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Brian Mac Namee
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2020 – today
- 2024
- [j29]Qin Ruan
, Brian Mac Namee
, Ruihai Dong
:
The Effects of Media Bias on News Recommendations. IEEE Access 12: 83391-83404 (2024) - [c92]Brian Mac Namee
:
Explainable Interactive Machine Learning Using Prototypical Part Networks for Medical Image Analysis. HHAI 2024: 402-408 - [c91]Joyce Mahon
, Brian Mac Namee
, Brett A. Becker
:
Guidelines for the Evolving Role of Generative AI in Introductory Programming Based on Emerging Practice. ITiCSE (1) 2024 - [c90]Qin Ruan
, Jin Xu
, Susan Leavy
, Brian Mac Namee
, Ruihai Dong
:
Rewriting Bias: Mitigating Media Bias in News Recommender Systems through Automated Rewriting. UMAP 2024: 67-77 - [i37]Jinghui Lu, Ziwei Yang, Yanjie Wang, Xuejing Liu, Brian Mac Namee, Can Huang:
PaDeLLM-NER: Parallel Decoding in Large Language Models for Named Entity Recognition. CoRR abs/2402.04838 (2024) - 2023
- [j28]Luis Miralles-Pechuán
, Muhammad Atif Qureshi, Brian Mac Namee:
Real-time bidding campaigns optimization using user profile settings. Electron. Commer. Res. 23(2): 1297-1322 (2023) - [j27]Arjun Pakrashi, Duncan Wallace, Brian Mac Namee, Derek Greene, Christophe Guéret:
CowMesh: a data-mesh architecture to unify dairy industry data for prediction and monitoring. Frontiers Artif. Intell. 6 (2023) - [j26]Arjun Pakrashi
, Brian Mac Namee:
ML-KFHE: Multi-label Ensemble Classification Algorithm Exploiting Sensor Fusion Properties of the Kalman Filter. SN Comput. Sci. 4(6): 821 (2023) - [c89]Jinghui Lu, Rui Zhao, Brian Mac Namee, Fei Tan:
PUnifiedNER: A Prompting-Based Unified NER System for Diverse Datasets. AAAI 2023: 13327-13335 - [c88]Changhong Jin
, John Upton
, Brian Mac Namee
:
Do Cows Have Fingerprints? Using Time Series Techniques and Milk Flow Profiles to Characterise Cow Milking Performance and Detect Health Issues. AALTD@ECML/PKDD 2023: 230-242 - [c87]Jinghui Lu, Dongsheng Zhu, Weidong Han, Rui Zhao, Brian Mac Namee, Fei Tan:
What Makes Pre-trained Language Models Better Zero-shot Learners? ACL (1) 2023: 2288-2303 - [c86]Qin Ruan, Brian Mac Namee, Ruihai Dong:
Reducing Media Bias in News Headlines. AICS 2023: 1-4 - [c85]Misgina Tsighe Hagos
, Kathleen M. Curran
, Brian Mac Namee
:
Unlearning Spurious Correlations in Chest X-Ray Classification. DS 2023: 387-397 - [c84]Min Jing, Kathryn Owen, Brian Mac Namee, Iab B. A. Menown, James McLaughlin:
Investigating Temporal Features of Carotid Intima-Media Thickness from Ultrasound Imaging with Recurrent Neural Networks. EMBC 2023: 1-4 - [c83]Payel Sadhukhan
, Arjun Pakrashi, Sarbani Palit, Brian Mac Namee:
Integrating Unsupervised Clustering and Label-Specific Oversampling to Tackle Imbalanced Multi-Label Data. ICAART (2) 2023: 489-498 - [c82]Misgina Tsighe Hagos, Niamh Belton, Kathleen M. Curran, Brian Mac Namee:
Distance-Aware eXplanation Based Learning. ICTAI 2023: 279-286 - [c81]Alec Parise
, Brian Mac Namee
:
Exploring Optimal Configurations in Active Learning for Medical Imaging. SGAI Conf. 2023: 75-88 - [c80]Qin Ruan
, Brian Mac Namee
, Ruihai Dong
:
Unveiling the Relationship Between News Recommendation Algorithms and Media Bias: A Simulation-Based Analysis of the Evolution of Bias Prevalence. SGAI Conf. 2023: 210-215 - [c79]Misgina Tsighe Hagos
, Niamh Belton
, Ronan P. Killeen
, Kathleen M. Curran
, Brian Mac Namee
:
Interpretable Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI Images. SGAI Conf. 2023: 391-403 - [c78]Joyce Mahon
, Brian Mac Namee
, Brett A. Becker
