James Bailey
James Bailey
Professor, School of Computing and Information Systems, University of Melbourne
Verified email at unimelb.edu.au - Homepage
Cited by
Cited by
Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance
NX Vinh, J Epps, J Bailey
The Journal of Machine Learning Research 11, 2837-2854, 2010
Characterizing adversarial subspaces using local intrinsic dimensionality
X Ma, B Li, Y Wang, SM Erfani, S Wijewickrema, G Schoenebeck, D Song, ...
arXiv preprint arXiv:1801.02613, 2018
Discovery of minimal unsatisfiable subsets of constraints using hitting set dualization
J Bailey, P Stuckey
Practical Aspects of Declarative Languages, 174-186, 2005
Dimensionality-driven learning with noisy labels
X Ma, Y Wang, ME Houle, S Zhou, S Erfani, S Xia, S Wijewickrema, ...
International Conference on Machine Learning, 3355-3364, 2018
Symmetric cross entropy for robust learning with noisy labels
Y Wang, X Ma, Z Chen, Y Luo, J Yi, J Bailey
Proceedings of the IEEE/CVF International Conference on Computer Vision, 322-330, 2019
Mining minimal distinguishing subsequence patterns with gap constraints
X Ji, J Bailey, G Dong
Knowledge and Information Systems 11 (3), 259-286, 2007
An event-condition-action language for XML
J Bailey, A Poulovassilis, PT Wood
Proceedings of the 11th international conference on World Wide Web, 486-495, 2002
An event-condition-action language for XML
J Bailey, G Papamarkos, A Poulovassilis, PT Wood
Web Dynamics, 223-248, 2004
Iterative learning with open-set noisy labels
Y Wang, W Liu, X Ma, J Bailey, H Zha, L Song, ST Xia
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Identifying at-risk students in massive open online courses
J He, J Bailey, B Rubinstein, R Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
Computer-aided Diagnosis of Melanoma Using Border and Wavelet-based Texture Analysis
R Garnavi, M Aldeen, J Bailey
IEEE, 2012
Coala: A novel approach for the extraction of an alternate clustering of high quality and high dissimilarity
E Bae, J Bailey
Sixth International Conference on Data Mining (ICDM'06), 53-62, 2006
Web and semantic web query languages: A survey
J Bailey, F Bry, T Furche, S Schaffert
Reasoning Web, 95-95, 2005
Improving adversarial robustness requires revisiting misclassified examples
Y Wang, D Zou, J Yi, J Bailey, X Ma, Q Gu
International Conference on Learning Representations, 2019
Contrast Data Mining: Concepts, Algorithms, and Applications
G Dong, J Bailey, J Li
Chapman & Hall, 2012
is-rSNP: a novel technique for in silico regulatory SNP detection
G Macintyre, J Bailey, I Haviv, A Kowalczyk
Bioinformatics 26 (18), i524-i530, 2010
On the Convergence and Robustness of Adversarial Training.
Y Wang, X Ma, J Bailey, J Yi, B Zhou, Q Gu
ICML 1, 2, 2019
Fast algorithms for mining emerging patterns
J Bailey, T Manoukian, K Ramamohanarao
Principles of Data Mining and Knowledge Discovery, 187-208, 2002
Adjusting for chance clustering comparison measures
S Romano, NX Vinh, J Bailey, K Verspoor
The Journal of Machine Learning Research 17 (1), 4635-4666, 2016
Document clustering of scientific texts using citation contexts
B Aljaber, N Stokes, J Bailey, J Pei
Information Retrieval 13 (2), 101-131, 2010
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