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ORCIDIrena Koprinska
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- affiliation: University of Sydney, Australia
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2020 – today
- 2024
[c114]Ziwei Wang
, Irena Koprinska, Bryn Jeffries:
Interpretable Methods for Early Prediction of Student Performance in Programming Courses. AIED Companion (2) 2024: 115-123- [c113]Ka Weng Pan, Bryn Jeffries, Irena Koprinska:
Predicting Successful Programming Submissions Based on Critical Logic Blocks. AIED (2) 2024: 363-371 - 2023
- [j22]Ling Luo, Bin Li, Xuhui Fan, Yang Wang, Irena Koprinska, Fang Chen:
Dynamic customer segmentation via hierarchical fragmentation-coagulation processes. Mach. Learn. 112(1): 281-310 (2023) - [j21]Eileen Wang, Irena Koprinska, Bryn Jeffries:
Sleep Apnea Prediction Using Deep Learning. IEEE J. Biomed. Health Informatics 27(11): 5644-5654 (2023) - [c112]Enqi Liu, Irena Koprinska, Kalina Yacef:
Early Prediction of Student Performance in Online Programming Courses. AIED (Posters/Late Breaking Results/...) 2023: 365-371 - [c111]Vincent Zhang, Bryn Jeffries, Irena Koprinska:
Predicting Progress in a Large-Scale Online Programming Course. AIED 2023: 810-816 - [c110]Gavin Fungtammasan, Irena Koprinska:
Convolutional and LSTM Neural Networks for Solar Power Forecasting. IJCNN 2023: 1-7 - [e5]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e4]Irena Koprinska, Paolo Mignone, Riccardo Guidotti, Szymon Jaroszewicz, Holger Fröning, Francesco Gullo, Pedro M. Ferreira, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk, João Gama, Rita P. Ribeiro, Ricard Gavaldà, Elio Masciari, Zbigniew W. Ras, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek, Wouter Verbeke, Gregor Schiele, Franz Pernkopf, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice, Giuseppina Andresini, Ibéria Medeiros, Guilherme Graça, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Diego Saldana Miranda, Konstantinos Sechidis, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet, Sepideh Pashami:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - 2022
- [j20]Jessica McBroom, Irena Koprinska, Kalina Yacef:
A Survey of Automated Programming Hint Generation: The HINTS Framework. ACM Comput. Surv. 54(8): 172:1-172:27 (2022) - [j19]Benjamin Paaßen, Irena Koprinska, Kalina Yacef:
Recursive tree grammar autoencoders. Mach. Learn. 111(9): 3393-3423 (2022) - [c109]Sophia Polito, Irena Koprinska, Bryn Jeffries:
Exploring Student Engagement in an Online Programming Course Using Machine Learning Methods. AIED (2) 2022: 546-550 - [c108]Jung A Lee, Irena Koprinska, Bryn Jeffries:
Data Mining of Syntax Errors in a Large-Scale Online Python Course. AIED (2) 2022: 599-603 - [c107]Filip Schlembach, Evgueni N. Smirnov, Irena Koprinska:
Conformal Multistep-Ahead Multivariate Time-Series Forecasting. COPA 2022: 316-318 - [c106]Gio Picones, Benjamin Paaßen, Irena Koprinska, Kalina Yacef:
Combining domain modelling and student modelling techniques in a single automated pipeline. EDM 2022 - [c105]Bryn Jeffries, Jung A Lee, Irena Koprinska:
115 Ways Not to Say Hello, World!: Syntax Errors Observed in a Large-Scale Online CS0 Python Course. ITiCSE (1) 2022: 337-343 - [c104]Stephen McCloskey, Bryn Jeffries, Irena Koprinska, Christopher James Gordon, Ronald R. Grunstein:
Insomnia Disorder Detection Using EEG Sleep Trajectories. PAKDD (3) 2022: 314-325 - [r2]Irena Koprinska, Kalina Yacef:
People-to-People Reciprocal Recommenders. Recommender Systems Handbook 2022: 421-446 - 2021