:
No More Pencils No More Books: Capabilities of Generative AI on Irish and UK Computer Science School Leaving Examinations. UKICER 2023: 2:1-2:7 - [c77]Qin Ruan
, Brian Mac Namee
, Ruihai Dong
:
The Influence of Media Bias on News Recommender Systems. UMAP 2023: 301-305 - [i36]Misgina Tsighe Hagos, Niamh Belton, Ronan P. Killeen, Kathleen M. Curran, Brian Mac Namee:
Weighted Siamese Network to Predict the Time to Onset of Alzheimer's Disease from MRI Images. CoRR abs/2304.07097 (2023) - [i35]Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee:
Learning from Exemplary Explanations. CoRR abs/2307.06026 (2023) - [i34]Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee:
Unlearning Spurious Correlations in Chest X-ray Classification. CoRR abs/2308.01119 (2023) - [i33]Misgina Tsighe Hagos, Niamh Belton, Kathleen M. Curran, Brian Mac Namee:
Distance-Aware eXplanation Based Learning. CoRR abs/2309.05548 (2023) - [i32]Svetoslav Nizhnichenkov, Rahul Nair, Elizabeth Daly, Brian Mac Namee:
Explaining Knock-on Effects of Bias Mitigation. CoRR abs/2312.00765 (2023) - 2022
- [j25]Mehran Hossein Zadeh Bazargani
, Arjun Pakrashi
, Brian Mac Namee
:
The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection. IEEE Access 10: 70645-70661 (2022) - [c76]Jinghui Lu
, Linyi Yang, Brian MacNamee, Yue Zhang:
A Rationale-Centric Framework for Human-in-the-loop Machine Learning. ACL (1) 2022: 6986-6996 - [c75]Joyce Mahon
, Brett A. Becker
, Brian Mac Namee
:
AI and ML in School Level Computing Education: Who, What and Where? AICS 2022: 201-213 - [c74]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness
:
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. CVPR Workshops 2022: 1635-1645 - [c73]Misgina Tsighe Hagos
, Ronan P. Killeen, Kathleen M. Curran, Brian Mac Namee:
Interpretable Identification of Mild Cognitive Impairment Progression Using Stereotactic Surface Projections. PAIS@ECAI 2022: 153-156 - [c72]Misgina Tsighe Hagos
, Kathleen M. Curran
, Brian Mac Namee
:
Impact of Feedback Type on Explanatory Interactive Learning. ISMIS 2022: 127-137 - [c71]Ellen Rushe, Brian Mac Namee:
Deep Contextual Novelty Detection with Context Prediction. LIDTA 2022: 127-138 - [c70]Joyce Mahon, Keith Quille
, Brian Mac Namee, Brett A. Becker
:
A Novel Machine Learning and Artificial Intelligence Course for Secondary School Students. SIGCSE (2) 2022: 1155 - [c69]Payel Sadhukhan
, Arjun Pakrashi, Brian Mac Namee:
Random Walk-steered Majority Undersampling. SMC 2022: 530-537 - [e4]Arjun Pakrashi, Ellen Rushe, Mehran Hossein Zadeh Bazargani, Brian Mac Namee:
The 29th Irish Conference on Artificial Intelligence and Cognitive Science 2021, Dublin, Republic of Ireland, December 9-10, 2021. CEUR Workshop Proceedings 3105, CEUR-WS.org 2022 [contents] - [i31]Jinghui Lu, Linyi Yang, Brian Mac Namee, Yue Zhang:
A Rationale-Centric Framework for Human-in-the-loop Machine Learning. CoRR abs/2203.12918 (2022) - [i30]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Jaime B. Fernandez, Brian Mac Namee, Deirdre Hennessy, Noel E. O'Connor, Kevin McGuinness:
Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. CoRR abs/2204.08271 (2022) - [i29]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling H. O'Connor, Noel E. O'Connor, Kevin McGuinness:
Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation. CoRR abs/2204.09343 (2022) - [i28]Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee:
Impact of Feedback Type on Explanatory Interactive Learning. CoRR abs/2209.12476 (2022) - [i27]Jinghui Lu, Rui Zhao, Brian Mac Namee, Dongsheng Zhu, Weidong Han, Fei Tan:
