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ORCIDSundararajan Sellamanickam
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2020 – today
- 2023
[c24]Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari, Nagarajan Natarajan, Sundararajan Sellamanickam, Venkat N. Padmanabhan:
Simulating Network Paths with Recurrent Buffering Units. AAAI 2023: 6684-6692- [c23]Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Sundararajan Sellamanickam, Ramakrishna Bairi:
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. NeurIPS 2023 - [i19]Chanakya Ekbote, Ajinkya Pankaj Deshpande, Arun Iyer, Ramakrishna Bairi, Sundararajan Sellamanickam:
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations. CoRR abs/2310.01892 (2023) - 2022
- [j2]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): 6:1-6:26 (2022) - [c22]S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam:
IGLU: Efficient GCN Training via Lazy Updates. ICLR 2022 - [c21]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: 412-452 - [c20]Sachin Ashok, Shubham Tiwari, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam:
Data-Driven Network Path Simulation with iBox. SIGMETRICS (Abstracts) 2022: 47-48 - [i18]Divyam Anshumaan, Sriram Balasubramanian, Shubham Tiwari, Nagarajan Natarajan, Sundararajan Sellamanickam, Venkata N. Padmanabhan:
Simulating Network Paths with Recurrent Buffering Units. CoRR abs/2202.13870 (2022) - 2021
- [c19]Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam:
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification. WSDM 2021: 860-868 - [i17]Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer, Ramakrishna Bairi:
User Embedding based Neighborhood Aggregation Method for Inductive Recommendation. CoRR abs/2102.07575 (2021) - [i16]Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam:
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs. CoRR abs/2106.12807 (2021) - [i15]Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam:
Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks. CoRR abs/2107.13312 (2021) - [i14]S. Deepak Narayanan, Aditya Sinha, Prateek Jain, Purushottam Kar, Sundararajan Sellamanickam:
IGLU: Efficient GCN Training via Lazy Updates. CoRR abs/2109.13995 (2021) - [i13]Vijay Lingam, Chanakya Ekbote, Manan Sharma, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam:
A Piece-wise Polynomial Filtering Approach for Graph Neural Networks. CoRR abs/2112.03499 (2021) - 2020
- [c18]Sachin Ashok, Sai Surya Duvvuri, Nagarajan Natarajan, Venkata N. Padmanabhan, Sundararajan Sellamanickam, Johannes Gehrke:
iBox: Internet in a Box. HotNets 2020: 23-29 - [i12]Rahul Ragesh, Sundararajan Sellamanickam, Vijay Lingam, Arun Iyer:
A Graph Convolutional Network Composition Framework for Semi-supervised Classification. CoRR abs/2004.03994 (2020) - [i11]Rahul Ragesh, Sundararajan Sellamanickam, Arun Iyer, Ramakrishna Bairi, Vijay Lingam:
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification. CoRR abs/2008.12842 (2020)
2010 – 2019
- 2018
- [j1]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: 74:1-74:37 (2018) - 2017
- [i10]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 abs/1711.05482 (2017) - 2016
- [c17]Dhruv Mahajan, Vishwajit Kolathur, Chetan Bansal, Suresh Parthasarathy, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke:
Hashtag Recommendation for Enterprise Applications. CIKM 2016: 893-902 - [i9]Madhusudan Lakshmana, Sundararajan Sellamanickam, Shirish K. Shevade, Keerthi Selvaraj:
Learning Semantically Coherent and Reusable Kernels in Convolution Neural Nets for Sentence Classification. CoRR abs/1608.00466 (2016) - 2015
- [c16]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: 2029-2038 - 2013
- [c15]Tanuja Ganu, Sundararajan Sellamanickam, Shirish K. Shevade:
Sparse Max-Margin Multiclass and Multi-label Classifier Design for Fast Inference. SDM 2013: 423-431 - [i8]Rahul Kidambi, Vinod Nair, Sundararajan Sellamanickam, S. Sathiya Keerthi:
A Structured Prediction Approach for Missing Value Imputation. CoRR abs/1311.2137 (2013) - [i7]Balamurugan Palaniappan, Shirish K. Shevade, Sundararajan Sellamanickam:
Large Margin Semi-supervised Structured Output Learning. CoRR abs/1311.2139 (2013) - [i6]Vinod Nair, Rahul Kidambi, Sundararajan Sellamanickam, S. Sathiya Keerthi, Johannes Gehrke, Vijay Narayanan:
A Quantitative Evaluation Framework for Missing Value Imputation Algorithms. CoRR abs/1311.2276 (2013) - 2012
- [c14]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: 1091-1100 - [c13]Nakul Verma, Dhruv Mahajan, Sundararajan Sellamanickam, Vinod Nair:
Learning hierarchical similarity metrics. CVPR 2012: 2280-2287 - [c12]Dhruv Mahajan, Sundararajan Sellamanickam, Subhajit Sanyal, Amit Madaan:
A Classification Based Framework for Concept Summarization. ICDM 2012: 1008-1013 - [c11]Sundararajan Sellamanickam, Charu Tiwari, Sathiya Keerthi Selvaraj:
Regularized Structured Output Learning with Partial Labels. SDM 2012: 1059-1070 - [c10]Vinod Nair, Dhruv Kumar Mahajan, Sundararajan Sellamanickam:
A unified approach to learning task-specific bit vector representations for fast nearest neighbor search. WWW 2012: 929-938 - [c9]Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam:
Deterministic Annealing for Semi-Supervised Structured Output Learning. AISTATS 2012: 299-307 - [i5]Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj:
Graph Based Classification Methods Using Inaccurate External Classifier Information. CoRR abs/1206.5915 (2012) - [i4]Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj:
Transductive Classification Methods for Mixed Graphs. CoRR abs/1206.6015 (2012) - [i3]Sundararajan Sellamanickam, Shirish K. Shevade:
An Additive Model View to Sparse Gaussian Process Classifier Design. CoRR abs/1206.6030 (2012) - [i2]Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj:
Predictive Approaches For Gaussian Process Classifier Model Selection. CoRR abs/1206.6038 (2012) - [i1]Sathiya Keerthi Selvaraj, Sundararajan Sellamanickam, Shirish K. Shevade:
Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses. CoRR abs/1211.0210 (2012) - 2011
- [c8]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: 653-662 - [c7]Sundararajan Sellamanickam, Priyanka Garg, Sathiya Keerthi Selvaraj:
A pairwise ranking based approach to learning with positive and unlabeled examples. CIKM 2011: 663-672 - [c6]Paramveer S. Dhillon, Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj:
Semi-supervised multi-task learning of structured prediction models for web information extraction. CIKM 2011: 957-966 - [c5]Dhruv Kumar Mahajan, Sundararajan Sellamanickam, Vinod Nair:
A joint learning framework for attribute models and object descriptions. ICCV 2011: 1227-1234 - [c4]Sandeepkumar Satpal, Sahely Bhadra, Sundararajan Sellamanickam, Rajeev Rastogi, Prithviraj Sen:
Web information extraction using markov logic networks. KDD 2011: 1406-1414 - [c3]Dinesh Garg, Sundararajan Sellamanickam, Shirish K. Shevade:
A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection. PAKDD (1) 2011: 13-25 - [c2]Dhruv Kumar Mahajan, Sundararajan Sellamanickam, Subhajit Sanyal, Amit Madaan:
A classification based framework for concept summarization. WWW (Companion Volume) 2011: 83-84 - [c1]Sandeepkumar Satpal, Sahely Bhadra, Sundararajan Sellamanickam, Rajeev Rastogi, Prithviraj Sen:
Web information extraction using Markov logic networks. WWW (Companion Volume) 2011: 115-116
Coauthor Index
aka: Sathiya Keerthi Selvaraj
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