- [c103]Jessica McBroom, Benjamin Paassen, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
Progress Networks as a Tool for Analysing Student Programming Difficulties. ACE 2021: 158-167 - [c102]Benjamin Paaßen, Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
ast2vec: Utilizing Recursive Neural Encodings of Python Programs. EDM 2021 - [c101]Benjamin Paaßen, Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
Next Steps for Next-step Hints: Lessons Learned from Teacher Evaluations of Automatic Programming Hints (Full Paper). EDM (Workshops) 2021 - [c100]Yang Gao, Mahnoosh Kholghi, Irena Koprinska, Qing Zhang:
Association of Longitudinal Sleep and Next-day Indoor Mobility Measured via Passive Sensors among Community-dwelling Older Adults. EMBC 2021: 2400-2404 - [c99]Yang Lin, Irena Koprinska, Mashud Rana:
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting. ICDM 2021: 370-378 - [c98]Yang Lin, Irena Koprinska, Mashud Rana:
Temporal Convolutional Attention Neural Networks for Time Series Forecasting. IJCNN 2021: 1-8 - [e3]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e2]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i6]Benjamin Paaßen, Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
ast2vec: Utilizing Recursive Neural Encodings of Python Programs. CoRR abs/2103.11614 (2021) - [i5]Yang Lin, Irena Koprinska, Mashud Rana:
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting. CoRR abs/2112.10251 (2021) - 2020
- [j18]Jisu Jung, Lyndal Wellard-Cole, Colin Cai, Irena Koprinska, Kalina Yacef, Margaret Allman-Farinelli, Judy Kay:
Foundations for Systematic Evaluation and Benchmarking of a Mobile Food Logger in a Large-scale Nutrition Study. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(2): 47:1-47:25 (2020) - [j17]Ronnie Taib, Shlomo Berkovsky, Irena Koprinska, Eileen Wang, Yucheng Zeng, Jingjie Li:
Personality Sensing: Detection of Personality Traits Using Physiological Responses to Image and Video Stimuli. ACM Trans. Interact. Intell. Syst. 10(3): 18:1-18:32 (2020) - [c97]Jessica McBroom, Irena Koprinska, Kalina Yacef:
Understanding Gender Differences to Improve Equity in Computer Programming Education. ACE 2020: 185-194 - [c96]Jessica McBroom, Kalina Yacef, Irena Koprinska:
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data. AIED (1) 2020: 374-385 - [c95]Jessica McBroom, Irena Koprinska, Kalina Yacef:
How Does Student Behaviour Change Approaching Dropout? A Study of Gender and School Year Differences. EDM 2020 - [c94]Jessica McBroom, Kalina Yacef, Irena Koprinska:
Scalability in Online Computer Programming Education: Automated Techniques for Feedback, Evaluation and Equity. EDM 2020 - [c93]Roneel V. Sharan, Shlomo Berkovsky, Ronnie Taib, Irena Koprinska, Jingjie Li:
Detecting Personality Traits Using Inter-Hemispheric Asynchrony of the Brainwaves. EMBC 2020: 62-65 - [c92]Yang Lin, Irena Koprinska, Mashud Rana, Alicia Troncoso:
Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning. ICANN (1) 2020: 271-283 - [c91]Yang Lin, Irena Koprinska, Mashud Rana:
SpringNet: Transformer and Spring DTW for Time Series Forecasting. ICONIP (3) 2020: 616-628 - [c90]Zezhou Chen, Irena Koprinska:
Ensemble Methods for Solar Power Forecasting. IJCNN 2020: 1-8 - [c89]Rim Haidar, Irena Koprinska, Bryn Jeffries:
Sleep Apnea Event Prediction Using Convolutional Neural Networks and Markov Chains. IJCNN 2020: 1-8 - [c88]Yang Lin, Irena Koprinska, Mashud Rana:
Temporal Convolutional Neural Networks for Solar Power Forecasting. IJCNN 2020: 1-8 - [c87]Benjamin Paassen, Irena Koprinska, Kalina Yacef:
Tree Echo State Autoencoders with Grammars. IJCNN 2020: 1-8 - [e1]Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [i4]Benjamin Paassen, Irena Koprinska, Kalina Yacef:
Tree Echo State Autoencoders with Grammars. CoRR abs/2004.08925 (2020) - [i3]Jessica McBroom, Kalina Yacef, Irena Koprinska:
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data. CoRR abs/2005.10640 (2020) - [i2]Benjamin Paassen, Irena Koprinska, Kalina Yacef:
Recursive Tree Grammar Autoencoders. CoRR abs/2012.02097 (2020)
2010 – 2019
- 2019
- [j16]José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez:
Big data solar power forecasting based on deep learning and multiple data sources. Expert Syst. J. Knowl. Eng. 36(4) (2019) - [j15]Antonio Galicia, Ricardo L. Talavera-Llames, Alicia Troncoso Lora, Irena Koprinska, Francisco Martínez-Álvarez:
Multi-step forecasting for big data time series based on ensemble learning. Knowl. Based Syst. 163: 830-841 (2019) - [j14]Givanna H. Putri, Mark N. Read, Irena Koprinska, Deeksha Singh, Uwe Röhm, Thomas M. Ashhurst, Nicholas J. C. King:
ChronoClust: Density-based clustering and cluster tracking in high-dimensional time-series data. Knowl. Based Syst. 174: 9-26 (2019) - [j13]Stephen McCloskey, Bryn Jeffries, Irena Koprinska, Christopher B. Miller, Ronald R. Grunstein:
Data-driven cluster analysis of insomnia disorder with physiology-based qEEG variables. Knowl. Based Syst. 183 (2019) - [c86]Shlomo Berkovsky, Ronnie Taib, Irena Koprinska, Eileen Wang, Yucheng Zeng, Jingjie Li, Sabina Kleitman:
Detecting Personality Traits Using Eye-Tracking Data. CHI 2019: 221 - [c85]Irena Koprinska, Mashud Rana, Ashfaqur Rahman:
Dynamic Ensemble Using Previous and Predicted Future Performance for Multi-step-ahead Solar Power Forecasting. ICANN (4) 2019: 436-449 - [c84]Givanna H. Putri, Mark N. Read, Irena Koprinska, Thomas M. Ashhurst, Nicholas J. C. King:
Dimensionality Reduction for Clustering and Cluster Tracking of Cytometry Data. ICANN (4) 2019: 624-640 - [c83]Rim Haidar, Irena Koprinska, Bryn Jeffries:
Feature Learning and Data Compression of Biosignals Using Convolutional Autoencoders for Sleep Apnea Detection. ICONIP (1) 2019: 162-174 - [c82]Yang Lin, Irena Koprinska, Mashud Rana, Alicia Troncoso:
Pattern Sequence Neural Network for Solar Power Forecasting. ICONIP (5) 2019: 727-737 - [i1]Jessica McBroom, Irena Koprinska, Kalina Yacef:
A Survey of Automated Programming Hint Generation - The HINTS Framework. CoRR abs/1908.11566 (2019) - 2018
- [c81]Jessica McBroom, Kalina Yacef, Irena Koprinska, James R. Curran:
A Data-Driven Method for Helping Teachers Improve Feedback in Computer Programming Automated Tutors. AIED (1) 2018: 324-337 - [c80]Zheng Wang, Irena Koprinska:
Solar Power Forecasting Using Dynamic Meta-Learning Ensemble of Neural Networks. ICANN (1) 2018: 528-537 - [c79]Rim Haidar, Stephen McCloskey, Irena Koprinska, Bryn Jeffries:
Convolutional Neural Networks on Multiple Respiratory Channels to Detect Hypopnea and Obstructive Apnea Events. IJCNN 2018: 1-7 - [c78]Irena Koprinska, Dengsong Wu, Zheng Wang:
Convolutional Neural Networks for Energy Time Series Forecasting. IJCNN 2018: 1-8 - [c77]Zheng Wang, Irena Koprinska, Alicia Troncoso, Francisco Martínez-Álvarez:
Static and Dynamic Ensembles of Neural Networks for Solar Power Forecasting. IJCNN 2018: 1-8 - [c76]Stephen McCloskey, Rim Haidar, Irena Koprinska, Bryn Jeffries:
Detecting Hypopnea and Obstructive Apnea Events Using Convolutional Neural Networks on Wavelet Spectrograms of Nasal Airflow. PAKDD (1) 2018: 361-372 - [c75]José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez:
Deep Learning for Big Data Time Series Forecasting Applied to Solar Power. SOCO-CISIS-ICEUTE 2018: 123-133 - 2017
- [j12]Ahmed Al-Ani, Irena Koprinska, Ganesh R. Naik:
Dynamically identifying relevant EEG channels by utilizing channels classification behaviour. Expert Syst. Appl. 83: 273-282 (2017) - [j11]Ling Luo, Wei Liu, Irena Koprinska, Fang Chen:
DAAR: A Discrimination-Aware Association Rule Classifier for Decision Support. Trans. Large Scale Data Knowl. Centered Syst. 32: 47-68 (2017) - [c74]Zheng Wang, Irena Koprinska, Mashud Rana:
Solar Power Forecasting Using Pattern Sequences. ICANN (2) 2017: 486-494 - [c73]Rim Haidar, Irena Koprinska, Bryn Jeffries:
Sleep Apnea Event Detection from Nasal Airflow Using Convolutional Neural Networks. ICONIP (5) 2017: 819-827 - [c72]Ling Luo, Bin Li, Irena Koprinska, Shlomo Berkovsky, Fang Chen:
Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process. IJCAI 2017: 2414-2420 - [c71]Zheng Wang, Irena Koprinska:
Solar power prediction with data source weighted nearest neighbors. IJCNN 2017: 1411-1418 - [c70]Zheng Wang, Irena Koprinska, Mashud Rana:
Solar power prediction using weather type pair patterns. IJCNN 2017: 4259-4266 - [c69]Sammi Chow, Kalina Yacef, Irena Koprinska, James R. Curran:
Automated Data-Driven Hints for Computer Programming Students. UMAP (Adjunct Publication) 2017: 5-10 - [c68]Kurt Driessens, Irena Koprinska, Olga C. Santos, Evgueni N. Smirnov, Kalina Yacef, Osmar R. Zaïane:
UMAP 2017 EdRecSys Workshop Organizers' Welcome & Organization. UMAP (Adjunct Publication) 2017: 125-127 - [c67]Ling Luo, Bin Li, Shlomo Berkovsky, Irena Koprinska, Fang Chen:
Online Engagement for a Healthier You: A Case Study of Web-based Supermarket Health Program. WWW (Companion Volume) 2017: 1053-1061 - 2016
- [j10]Mashud Rana, Irena Koprinska:
Forecasting electricity load with advanced wavelet neural networks. Neurocomputing 182: 118-132 (2016) - [c66]Vincent Gramoli, Michael A. Charleston, Bryn Jeffries, Irena Koprinska, Martin McGrane, Alex Radu, Anastasios Viglas, Kalina Yacef:
Mining autograding data in computer science education. ACSW 2016: 1 - [c65]Ling Luo, Bin Li, Irena Koprinska, Shlomo Berkovsky, Fang Chen:
Discovering Temporal Purchase Patterns with Different Responses to Promotions. CIKM 2016: 2197-2202 - [c64]Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
Mining behaviors of students in autograding submission system logs. EDM 2016: 159-166 - [c63]Jessica McBroom, Bryn Jeffries, Irena Koprinska, Kalina Yacef:
Exploring and Following Students' Strategies When Completing Their Weekly Tasks. EDM 2016: 609-610 - [c62]Mashud Rana, Irena Koprinska, Alicia Troncoso, Vassilios G. Agelidis:
Extended Weighted Nearest Neighbor for Electricity Load Forecasting. ICANN (2) 2016: 299-307 - [c61]Zheng Wang, Irena Koprinska, Mashud Rana:
Clustering based methods for solar power forecasting. IJCNN 2016: 1487-1494 - [c60]Ahmed Al-Ani, Irena Koprinska, Ganesh R. Naik, Rami N. Khushaba:
A dynamic channel selection algorithm for the classification of EEG and EMG data. IJCNN 2016: 4076-4081 - [c59]Mashud Rana, Irena Koprinska, Vassilios G. Agelidis:
Solar power forecasting using weather type clustering and ensembles of neural networks. IJCNN 2016: 4962-4969 - [c58]Ling Luo, Bin Li, Shlomo Berkovsky, Irena Koprinska, Fang Chen:
