Sundararajan Sellamanickam

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 22

Top Topics

Eigendecomposition

Top Venues

J. Mach. Learn. Res.

Publications

Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. CoRR (2023)
Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari, Nagarajan Natarajan, Sundararajan Sellamanickam, Venkat N. Padmanabhan
Simulating Network Paths with Recurrent Buffering Units. AAAI (2023)
Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. NeurIPS (2023)
Sachin Ashok, Shubham Tiwari, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam
Data-Driven Network Path Simulation with iBox. Proc. ACM Meas. Anal. Comput. Syst. 6 (1) (2022)
Sachin Ashok, Shubham Tiwari, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam
Data-Driven Network Path Simulation with iBox. SIGMETRICS (Abstracts) (2022)
S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam
IGLU: Efficient GCN Training via Lazy Updates. ICLR (2022)
Vijay Lingam, Manan Sharma, Chanakya Ekbote, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
A Piece-Wise Polynomial Filtering Approach for Graph Neural Networks. ECML/PKDD (2) (2022)
Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari, Nagarajan Natarajan, Sundararajan Sellamanickam, Venkata N. Padmanabhan
Simulating Network Paths with Recurrent Buffering Units. CoRR (2022)
Vijay Lingam, Chanakya Ekbote, Manan Sharma, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
A Piece-wise Polynomial Filtering Approach for Graph Neural Networks. CoRR (2021)
Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks. CoRR (2021)
S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam
IGLU: Efficient GCN Training via Lazy Updates. CoRR (2021)
Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer, Ramakrishna Bairi
User Embedding based Neighborhood Aggregation Method for Inductive Recommendation. CoRR (2021)
Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification. WSDM (2021)
Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs. CoRR (2021)
Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification. CoRR (2020)
Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer
A Graph Convolutional Network Composition Framework for Semi-supervised Classification. CoRR (2020)
Sachin Ashok, Sai Surya Duvvuri, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam, Johannes Gehrke
iBox: Internet in a Box. HotNets (2020)
Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, Sundararajan Sellamanickam, Léon Bottou
An efficient distributed learning algorithm based on effective local functional approximations. J. Mach. Learn. Res. 19 (2018)
Dhruv Mahajan, Vivek Gupta, S. Sathiya Keerthi, Sundararajan Sellamanickam, Shravan Narayanamurthy, Rahul Kidambi
Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles. CoRR (2017)
Madhusudan Lakshmana, Sundararajan Sellamanickam, Shirish K. Shevade, Keerthi Selvaraj
Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification. CoRR (2016)
Dhruv Mahajan, Vishwajit Kolathur, Chetan Bansal, Suresh Parthasarathy, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke
Hashtag Recommendation for Enterprise Applications. CIKM (2016)
Vinod Nair, Ameya Raul, Shwetabh Khanduja, Vikas Bahirwani, Sundararajan Sellamanickam, S. Sathiya Keerthi, Steve Herbert, Sudheer Dhulipalla
Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues. KDD (2015)
Balamurugan Palaniappan, Shirish K. Shevade, Sundararajan Sellamanickam
Large Margin Semi-supervised Structured Output Learning. CoRR (2013)
Rahul Kidambi, Vinod Nair, Sundararajan Sellamanickam, S. Sathiya Keerthi
A Structured Prediction Approach for Missing Value Imputation. CoRR (2013)
Vinod Nair, Rahul Kidambi, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke, Vijay Narayanan
A Quantitative Evaluation Framework for Missing Value Imputation Algorithms. CoRR (2013)
Tanuja Ganu, Sundararajan Sellamanickam, Shirish K. Shevade
Sparse Max-Margin Multiclass and Multi-label Classifier Design for Fast Inference. SDM (2013)
Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Predictive Approaches For Gaussian Process Classifier Model Selection CoRR (2012)
Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Graph Based Classification Methods Using Inaccurate External Classifier Information CoRR (2012)
Nakul Verma, Dhruv Mahajan, Sundararajan Sellamanickam, Vinod Nair
Learning hierarchical similarity metrics. CVPR (2012)
Vinod Nair, Dhruv Kumar Mahajan, Sundararajan Sellamanickam
A unified approach to learning task-specific bit vector representations for fast nearest neighbor search. WWW (2012)
Sathiya Keerthi Selvaraj, Sundararajan Sellamanickam, Shirish K. Shevade
Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses CoRR (2012)
Sundararajan Sellamanickam, Shirish K. Shevade
An Additive Model View to Sparse Gaussian Process Classifier Design CoRR (2012)
Sundararajan Sellamanickam, Charu Tiwari, Sathiya Keerthi Selvaraj
Regularized Structured Output Learning with Partial Labels. SDM (2012)
Dhruv Mahajan, Sundararajan Sellamanickam, Subhajit Sanyal, Amit Madaan
A Classification Based Framework for Concept Summarization. ICDM (2012)
Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Transductive Classification Methods for Mixed Graphs CoRR (2012)
Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam
Deterministic Annealing for Semi-Supervised Structured Output Learning. AISTATS (2012)
Sathiya Keerthi Selvaraj, Sundararajan Sellamanickam, Shirish K. Shevade
Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses. COLING (Posters) (2012)
Sundararajan Sellamanickam, Priyanka Garg, Sathiya Keerthi Selvaraj
A pairwise ranking based approach to learning with positive and unlabeled examples. CIKM (2011)
Dhruv Kumar Mahajan, Sundararajan Sellamanickam, Vinod Nair
A joint learning framework for attribute models and object descriptions. ICCV (2011)
Dhruv Kumar Mahajan, Sundararajan Sellamanickam, Subhajit Sanyal, Amit Madaan
A classification based framework for concept summarization. WWW (Companion Volume) (2011)
Sathiya Keerthi Selvaraj, Bigyan Bhar, Sundararajan Sellamanickam, Shirish K. Shevade
Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset. CIKM (2011)
Sandeepkumar Satpal, Sahely Bhadra, Sundararajan Sellamanickam, Rajeev Rastogi, Prithviraj Sen
Web information extraction using Markov logic networks. WWW (Companion Volume) (2011)
Paramveer S. Dhillon, Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj
Semi-supervised multi-task learning of structured prediction models for web information extraction. CIKM (2011)
Dinesh Garg, Sundararajan Sellamanickam, Shirish K. Shevade
A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection. PAKDD (1) (2011)
Sandeepkumar Satpal, Sahely Bhadra, Sundararajan Sellamanickam, Rajeev Rastogi, Prithviraj Sen
Web information extraction using markov logic networks. KDD (2011)