PRINCIPAL APPLIED SCIENTIST
I am a senior applied scientist in the applied sciences - CISL group of MSR India, Bangalore, and is technical lead for the members of this group. There are two applied scientists and research development engineers. My current research interests are in the areas of large scale machine learning, numerical optimization and data mining. There are several projects that we are involved in - distributed machine learning (linear solvers), missing value imputation, interactive learning (e.g., for table search task completion), anomaly detection and developer analytics. Several of them nearing completion. All these projects are done in collaboration with CISL scientists, MSR researchers and other product groups such as AIP (Boston), Ad Center (IDC, Bangalore) and App Analytics group (IDC, Hyderabad).
- Dhruv Mahajan, S. Sathiya Keerthi, and Sundararajan Sellamanickam, A distributed block coordinate descent method for training l1 regularized linear classifiers, CoRR, 2014.
- Dhruv Mahajan, S. Sathiya Keerthi, and Sundararajan Sellamanickam, A Distributed Algorithm for Training Nonlinear Kernel Machines, CoRR, 2014.
- P.K. Srijith, Shirish Shevade, and S. Sundararajan, Semi-supervised Gaussian Process Ordinal Regression, European Conference on Machine Learning (ECML), June 2013.
- Kai-Wei Chang, S. Sundararajan, and S. Sathiya Keerthi, Tractable semi-supervised learning of complex structured prediction models, European Conference on Machine Learning (ECML), June 2013.
- Tanuja Ganu, Shirish Shevade, and S. Sundararajan, Sparse Max-Margin Multiclass and Multi-label Classifier Design for Fast Inference, SIAM International Conference on Data Mining (SDM), April 2013.
- Dhruv Mahajan, S. Sathiya Keerthi, Sundararajan Sellamanickam, and Leon Bottou, A Functional Approximation Based Distributed Learning Algorithm, CoRR, 2013.
- Dhruv Mahajan, S. Sathiya Keerthi, Sundararajan Sellamanickam, and Leon Bottou, A Parallel SGD method with Strong Convergence, NIPS 2013 Workshop on Optimization for Machine Learning, 2013.
- Shravan Narayanamurthy, Markus Weimer, Dhruv Mahajan, Tyson Condie, Sundararajan Sellamanickam, and S. Sathiya Keerthi, Towards Resource-Elastic Machine Learning, NIPS 2013 BigLearn Workshop, 2013.
- Dhruv Mahajan, Sundararajan Sellamanickam, Subhajit Sanyal, and Amit Madaan, A Classification Based Framework for Concept Summarization, International Conference on Data Mining (ICDM), December 2012.
- Sathiya Keerthi Selvaraj, Sundararajan Sellamanickam, and Shirish Krishnaj Shevade, Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses, in COLING (Posters), 2012.