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Budhaditya Saha
Budhaditya Saha
AI Scientist, Oracle
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Title
Cited by
Cited by
Year
Memorizing normality to detect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection
D Gong, L Liu, V Le, B Saha, MR Mansour, S Venkatesh, A Hengel
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
12542019
Learning regularity in skeleton trajectories for anomaly detection in videos
R Morais, V Le, T Tran, B Saha, M Mansour, S Venkatesh
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019
2812019
Comparative antimutagenic and anticlastogenic effects of green tea and black tea: a review
S Gupta, B Saha, AK Giri
Mutation Research/Reviews in Mutation Research 512 (1), 37-65, 2002
2482002
A framework for classifying online mental health-related communities with an interest in depression
B Saha, T Nguyen, D Phung, S Venkatesh
IEEE journal of biomedical and health informatics 20 (4), 1008-1015, 2016
822016
Anomaly Detection in Large-Scale Data Stream Networks
DS Pham, S Venkatesh, M Lazarescu, S Budhaditya
Data Mining and Knowledge Discovery, 2012
762012
Improved subspace clustering via exploitation of spatial constraints
DS Pham, S Budhaditya, D Phung, S Venkatesh
2012 IEEE Conference on computer vision and pattern recognition, 550-557, 2012
492012
Systems and methods for detecting anomalies from data
S Venkatesh, B Saha, MM Lazarescu, DS Pham
US Patent 8,744,124, 2014
452014
Multiple task transfer learning with small sample sizes
B Saha, S Gupta, D Phung, S Venkatesh
Knowledge and information systems 46, 315-342, 2016
392016
Effective anomaly detection in sensor networks data streams
S Budhaditya, DS Pham, M Lazarescu, S Venkatesh
2009 Ninth IEEE International Conference on Data Mining, 722-727, 2009
392009
Hengel Avd (2019) Memorizing normality to detect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection
D Gong, L Liu, V Le, B Saha, MR Mansour, S Venkatesh
Proceedings of the IEEE/CVF international conference on computer vision …, 0
35
Sparse Subspace Clustering via Group Sparse Coding
B Saha, D Phung, DS Pham, S Venkatesh
SIAM International Conference on Data Mining (SDM), 2013
272013
Infrequent item mining in multiple data streams
B Saha, M Lazarescu, S Venkatesh
Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007 …, 2007
202007
Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions
B Saha, S Gupta, D Phung, S Venkatesh
Knowledge and Information Systems 53, 179-206, 2017
152017
Understanding patient complaint characteristics using contextual clinical BERT embeddings
B Saha, S Lisboa, S Ghosh
2020 42nd Annual International Conference of the IEEE Engineering in …, 2020
102020
Detection of cross-channel anomalies from multiple data channels
DS Pham, B Saha, DQ Phung, S Venkatesh
2011 IEEE 11th International Conference on Data Mining, 527-536, 2011
102011
A framework for mixed-type multioutcome prediction with applications in healthcare
B Saha, S Gupta, D Phung, S Venkatesh
IEEE journal of biomedical and health informatics 21 (4), 1182-1191, 2017
82017
A new transfer learning framework with application to model-agnostic multi-task learning
S Gupta, S Rana, B Saha, D Phung, S Venkatesh
Knowledge and Information Systems 49, 933-973, 2016
82016
Multi-task transfer learning for in-hospital-death prediction of ICU patients
C Karmakar, B Saha, M Palaniswami, S Venkatesh
2016 38th Annual International Conference of the IEEE Engineering in …, 2016
82016
Clustering Patient Medical Records via Sparse Subspace Representation
B Saha, D Phung, DS Pham, S Venkatesh
The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2013
82013
Scalable network-wide anomaly detection using compressed data
D Pham, B Saha, M Lazarescu, S Venkatesh
Deakin University, 2009
72009
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