Sundararajan Sellamanickam

According to our database, Sundararajan Sellamanickam authored at least 36 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations.

Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Simulating Network Paths with Recurrent Buffering Units.

Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari, Nagarajan Natarajan, Sundararajan Sellamanickam, Venkat N. Padmanabhan

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Data-Driven Network Path Simulation with iBox.

Sachin Ashok, Shubham Tiwari, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam

Proceedings of the SIGMETRICS/PERFORMANCE '22: ACM SIGMETRICS/IFIP PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems, Mumbai, India, June 6, 2022

A Piece-Wise Polynomial Filtering Approach for Graph Neural Networks.

Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

IGLU: Efficient GCN Training via Lazy Updates.

S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks.

Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam

CoRR, 2021

Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs.

Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam

CoRR, 2021

User Embedding based Neighborhood Aggregation Method for Inductive Recommendation.

Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer, Ramakrishna Bairi

CoRR, 2021

HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification.

Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam

Proceedings of the WSDM '21, 2021

2020

A Graph Convolutional Network Composition Framework for Semi-supervised Classification.

Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer

CoRR, 2020

iBox: Internet in a Box.

Sachin Ashok, Sai Surya Duvvuri, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam, Johannes Gehrke

Proceedings of the HotNets '20: The 19th ACM Workshop on Hot Topics in Networks, 2020

2018

An efficient distributed learning algorithm based on effective local functional approximations.

Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, Sundararajan Sellamanickam, Léon Bottou

J. Mach. Learn. Res., 2018

2017

Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles.

Dhruv Mahajan, Vivek Gupta, S. Sathiya Keerthi, Sundararajan Sellamanickam, Shravan Narayanamurthy, Rahul Kidambi

CoRR, 2017

2016

Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification.

Madhusudan Lakshmana, Sundararajan Sellamanickam, Shirish K. Shevade, Sathiya Keerthi Selvaraj

CoRR, 2016

Hashtag Recommendation for Enterprise Applications.

Dhruv Mahajan, Vishwajit Kolathur, Chetan Bansal, Suresh Parthasarathy, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015

Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues.

Vinod Nair, Ameya Raul, Shwetabh Khanduja, Vikas Bahirwani, Sundararajan Sellamanickam, S. Sathiya Keerthi, Steve Herbert, Sudheer Dhulipalla

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2013

Large Margin Semi-supervised Structured Output Learning.

P. Balamurugan, Shirish K. Shevade, Sundararajan Sellamanickam

CoRR, 2013

A Quantitative Evaluation Framework for Missing Value Imputation Algorithms.

Vinod Nair, Rahul Kidambi, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke, Vijay Narayanan

CoRR, 2013

A Structured Prediction Approach for Missing Value Imputation.

Rahul Kidambi, Vinod Nair, Sundararajan Sellamanickam, S. Sathiya Keerthi

CoRR, 2013

Sparse Max-Margin Multiclass and Multi-label Classifier Design for Fast Inference.

Tanuja Ganu, Sundararajan Sellamanickam, Shirish K. Shevade

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

2012

Deterministic Annealing for Semi-Supervised Structured Output Learning.

Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Predictive Approaches For Gaussian Process Classifier Model Selection

Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj

CoRR, 2012

An Additive Model View to Sparse Gaussian Process Classifier Design

Sundararajan Sellamanickam, Shirish K. Shevade

CoRR, 2012

Transductive Classification Methods for Mixed Graphs

Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj

CoRR, 2012

Graph Based Classification Methods Using Inaccurate External Classifier Information

Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj

CoRR, 2012

A unified approach to learning task-specific bit vector representations for fast nearest neighbor search.

Vinod Nair, Dhruv Kumar Mahajan, Sundararajan Sellamanickam

Proceedings of the 21st World Wide Web Conference 2012, 2012

Regularized Structured Output Learning with Partial Labels.

Sundararajan Sellamanickam, Charu Tiwari, Sathiya Keerthi Selvaraj

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Learning hierarchical similarity metrics.

Nakul Verma, Dhruv Mahajan, Sundararajan Sellamanickam, Vinod Nair

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses.

Sathiya Keerthi Selvaraj, Sundararajan Sellamanickam, Shirish K. Shevade

Proceedings of the COLING 2012, 2012

2011

A classification based framework for concept summarization.

Dhruv Kumar Mahajan, Sundararajan Sellamanickam, Subhajit Sanyal, Amit Madaan

Proceedings of the 20th International Conference on World Wide Web, 2011

A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection.

Dinesh Garg, Sundararajan Sellamanickam, Shirish K. Shevade

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2011

Web information extraction using markov logic networks.

Sandeepkumar Satpal, Sahely Bhadra, Sundararajan Sellamanickam, Rajeev Rastogi, Prithviraj Sen

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

A joint learning framework for attribute models and object descriptions.

Dhruv Kumar Mahajan, Sundararajan Sellamanickam, Vinod Nair

Proceedings of the IEEE International Conference on Computer Vision, 2011

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset.

Sathiya Keerthi Selvaraj, Bigyan Bhar, Sundararajan Sellamanickam, Shirish K. Shevade

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

A pairwise ranking based approach to learning with positive and unlabeled examples.

Sundararajan Sellamanickam, Priyanka Garg, Sathiya Keerthi Selvaraj

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

Semi-supervised multi-task learning of structured prediction models for web information extraction.

Paramveer S. Dhillon, Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011