What Makes Pre-trained Language Models Better Zero/Few-shot Learners? CoRR abs/2209.15206 (2022) - [i26]Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee:
Identifying Spurious Correlations and Correcting them with an Explanation-based Learning. CoRR abs/2211.08285 (2022) - [i25]Jinghui Lu, Rui Zhao, Brian Mac Namee, Fei Tan:
PUnifiedNER: a Prompting-based Unified NER System for Diverse Datasets. CoRR abs/2211.14838 (2022) - 2021
- [j24]Liang Zhao
, Kun Chen, Jie Song, Xiaoliang Zhu, Jianwen Sun, Brian Caulfield
, Brian Mac Namee:
Academic Performance Prediction Based on Multisource, Multifeature Behavioral Data. IEEE Access 9: 5453-5465 (2021) - [j23]Arjun Pakrashi
, Brian Mac Namee:
A multi-label cascaded neural network classification algorithm for automatic training and evolution of deep cascaded architecture. Expert Syst. J. Knowl. Eng. 38(7) (2021) - [j22]Min Jing
, Kok Yew Ng, Brian Mac Namee, Pardis Biglarbeigi
, Rob Brisk, Raymond R. Bond, Dewar D. Finlay, James McLaughlin:
COVID-19 modelling by time-varying transmission rate associated with mobility trend of driving via Apple Maps. J. Biomed. Informatics 122: 103905 (2021) - [c68]James Murphy, John E. Ward, Brian Mac Namee:
Machine Learning in Space: A Review of Machine Learning Algorithms and Hardware for Space Applications. AICS 2021: 72-83 - [c67]Qin Ruan, Brian Mac Namee, Ruihai Dong:
Bias Bubbles: Using Semi-Supervised Learning to Measure How Many Biased News Articles Are Around Us. AICS 2021: 153-164 - [c66]Badri Narayanan, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Noel E. O'Connor, Brian Mac Namee:
Adaptation of Compositional Data Analysis in Deep Learning to Predict Pasture Biomass Proportions. AICS 2021: 176-187 - [c65]Jinghui Lu
, Maeve Henchion
, Ivan Bacher, Brian Mac Namee
:
A Sentence-Level Hierarchical BERT Model for Document Classification with Limited Labelled Data. DS 2021: 231-241 - [c64]Paul Albert, Mohamed Saadeldin
, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness
:
Semi-supervised dry herbage mass estimation using automatic data and synthetic images. ICCVW 2021: 1284-1293 - [c63]John Mitros
, Brian Mac Namee:
On the Importance of Regularisation and Auxiliary Information in OOD Detection. ICONIP (6) 2021: 361-368 - [c62]Mohamed Saadeldin
, Brian MacNamee:
An Orthogonal Classification Layer with Kasami Sequences for Discriminative Feature Learning in Neural Networks. ICTAI 2021: 370-375 - [c61]Arjun Pakrashi, Payel Sadhukhan, Brian Mac Namee:
ML-NCA: Multi-label Neighbourhood Component Analysis. LIDTA@ECML/PKDD 2021: 35-48 - [i24]Cathal Ryan, Christophe Guéret, Donagh Berry, Medb Corcoran, Mark T. Keane, Brian Mac Namee:
Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows. CoRR abs/2101.02188 (2021) - [i23]Badri Narayanan
, Mohamed Saadeldin, Paul Albert, Kevin McGuinness, Brian Mac Namee:
Extracting Pasture Phenotype and Biomass Percentages using Weakly Supervised Multi-target Deep Learning on a Small Dataset. CoRR abs/2101.03198 (2021) - [i22]Mehran Hossein Zadeh Bazargani, Arjun Pakrashi, Brian Mac Namee:
The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection. CoRR abs/2101.12632 (2021) - [i21]Jinghui Lu, Maeve Henchion, Ivan Bacher, Brian Mac Namee:
A Sentence-level Hierarchical BERT Model for Document Classification with Limited Labelled Data. CoRR abs/2106.06738 (2021) - [i20]John Mitros, Brian Mac Namee:
On the Importance of Regularisation & Auxiliary Information in OOD Detection. CoRR abs/2107.07564 (2021) - [i19]Qin Ruan
, Brian Mac Namee, Ruihai Dong:
Pseudo-labelling Enhanced Media Bias Detection. CoRR abs/2107.07705 (2021) - [i18]Payel Sadhukhan, Arjun Pakrashi, Sarbani Palit, Brian Mac Namee:
Integrating Unsupervised Clustering and Label-specific Oversampling to Tackle Imbalanced Multi-label Data. CoRR abs/2109.12421 (2021) - [i17]Payel Sadhukhan, Arjun Pakrashi, Brian Mac Namee:
Random Walk-steered Majority Undersampling. CoRR abs/2109.12423 (2021) - [i16]Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O'Connor, Noel E. O'Connor, Kevin McGuinness:
Semi-supervised dry herbage mass estimation using automatic data and synthetic images. CoRR abs/2110.13719 (2021) - 2020
- [j21]Arjun Pakrashi
, Brian Mac Namee:
KalmanTune: A Kalman Filter Based Tuning Method to Make Boosted Ensembles Robust to Class-Label Noise. IEEE Access 8: 145887-145897 (2020) - [j20]Elham Alghamdi
, Ellen Rushe, Brian Mac Namee, Derek Greene
:
Overlapping community finding with noisy pairwise constraints. Appl. Netw. Sci. 5(1): 98 (2020) - [j19]Elizabeth Hunter
, Brian Mac Namee, John D. Kelleher:
A Hybrid Agent-Based and Equation Based Model for the Spread of Infectious Diseases. J. Artif. Soc. Soc. Simul. 23(4) (2020) - [c60]Min Jing
, Donal McLaughlin
, David Steele, Sara McNamee
, Brian MacNamee, Patrick Cullen, Dewar D. Finlay, James McLaughlin:
Detection and Categorisation of Multilevel High-sensitivity Cardiovascular Biomarkers from Lateral Flow Immunoassay Images via Recurrent Neural Networks. BIOIMAGING 2020: 177-183 - [c59]John Mitros, Arjun Pakrashi
, Brian Mac Namee:
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings. ECCV Workshops (1) 2020: 71-87 - [c58]Min Jing
, Brian Mac Namee, Donal McLaughlin
, David Steele, Sara McNamee
, Patrick Cullen, Dewar D. Finlay, James McLaughlin:
Enhance Categorisation Of Multilevel High-Sensitivity Cardiovascular Biomarkers From Lateral Flow Immunoassay Images Via Neural Networks And Dynamic Time Warping. ICIP 2020: 365-369 - [c57]Jinghui Lu, Maeve Henchion, Brian Mac Namee:
Diverging Divergences: Examining Variants of Jensen Shannon Divergence for Corpus Comparison Tasks. LREC 2020: 6740-6744 - [c56]Luis Miralles-Pechuán
, Matthieu Bellucci, Muhammad Atif Qureshi
, Brian Mac Namee
:
ZeChipC: Time Series Interpolation Method Based on Lebesgue Sampling. MICAI (1) 2020: 182-196 - [c55]Muhammad Atif Qureshi
, Luis Miralles-Pechuán
, Jason Payne, Ronan O'Malley, Brian Mac Namee
:
Valve Health Identification Using Sensors and Machine Learning Methods. IoT Streams/ITEM@PKDD/ECML 2020: 45-60 - [i15]Jinghui Lu, Brian MacNamee:
Investigating the Effectiveness of Representations Based on Pretrained Transformer-based Language Models in Active Learning for Labelling Text Datasets. CoRR abs/2004.13138 (2020) - [i14]Ellen Rushe, Brian Mac Namee:
Deep Context-Aware Novelty Detection. CoRR abs/2006.01168 (2020) - [i13]John Mitros
, Arjun Pakrashi, Brian Mac Namee:
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings. CoRR abs/2009.01798 (2020) - [i12]Cathal Ryan, Christophe Guéret, Donagh Berry, Brian Mac Namee:
Can We Detect Mastitis earlier than Farmers? CoRR abs/2011.03344 (2020)
2010 – 2019
- 2019
- [j18]Arjun Pakrashi
, Brian Mac Namee:
Kalman Filter-based Heuristic Ensemble (KFHE): A new perspective on multi-class ensemble classification using Kalman filters. Inf. Sci. 485: 456-485 (2019) - [c54]Jinghui Lu, Maeve Henchion, Brian Mac Namee:
A Topic-Based Approach to Multiple Corpus Comparison. AICS 2019: 64-75 - [c53]John Mitros, Brian Mac Namee:
On the Validity of Bayesian Neural Networks for Uncertainty Estimation. AICS 2019: 140-151 - [c52]Ellen Rushe, Brian Mac Namee:
Anomaly Detection in Raw Audio Using Deep Autoregressive Networks. ICASSP 2019: 3597-3601 - [c51]Mehran Hossein Zadeh Bazargani
, Brian Mac Namee:
The Elliptical Basis Function Data Descriptor (EBFDD) Network: A One-Class Classification Approach to Anomaly Detection. ECML/PKDD (1) 2019: 107-123 - [c50]Arjun Pakrashi
, Brian Mac Namee:
CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification (Best Technical Paper). SGAI Conf. 2019: 3-17 - [c49]Niladri Sett, Brian Mac Namee, Francesc Calvo, Brian Caulfield, John Costello, Seamas Donnelly, Jonas F. Dorn
, Louis Jeay, Alison Keogh
, Killian McManus, Ronan H. Mullan, Emer O'Hare, Caroline G. M. Perraudin:
Are You in Pain? Predicting Pain and Stiffness from Wearable Sensor Activity Data. SGAI Conf. 2019: 183-197 - [e3]Ulf Brefeld, Edward Curry
, Elizabeth Daly, Brian MacNamee, Alice Marascu, Fabio Pinelli, Michele Berlingerio, Neil Hurley:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018, Proceedings, Part III. Lecture Notes in Computer Science 11053, Springer 2019, ISBN 978-3-030-10996-7 [contents] - [i11]John Mitros, Brian Mac Namee:
A Categorisation of Post-hoc Explanations for Predictive Models. CoRR abs/1904.02495 (2019) - [i10]Arjun Pakrashi, Brian Mac Namee:
CascadeML: An Automatic Neural Network Architecture Evolution and Training Algorithm for Multi-label Classification. CoRR abs/1904.10551 (2019) - [i9]Arjun Pakrashi, Brian Mac Namee:
KFHE-HOMER: Kalman Filter-based Heuristic Ensemble of HOMER for Multi-Label Classification. CoRR abs/1904.10552 (2019) - [i8]Matthieu Bellucci, Luis Miralles, Muhammad Atif Qureshi, Brian Mac Namee:
ZeLiC and ZeChipC: Time Series Interpolation Methods for Lebesgue or Event-based Sampling. CoRR abs/1906.03110 (2019) - [i7]Jinghui Lu, Maeve Henchion, Brian Mac Namee:
Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text Datasets. CoRR abs/1910.03505 (2019) - [i6]Luis Miralles, Muhammad Atif Qureshi, Brian Mac Namee:
Real-time Bidding campaigns optimization using attribute selection. CoRR abs/1910.13292 (2019) - [i5]John Mitros
, Brian Mac Namee:
On the Validity of Bayesian Neural Networks for Uncertainty Estimation. CoRR abs/1912.01530 (2019) - 2018
- [j17]Quan Le, Oisín Boydell
, Brian Mac Namee, Mark Scanlon
:
Deep learning at the shallow end: Malware classification for non-domain experts. Digit. Investig. 26 Supplement: S118-S126 (2018) - [j16]Mark Belford, Brian Mac Namee
, Derek Greene
:
Stability of topic modeling via matrix factorization. Expert Syst. Appl. 91: 159-169 (2018) - [j15]Elizabeth Hunter
, Brian Mac Namee, John D. Kelleher
:
Using a Socioeconomic Segregation Burn-in Model to Initialise an Agent-Based Model for Infectious Diseases. J. Artif. Soc. Soc. Simul. 21(4) (2018) - [c48]Elizabeth Hunter, Brian Mac Namee, John D. Kelleher:
A Comparison of Agent-Based Models and Equation Based Models for Infectious Disease Epidemiology. AICS 2018: 33-44 - [c47]Arjun Pakrashi, Elham Alghamdi, Brian Mac Namee, Derek Greene:
MeetupNet Dublin: Discovering Communities in Dublin's Meetup Network. AICS 2018: 114-125 - [c46]Niamh Donnelly, Conor Nugent, Brian Mac Namee:
Identifying Urban Canopy Coverage from Satellite Imagery Using Convolutional Neural Networks. AICS 2018: 315-326 - [c45]Shen Wang
, Aditya Grover
, Brian Mac Namee
, Philip Plantholt, Javier Lopez-Leones, Pablo Sanchez-Escalonilla:
ROGER: An On-Line Flight Efficiency Monitoring System Using ADS-B Data. MDM 2018: 233-238 - [c44]Jack O'Neill, Sarah Jane Delany, Brian Mac Namee:
Rank Scoring via Active Learning (RaScAL). HumL@ISWC 2018: 38-50 - [c43]Jack O'Neill, Sarah Jane Delany, Brian Mac Namee:
From Rankings to Ratings: Rank Scoring via Active Learning. ISWC (Best Workshop Papers) 2018: 69-81 - [c42]Ivan Bacher, Brian Mac Namee
, John D. Kelleher
:
Scoped: Evaluating A Composite Visualisation of the Scope Chain Hierarchy Within Source Code. VISSOFT 2018: 117-121 - [c41]Ivan Bacher, Brian Mac Namee
, John D. Kelleher
:
The Code Mini-Map Visualisation: Encoding Conceptual Structures Within Source Code. VISSOFT 2018: 127-131 - [i4]Quan Le, Oisín Boydell, Brian Mac Namee, Mark Scanlon:
Deep learning at the shallow end: Malware classification for non-domain experts. CoRR abs/1807.08265 (2018) - [i3]Arjun Pakrashi, Brian Mac Namee:
Kalman Filter-based Heuristic Ensemble: A New Perspective on Ensemble Classification Using Kalman Filters. CoRR abs/1807.11429 (2018) - [i2]Arjun Pakrashi, Elham Alghamdi, Brian Mac Namee, Derek Greene:
MeetupNet Dublin: Discovering Communities in Dublin's Meetup Network. CoRR abs/1810.03046 (2018) - 2017
- [j14]Niels Schütte, Brian Mac Namee
, John D. Kelleher
:
Robot perception errors and human resolution strategies in situated human-robot dialogue. Adv. Robotics 31(5): 243-257 (2017) - [j13]Elizabeth Hunter
, Brian Mac Namee, John D. Kelleher
:
A Taxonomy for Agent-Based Models in Human Infectious Disease Epidemiology. J. Artif. Soc. Soc. Simul. 20(3) (2017) - [c40]Brian Mac Namee, John D. Kelleher, Noel Fitzpatrick:
Assessing the Usefulness of Different Feature Sets for Predicting the Comprehension Difficulty of Text. AICS 2017: 12-25 - [c39]Mark Belford, Brian Mac Namee, Derek Greene:
Synthetic Dataset Generation for Online Topic Modeling. AICS 2017: 63-75 - [c38]Jinghui Lu, Maeve Henchion, Brian Mac Namee:
Extending Jensen Shannon Divergence to Compare Multiple Corpora. AICS 2017: 76-88 - [c37]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
The Code-Map Metaphor - A Review of Its Use Within Software Visualisations. VISIGRAPP (3: IVAPP) 2017: 17-28 - [c36]Arjun Pakrashi
, Brian Mac Namee:
Stacked-MLkNN: A stacking based improvement to Multi-Label k-Nearest Neighbours. LIDTA@PKDD/ECML 2017: 51-63 - [c35]Jack O'Neill, Sarah Jane Delany, Brian Mac Namee:
Rating by Ranking: An Improved Scale for Judgement-Based Labels. IntRS@RecSys 2017: 24-29 - [c34]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
Scoped: Visualising the Scope Chain Within Source Code. EuroVis (Short Papers) 2017: 115-119 - [i1]Mark Belford, Brian Mac Namee, Derek Greene:
Stability of Topic Modeling via Matrix Factorization. CoRR abs/1702.07186 (2017) - 2016
- [j12]Rong Hu
, Brian Mac Namee
, Sarah Jane Delany
:
Active learning for text classification with reusability. Expert Syst. Appl. 45: 438-449 (2016) - [j11]Arkaitz Zubiaga, Brian Mac Namee:
Graphical Perception of Value Distributions: An Evaluation of Non-Expert Viewers' Data Literacy. J. Community Informatics 12(3) (2016) - [c33]Mark Belford, Brian Mac Namee, Derek Greene:
Ensemble Topic Modeling via Matrix Factorization. AICS 2016: 21-32 - [c32]Elizabeth Hunter, Brian Mac Namee, John D. Kelleher:
An Open Data Driven Epidemiological Agent-Based Model for Irish Towns. AICS 2016: 92-103 - [c31]Jack O'Neill, Sarah Jane Delany, Brian Mac Namee:
Activist: A New Framework for Dataset Labelling. AICS 2016: 140-148 - [c30]Arjun Pakrashi, Derek Greene, Brian Mac Namee:
Benchmarking Multi-label Classification Algorithms. AICS 2016: 149-160 - [c29]Jack O'Neill, Sarah Jane Delany
, Brian Mac Namee
:
Model-Free and Model-Based Active Learning for Regression. UKCI 2016: 375-386 - [c28]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
On Using Tree Visualisation Techniques to Support Source Code Comprehension. VISSOFT 2016: 91-95 - [c27]Ivan Bacher, Brian Mac Namee, John D. Kelleher
:
Using Icicle Trees to Encode the Hierarchical Structure of Source Code. EuroVis (Short Papers) 2016: 97-101 - [e2]Derek Greene, Brian Mac Namee, Robert J. Ross:
Proceedings of the 24th Irish Conference on Artificial Intelligence and Cognitive Science, AICS 2016, Dublin, Ireland, September 20-21, 2016. CEUR Workshop Proceedings 1751, CEUR-WS.org 2016 [contents] - 2014
- [j10]Alexey Tarasov, Sarah Jane Delany
, Brian Mac Namee
:
Dynamic estimation of worker reliability in crowdsourcing for regression tasks: Making it work. Expert Syst. Appl. 41(14): 6190-6210 (2014) - [c26]Niels Schütte, John D. Kelleher
, Brian Mac Namee
:
The Effect of Sensor Errors in Situated Human-Computer Dialogue. VL@COLING 2014: 1-8 - [c25]Eoghan O'Shea, Sarah Jane Delany, Rob Lane, Brian Mac Namee
:
NudgeAlong: A Case Based Approach to Changing User Behaviour. ICCBR 2014: 345-359 - [c24]Niels Schütte, John D. Kelleher
, Brian Mac Namee
:
Clarification Dialogues for Perception-based Errors in Situated Human-Computer Dialogues. MMRWHRI@ICMI 2014: 25-26 - 2013
- [j9]Kenneth Kennedy, Brian Mac Namee
, Sarah Jane Delany
, M. O'Sullivan, N. Watson:
A window of opportunity: Assessing behavioural scoring. Expert Syst. Appl. 40(4): 1372-1380 (2013) - [j8]Patrick Lindstrom, Brian Mac Namee
, Sarah Jane Delany
:
Drift detection using uncertainty distribution divergence. Evol. Syst. 4(1): 13-25 (2013) - [j7]Kenneth Kennedy, Brian Mac Namee
, Sarah Jane Delany
:
Using semi-supervised classifiers for credit scoring. J. Oper. Res. Soc. 64(4): 513-529 (2013) - [c23]Yan Li, Brian Mac Namee
, John D. Kelleher
:
Expecting the Unexpected: Measure the Uncertainties for Mobile Robot Path Planning in Dynamic Environment. TAROS 2013: 363-374 - 2012
- [j6]Sarah Jane Delany
, Nicola Segata
, Brian Mac Namee
:
Profiling instances in noise reduction. Knowl. Based Syst. 31: 28-40 (2012) - [c22]Dmitry Strunkin, Brian Mac Namee
, John D. Kelleher
:
An Investigation Into Feature Selection for Oncological Survival Prediction. ITNG 2012: 764-768 - [c21]Mark Dunne, Brian Mac Namee
, John D. Kelleher
:
The Turning, Stretching and Boxing Technique: A Step in the Right Direction. IVA 2012: 363-369 - [c20]Alexey Tarasov, Sarah Jane Delany
, Brian Mac Namee
:
Dynamic Estimation of Rater Reliability in Subjective Tasks Using Multi-armed Bandits. SocialCom/PASSAT 2012: 979-980 - 2011
- [j5]John D. Kelleher
, Robert J. Ross
, Colm Sloan, Brian Mac Namee
:
The effect of occlusion on the semantics of projective spatial terms: a case study in grounding language in perception. Cogn. Process. 12(1): 95-108 (2011) - [j4]Niels Schütte, John D. Kelleher, Brian Mac Namee:
Automatic Annotation of Referring Expressions in Situated Dialogues. Int. J. Comput. Linguistics Appl. 2(1-2): 175-190 (2011) - [c19]Colm Sloan, John D. Kelleher
, Brian Mac Namee
:
Feasibility study of utility-directed behaviour for computer game agents. Advances in Computer Entertainment Technology 2011: 5 - [c18]Colm Sloan, John D. Kelleher
, Brian Mac Namee
:
Feeling the ambiance: using smart ambiance to increase contextual awareness in game agents. FDG 2011: 298-300 - [c17]Patrick Lindstrom, Brian Mac Namee
, Sarah Jane Delany
:
Drift Detection Using Uncertainty Distribution Divergence. ICDM Workshops 2011: 604-608 - 2010
- [j3]Brian Mac Namee
, David Beaney, Qingqing Dong:
Motion in Augmented Reality Games: An Engine for Creating Plausible Physical Interactions in Augmented Reality Games. Int. J. Comput. Games Technol. 2010: 979235:1-979235:8 (2010) - [c16]John D. Kelleher, Robert J. Ross, Brian Mac Namee, Colm Sloan:
Situating Spatial Templates for Human-Robot Interaction. AAAI Fall Symposium: Dialog with Robots 2010 - [c15]Niels Schuette, John D. Kelleher, Brian Mac Namee:
Visual Salience and Reference Resolution in Situated Dialogues: A Corpus-based Evaluation. AAAI Fall Symposium: Dialog with Robots 2010 - [c14]Rong Hu, Brian Mac Namee, Sarah Jane Delany:
Off to a Good Start: Using Clustering to Select the Initial Training Set in Active Learning. FLAIRS 2010 - [c13]Patrick Lindstrom, Sarah Jane Delany, Brian Mac Namee:
Handling Concept Drift in a Text Data Stream Constrained by High Labelling Cost. FLAIRS 2010 - [c12]Rong Hu
, Sarah Jane Delany
, Brian Mac Namee
:
EGAL: Exploration Guided Active Learning for TCBR. ICCBR 2010: 156-170 - [c11]Brian Mac Namee
, Sarah Jane Delany
:
CBTV: Visualising Case Bases for Similarity Measure Design and Selection. ICCBR 2010: 213-227 - [e1]John D. Kelleher, Brian Mac Namee, Ielka van der Sluis, Anja Belz, Albert Gatt, Alexander Koller:
INLG 2010 - Proceedings of the Sixth International Natural Language Generation Conference, July 7-9, 2010, Trim, Co. Meath, Ireland. The Association for Computer Linguistics 2010 [contents]
2000 – 2009
- 2009
- [c10]Nicholas Hanlon, Brian Mac Namee
, John D. Kelleher
:
Just Say It: An Evaluation of Speech Interfaces for Augmented Reality Design Applications. AICS 2009: 134-143 - [c9]Kenneth Kennedy, Brian Mac Namee
, Sarah Jane Delany
:
Learning without Default: A Study of One-Class Classification and the Low-Default Portfolio Problem. AICS 2009: 174-187 - [c8]David Beaney, Brian Mac Namee
:
Forked! A demonstration of physics realism in augmented reality. ISMAR 2009: 171-172 - [c7]Brian Mac Namee
, Mark Dunne:
Widening the Evaluation Net. IVA 2009: 525-526 - [c6]Pauline Rooney, K. C. O'Rourke, Greg Burke, Brian MacNamee
, Claudia Igbrude:
Cross-Disciplinary Approaches for Developing Serious Games in Higher Education. VS-GAMES 2009: 161-165 - [r1]Brian Mac Namee
:
Computer Graphics and Games, Agent Based Modeling in. Encyclopedia of Complexity and Systems Science 2009: 1335-1352 - 2008
- [c5]Qian Zhang, Rong Hu, Brian Mac Namee, Sarah Jane Delany:
Back to the Future: Knowledge Light Case Base Cookery. ECCBR Workshops 2008: 239-248 - [c4]John D. Kelleher, Brian Mac Namee:
Referring Expression Generation Challenge 2008 DIT System Descriptions (DIT-FBI, DIT-TVAS, DIT-CBSR, DIT-RBR, DIT-FBI-CBSR, DIT-TVAS-RBR). INLG 2008 - 2003
- [j2]Brian MacNamee, Padraig Cunningham:
Creating socially interactive no-player characters: The µ-SIV system. Int. J. Intell. Games Simul. 2(1): 28-35 (2003) - [c3]Brian MacNamee
, Simon Dobbyn, Padraig Cunningham
, Carol O'Sullivan:
Simulating Virtual Humans Across Diverse Situations. IVA 2003: 159-163 - [c2]Christopher E. Peters, Simon Dobbyn, Brian MacNamee, Carol O'Sullivan:
Smart Objects for Attentive Agents. WSCG 2003 - 2002
- [j1]Brian MacNamee
, Padraig Cunningham
, Stephen Byrne, O. I. Corrigan:
The problem of bias in training data in regression problems in medical decision support. Artif. Intell. Medicine 24(1): 51-70 (2002) - [c1]Brian MacNamee, Padraig Cunningham:
The u-SIG System; A Connectionist Driven Simulation of Socially Interactive Agents. GAME-ON 2002
Coauthor Index
![](https://dblp.dagstuhl.de/img/cog.dark.24x24.png)
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