Who Will Be Affected by Supermarket Health Programs? Tracking Customer Behavior Changes via Preference Modeling. PAKDD (1) 2016: 527-539 - 2015
- [j9]Irena Koprinska, Mashud Rana, Vassilios G. Agelidis:
Correlation and instance based feature selection for electricity load forecasting. Knowl. Based Syst. 82: 29-40 (2015) - [c57]Irena Koprinska, Joshua Stretton, Kalina Yacef:
Predicting Student Performance from Multiple Data Sources. AIED 2015: 678-681 - [c56]Ling Luo, Wei Liu, Irena Koprinska, Fang Chen:
Discovering Causal Structures from Time Series Data via Enhanced Granger Causality. Australasian Conference on Artificial Intelligence 2015: 365-378 - [c55]Ling Luo, Wei Liu, Irena Koprinska, Fang Chen:
Discrimination-Aware Association Rule Mining for Unbiased Data Analytics. DaWaK 2015: 108-120 - [c54]Ling Luo, Irena Koprinska, Wei Liu:
Discrimination-Aware Classifiers for Student Performance Prediction. EDM 2015: 384-387 - [c53]Irena Koprinska, Joshua Stretton, Kalina Yacef:
Students at Risk: Detection and Remediation. EDM 2015: 512-515 - [c52]Tommaso Colombo, Irena Koprinska, Massimo Panella:
Maximum Length Weighted Nearest Neighbor approach for electricity load forecasting. IJCNN 2015: 1-8 - [c51]Mashud Rana, Irena Koprinska, Vassilios G. Agelidis:
Forecasting solar power generated by grid connected PV systems using ensembles of neural networks. IJCNN 2015: 1-8 - [r1]Irena Koprinska, Kalina Yacef:
People-to-People Reciprocal Recommenders. Recommender Systems Handbook 2015: 545-567 - 2014
- [c50]Mashud Rana, Irena Koprinska, Alicia Troncoso Lora:
Forecasting hourly electricity load profile using neural networks. IJCNN 2014: 824-831 - 2013
- [j8]Luiz Augusto Sangoi Pizzato, Tomasz Rej, Joshua Akehurst, Irena Koprinska, Kalina Yacef, Judy Kay:
Recommending people to people: the nature of reciprocal recommenders with a case study in online dating. User Model. User Adapt. Interact. 23(5): 447-488 (2013) - [c49]Timothy O'Keefe, James R. Curran, Peter Ashwell, Irena Koprinska:
An annotated corpus of quoted opinions in news articles. ACL (2) 2013: 516-520 - [c48]Timothy O'Keefe, Kellie Webster, James R. Curran, Irena Koprinska:
Examining the Impact of Coreference Resolution on Quote Attribution. ALTA 2013: 43-52 - [c47]Silvia Pareti, Timothy O'Keefe, Ioannis Konstas, James R. Curran, Irena Koprinska:
Automatically Detecting and Attributing Indirect Quotations. EMNLP 2013: 989-999 - [c46]Mashud Rana, Irena Koprinska, Abbas Khosravi:
Feature Selection for Neural Network-Based Interval Forecasting of Electricity Demand Data. ICANN 2013: 389-396 - [c45]Mashud Rana, Irena Koprinska:
Wavelet Neural Networks for Electricity Load Forecasting - Dealing with Border Distortion and Shift Invariance. ICANN 2013: 571-578 - [c44]Irena Koprinska, Mashud Rana, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Combining pattern sequence similarity with neural networks for forecasting electricity demand time series. IJCNN 2013: 1-8 - [c43]Mashud Rana, Irena Koprinska, Abbas Khosravi, Vassilios G. Agelidis:
Prediction intervals for electricity load forecasting using neural networks. IJCNN 2013: 1-8 - [c42]Mengxi Xu, Shlomo Berkovsky, Sebastien Ardon, Sipat Triukose, Anirban Mahanti, Irena Koprinska:
Catch-up TV recommendations: show old favourites and find new ones. RecSys 2013: 285-294 - 2012
- [c41]Timothy O'Keefe, Silvia Pareti, James R. Curran, Irena Koprinska, Matthew Honnibal:
A Sequence Labelling Approach to Quote Attribution. EMNLP-CoNLL 2012: 790-799 - [c40]Irena Koprinska, Mashud Rana, Vassilios G. Agelidis:
