Budhaditya Saha

发表

A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression.

S. Venkatesh, Dinh Phung, Thin Nguyen, 2016, IEEE journal of biomedical and health informatics.

Multiple task transfer learning with small sample sizes

Svetha Venkatesh, Dinh Q. Phung, Sunil Gupta, 2015, Knowledge and Information Systems.

Effective Anomaly Detection in Sensor Networks Data Streams

Svetha Venkatesh, Duc-Son Pham, Mihai Lazarescu, 2009, 2009 Ninth IEEE International Conference on Data Mining.

Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection

Svetha Venkatesh, Anton van den Hengel, Lingqiao Liu, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

A new transfer learning framework with application to model-agnostic multi-task learning

Svetha Venkatesh, Dinh Q. Phung, Santu Rana, 2016, Knowledge and Information Systems.

Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

Svetha Venkatesh, Truyen Tran, Moussa Reda Mansour, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Understanding patient complaint characteristics using contextual clinical BERT embeddings

Shameek Ghosh, Budhaditya Saha, Sanal Lisboa, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

A Framework for Classifying Online Mental Health-Related Communities With an Interest in Depression

Svetha Venkatesh, Dinh Q. Phung, Thin Nguyen, 2016, IEEE Journal of Biomedical and Health Informatics.

Anomaly detection in large-scale data stream networks

Svetha Venkatesh, Duc-Son Pham, Mihai Lazarescu, 2012, Data Mining and Knowledge Discovery.

Scalable network-wide anomaly detection using compressed data

Duc-Son Pham, Mihai Lazarescu, Svetha Venkatesh, 2009 .

Multiple task transfer learning with small sample sizes

Dinh Q. Phung, S. Gupta, S. Venkatesh, 2016, Knowledge and Information Systems.

A Framework for Mixed-Type Multioutcome Prediction With Applications in Healthcare

Svetha Venkatesh, Dinh Q. Phung, Sunil Gupta, 2017, IEEE Journal of Biomedical and Health Informatics.

Effective sparse imputation of patient conditions in electronic medical records for emergency risk predictions

Svetha Venkatesh, Dinh Q. Phung, Sunil Gupta, 2017, Knowledge and Information Systems.

Predicting missing and noisy links via neighbourhood preserving graph embeddings in a clinical knowlegebase

Shameek Ghosh, Budhaditya Saha, Vedant Mandloi, 2020, 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA).

Transfer learning for rare cancer problems via Discriminative Sparse Gaussian Graphical model

Svetha Venkatesh, Dinh Q. Phung, Sunil Gupta, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Visual Object Clustering via Mixed-Norm Regularization

Svetha Venkatesh, Duc-Son Pham, Wanquan Liu, 2015, 2015 IEEE Winter Conference on Applications of Computer Vision.

Improved subspace clustering via exploitation of spatial constraints

Svetha Venkatesh, Duc-Son Pham, Dinh Q. Phung, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Sparse Subspace Clustering via Group Sparse Coding

Svetha Venkatesh, Duc-Son Pham, Dinh Q. Phung, 2013, SDM.

Sparse Subspace Representation for Spectral Document Clustering

Svetha Venkatesh, Duc-Son Pham, Dinh Q. Phung, 2012, 2012 IEEE 12th International Conference on Data Mining.

Infrequent Item Mining in Multiple Data Streams

Svetha Venkatesh, Mihai Lazarescu, Budhaditya Saha, 2007, Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007).

Detection of cross-channel anomalies

Dinh Q. Phung, S. Venkatesh, Duc-Son Pham, 2013, Knowledge and Information Systems.

Detection of Cross-Channel Anomalies from Multiple Data Channels

Svetha Venkatesh, Duc-Son Pham, Dinh Q. Phung, 2011, 2011 IEEE 11th International Conference on Data Mining.