Articles with public access mandates - Mark J. CarmanLearn more
Not available anywhere: 2
Investigating deep learning based breast cancer subtyping using pan-cancer and multi-omic data
F Cristovao, S Cascianelli, A Canakoglu, M Carman, L Nanni, P Pinoli, ...
IEEE/ACM Transactions on Computational Biology and Bioinformatics 19 (1 …, 2020
Mandates: European Commission
Evaluating Deep Semi-supervised Learning for Whole-Transcriptome Breast Cancer Subtyping
S Cascianelli, F Cristovao, A Canakoglu, M Carman, L Nanni, P Pinoli, ...
Computational Intelligence Methods for Bioinformatics and Biostatistics …, 2020
Mandates: European Commission
Available somewhere: 14
Alleviating naive Bayes attribute independence assumption by attribute weighting
NA Zaidi, J Cerquides, MJ Carman, GI Webb
Journal of Machine Learning Research 14 (Jul), 1947-1988, 2013
Mandates: Australian Research Council
SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations
MA Rizoiu, S Mishra, Q Kong, M Carman, L Xie
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 419-428, 2018
Mandates: US Department of Defense
Overcoming key weaknesses of distance-based neighbourhood methods using a data dependent dissimilarity measure
KM Ting, Y Zhu, M Carman, Y Zhu, ZH Zhou
Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016
Mandates: National Natural Science Foundation of China
Efficient parameter learning of Bayesian network classifiers
NA Zaidi, GI Webb, MJ Carman, F Petitjean, W Buntine, M Hynes, ...
Machine Learning 106 (9-10), 1289-1329, 2017
Mandates: US Department of Defense, Australian Research Council
Naive-bayes inspired effective pre-conditioner for speeding-up logistic regression
NA Zaidi, MJ Carman, J Cerquides, GI Webb
2014 IEEE international conference on data mining, 1097-1102, 2014
Mandates: Australian Research Council
ALRn: accelerated higher-order logistic regression
NA Zaidi, GI Webb, MJ Carman, F Petitjean, J Cerquides
Machine Learning 104 (2-3), 151-194, 2016
Mandates: Australian Research Council
Lowest probability mass neighbour algorithms: relaxing the metric constraint in distance-based neighbourhood algorithms
KM Ting, Y Zhu, M Carman, Y Zhu, T Washio, ZH Zhou
Machine Learning 108, 331-376, 2019
Mandates: US Department of Defense, National Natural Science Foundation of China
Image-based social sensing: combining AI and the crowd to mine policy-adherence indicators from Twitter
V Negri, D Scuratti, S Agresti, D Rooein, G Scalia, AR Shankar, ...
2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021
Mandates: European Commission
A citizen science approach for analyzing social media with crowdsourcing
C Bono, MO Mülâyim, C Cappiello, MJ Carman, J Cerquides, ...
IEEE Access 11, 15329-15347, 2023
Mandates: European Commission
The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles
J Schreiber, C Boix, J wook Lee, H Li, Y Guan, CC Chang, JC Chang, ...
Genome biology 24 (1), 79, 2023
Mandates: US National Science Foundation, US National Institutes of Health, European …
Automated integration of genomic metadata with sequence-to-sequence models
G Cannizzaro, M Leone, A Bernasconi, A Canakoglu, MJ Carman
Machine Learning and Knowledge Discovery in Databases. Applied Data Science …, 2021
Mandates: European Commission
On the effectiveness of query weighting for adapting rank learners to new unlabelled collections
P Li, M Sanderson, M Carman, F Scholer
Proceedings of the 25th ACM International on Conference on Information and …, 2016
Mandates: Australian Research Council
Comparing classic, deep and semi-supervised learning for whole-transcriptome breast cancer subtyping
F Cristovao, A Canakoglu, M Carman, S Cascianelli, L Nanni, P Pinoli, ...
Proceedings of the 16th International Conference on Computational …, 2019
Mandates: European Commission
Dynamic Dimensionality Selection for Bayesian Classifier Ensembles
G Webb, M Carman, MONASH UNIV VICTORIA (AUSTRALIA)
Mandates: Australian Research Council
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