Electricity Load Forecasting: A Weekday-Based Approach. ICANN (2) 2012: 33-41 - [c39]Mashud Rana, Irena Koprinska, Vassilios G. Agelidis:
Feature Selection for Electricity Load Prediction. ICONIP (2) 2012: 526-534 - [c38]Alexandra Kotillova, Irena Koprinska, Mashud Rana:
Statistical and Machine Learning Methods for Electricity Demand Prediction. ICONIP (2) 2012: 535-542 - [c37]Mashud Rana, Irena Koprinska:
Electricity load forecasting using non-decimated wavelet prediction methods with two-stage feature selection. IJCNN 2012: 1-8 - [c36]Luiz Augusto Sangoi Pizzato, Joshua Akehurst, Cameron Silvestrini, Kalina Yacef, Irena Koprinska, Judy Kay:
The Effect of Suspicious Profiles on People Recommenders. UMAP 2012: 225-236 - [c35]Mengxi Xu, Shlomo Berkovsky, Irena Koprinska, Sebastien Ardon, Kalina Yacef:
Time dependency in TV viewer clustering. UMAP Workshops 2012 - 2011
- [c34]Irena Koprinska:
Mining Assessment and Teaching Evaluation Data of Regular, Advanced Stream Students. EDM 2011: 359-360 - [c33]Joshua Akehurst, Irena Koprinska, Kalina Yacef, Luiz Augusto Sangoi Pizzato, Judy Kay, Tomasz Rej:
CCR - A Content-Collaborative Reciprocal Recommender for Online Dating. IJCAI 2011: 2199-2204 - [c32]Irena Koprinska, Mashud Rana, Vassilios G. Agelidis:
Yearly and seasonal models for electricity load forecasting. IJCNN 2011: 1474-1481 - [c31]Joshua Akehurst, Irena Koprinska, Kalina Yacef, Luiz Augusto Sangoi Pizzato, Judy Kay, Tomasz Rej:
Explicit and Implicit User Preferences in Online Dating. PAKDD Workshops 2011: 15-27 - [c30]Luiz Augusto Sangoi Pizzato, Tomek Rej, Kalina Yacef, Irena Koprinska, Judy Kay:
Finding Someone You Will Like and Who Won't Reject You. UMAP 2011: 269-280 - 2010
- [c29]Irena Koprinska, Rohen Sood, Vassilios G. Agelidis:
Variable Selection for Five-Minute Ahead Electricity Load Forecasting. ICPR 2010: 2901-2904 - [c28]Rohen Sood, Irena Koprinska, Vassilios G. Agelidis:
Electricity load forecasting based on autocorrelation analysis. IJCNN 2010: 1-8 - [c27]Luiz Augusto Sangoi Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, Judy Kay:
RECON: a reciprocal recommender for online dating. RecSys 2010: 207-214 - [c26]Luiz Augusto Sangoi Pizzato, Tomek Rej, Thomas Chung, Irena Koprinska, Kalina Yacef, Judy Kay:
Reciprocal recommender system for online dating. RecSys 2010: 353-354 - [c25]Luiz Pizzato, Tomek Rej, Thomas Chung, Kalina Yacef, Irena Koprinska, Judy Kay:
Reciprocal Recommenders. ITWP@UMAP 2010
2000 – 2009
- 2009
- [j7]Dilhan Perera, Judy Kay, Irena Koprinska, Kalina Yacef, Osmar R. Zaïane:
Clustering and Sequential Pattern Mining of Online Collaborative Learning Data. IEEE Trans. Knowl. Data Eng. 21(6): 759-772 (2009) - [c24]Anthony Setiawan, Irena Koprinska, Vassilios G. Agelidis:
Very short-term electricity load demand forecasting using support vector regression. IJCNN 2009: 2888-2894 - [c23]Irena Koprinska:
Feature Selection for Brain-Computer Interfaces. PAKDD Workshops 2009: 106-117 - 2008
- [j6]Jason Chan, Irena Koprinska, Josiah Poon:
Semi-Supervised Classification Using Bridging. Int. J. Artif. Intell. Tools 17(3): 415-431 (2008) - [c22]Omar AlZoubi, Irena Koprinska, Rafael A. Calvo:
Classification of Brain-Computer Interface Data. AusDM 2008: 123-131 - 2007
- [j5]Irena Koprinska, Josiah Poon, James Clark, Jason Chan:
Learning to classify e-mail. Inf. Sci. 177(10): 2167-2187 (2007) - [c21]Jason Chan, Josiah Poon, Irena Koprinska:
Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging. FLAIRS 2007: 580-585 - 2006
- [j4]Dean Cummins, Kalina Yacef, Irena Koprinska:
