [d1] [i20] [i19] [i18] [i17] [i16] [i15] [i14] [i11] [i10] [i9] [i5] [i3]
Soukaina Filali Boubrahimi
aka: Soukaïna Filali Boubrahimi
aka: Soukaïna Filali Boubrahimi
Dustin Kempton
aka: Dustin J. Kempton
aka: Dustin J. Kempton
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