A Sequence Based Recommender System for Learning Resources. Aust. J. Intell. Inf. Process. Syst. 9(2): 49-57 (2006) - [c20]Irena Koprinska, Da Deng, Felix Feger:
Image classification using labelled and unlabelled data. EUSIPCO 2006: 1-5 - [c19]Felix Feger, Irena Koprinska:
Co-training using RBF Nets and Different Feature Splits. IJCNN 2006: 1878-1885 - 2005
- [c18]Daren Ler, Irena Koprinska, Sanjay Chawla:
A Hill-Climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Criteria. FLAIRS 2005: 418-423 - [c17]Masoumeh D. Saberi, Sergio Carrato, Irena Koprinska, James Clark:
Estimation of the Hierarchical Structure of a Video Sequence Using MPEG-7 Descriptors and GCS. KES (2) 2005: 8-15 - [c16]Qing Tang, Irena Koprinska, Jesse S. Jin:
Content-adaptive transmission of reconstructed soccer goal events over low bandwidth networks. ACM Multimedia 2005: 271-274 - 2004
- [c15]Jason Chan, Irena Koprinska, Josiah Poon:
Co-Training on Textual Documents with a Single Natural Feature Set. ADCS 2004: 47-54 - [c14]Elisabeth Crawford, Irena Koprinska, Jon D. Patrick:
Phrases and Feature Selection in E-Mail Classification. ADCS 2004: 59-62 - [c13]Daren Ler, Irena Koprinska, Sanjay Chawla:
A Landmarker Selection Algorithm Based on Correlation and Efficiency Criteria. Australian Conference on Artificial Intelligence 2004: 296-306 - [c12]Daren Ler, Irena Koprinska, Sanjay Chawla:
Comparisons between Heuristics Based on Correlativity and Efficiency for Landmarker Generation. HIS 2004: 32-37 - [c11]Daren Ler, Irena Koprinska, Sanjay Chawla:
A new landmarker generation algorithm based on correlativity. ICMLA 2004: 178-185 - [c10]Irena Koprinska, James Clark:
Video summarization and browsing using growing cell structures. IJCNN 2004: 2601-2606 - [c9]Jason Chan, Irena Koprinska, Josiah Poon:
Co-training with a Single Natural Feature Set Applied to Email Classification. Web Intelligence 2004: 586-589 - 2003
- [c8]Harry Mak, Irena Koprinska, Josiah Poon:
INTIMATE: A Web-Based Movie Recommender Using Text Categorization. Web Intelligence 2003: 602-605 - [c7]James Clark, Irena Koprinska, Josiah Poon:
A Neural Network Based Approach to Automated E-Mail Classification. Web Intelligence 2003: 702-705 - 2002
- [j3]Irena Koprinska, Sergio Carrato:
Hybrid Rule-Based/Neural Approach for Segmentation of MPEG Compressed Video. Multim. Tools Appl. 18(3): 187-212 (2002) - [c6]Elisabeth Crawford, Irena Koprinska, Jon D. Patrick:
A Multi-Learner Approach to E-mail Classification. ADCS 2002 - [c5]Anna Ceguerra, Irena Koprinska:
Automatic Fingerprint Verification Using Neural Networks. ICANN 2002: 1281-1286 - [c4]Anna Ceguerra, Irena Koprinska:
Integrating Local and Global Features in Automatic Fingerprint Verification. ICPR (3) 2002: 347-350 - 2001
- [j2]Irena Koprinska, Sergio Carrato:
Temporal video segmentation: A survey. Signal Process. Image Commun. 16(5): 477-500 (2001) - 2000
- [c3]Irena Koprinska, Nikola K. Kasabov:
Evolving Fuzzy Neural Network for Camera Operations Recognition. ICPR 2000: 2523-2526
1990 – 1999
- 1998
- [c2]Irena Koprinska, Sergio Carrato:
Detecting and classifying video shot boundaries in MPEG compressed sequences. EUSIPCO 1998: 1-4 - [c1]Irena Koprinska, Sergio Carrato:
Video segmentation of MPEG compressed data. ICECS 1998: 243-246 - 1996
- [j1]Irena Koprinska, Gert Pfurtscheller, Doris Flotzinger:
Sleep classification in infants by decision tree-based neural networks. Artif. Intell. Medicine 8(4): 387-401 (1996)
Coauthor Index
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