Arunkumar Bagavathi

According to our database, Arunkumar Bagavathi authored at least 32 papers between 2017 and 2024.

Collaborative distances:

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

2024

Exploiting Adaptive Contextual Masking for Aspect-Based Sentiment Analysis.

S. M. Rafiuddin, Mohammed Rakib, Sadia Kamal, Arunkumar Bagavathi

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

HeTAN: Heterogeneous Graph Triplet Attention Network for Drug Repurposing.

Farhan Tanvir, Khaled Mohammed Saifuddin, Tanvir Hossain, Arunkumar Bagavathi, Esra Akbas

Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

MIS-ME: A Multi-Modal Framework for Soil Moisture Estimation.

Mohammed Rakib, Adil Aman Mohammed, D. Cole Diggins, Sumit Sharma, Jeff Michael Sadler, Tyson Ochsner, Arun Bagavathi

Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

2023

HeTriNet: Heterogeneous Graph Triplet Attention Network for Drug-Target-Disease Interaction.

Farhan Tanvir, Khaled Mohammed Saifuddin, Tanvir Hossain, Arunkumar Bagavathi, Esra Akbas

CoRR, 2023

Modeling Political Orientation of Social Media Posts: An Extended Analysis.

Sadia Kamal, Brenner Little, Jade Gullic, Trevor Harms, Kristin Olofsson, Arunkumar Bagavathi

CoRR, 2023

Quantitative Analysis of Forecasting Models: In the Aspect of Online Political Bias.

Srinath Sai Tripuraneni, Sadia Kamal, Arunkumar Bagavathi

Proceedings of the International Conference on Machine Learning and Applications, 2023

Learning Unbiased News Article Representations: A Knowledge-Infused Approach.

Sadia Kamal, Jimmy Hartford, Jeremy Willis, Arunkumar Bagavathi

Proceedings of the International Conference on Machine Learning and Applications, 2023

2022

Scalable Pathogen Detection from Next Generation DNA Sequencing with Deep Learning.

Sai Narayanan, Sathyanarayanan N. Aakur, Priyadharsini Ramamurthy, Arunkumar Bagavathi, Vishalini Ramnath, Akhilesh Ramachandran

CoRR, 2022

Modeling Polarization on Social Media Posts: A Heuristic Approach Using Media Bias.

Sadia Kamal, Jade Gullic, Arunkumar Bagavathi

Proceedings of the Foundations of Intelligent Systems - 26th International Symposium, 2022

2021

Unsupervised Gaze Prediction in Egocentric Videos by Energy-based Surprise Modeling.

Sathyanarayanan N. Aakur, Arunkumar Bagavathi

Proceedings of the 16th International Joint Conference on Computer Vision, 2021

Sim2Real for Metagenomes: Accelerating Animal Diagnostics with Adversarial Co-training.

Vineela Indla, Vennela Indla, Sai Narayanan, Akhilesh Ramachandran, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Sathyanarayanan N. Aakur

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

MG-NET: Leveraging Pseudo-imaging for Multi-modal Metagenome Analysis.

Sathyanarayanan N. Aakur, Sai Narayanan, Vineela Indla, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis.

Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran

Proceedings of the 2021 International Conference on Data Mining, 2021

A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches.

Prasad Hajare, Sadia Kamal, Siddharth Krishnan, Arunkumar Bagavathi

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020

Action rules for sentiment analysis using Twitter.

Angelina A. Tzacheva, Jaishree Ranganathan, Arunkumar Bagavathi

Int. J. Soc. Netw. Min., 2020

Action Rules of Lowest Cost and Action Set Correlations.

Angelina A. Tzacheva, Ramya A. Shankar, Sridharan Ramachandran, Arunkumar Bagavathi

Fundam. Informaticae, 2020

Genome Sequence Classification for Animal Diagnostics with Graph Representations and Deep Neural Networks.

Sai Narayanan, Akhilesh Ramachandran, Sathyanarayanan N. Aakur, Arunkumar Bagavathi

CoRR, 2020

Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models.

Michael Ridenhour, Arunkumar Bagavathi, Elaheh Raisi, Siddharth Krishnan

Proceedings of the Social, Cultural, and Behavioral Modeling, 2020

GRaDL: A Framework for Animal Genome Sequence Classification with Graph Representations and Deep Learning.

Sai Narayanan, Akhilesh Ramachandran, Sathyanarayanan N. Aakur, Arunkumar Bagavathi

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech Detection.

Joshua Melton, Arunkumar Bagavathi, Siddharth Krishnan

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2019

Scalable Action Mining for Recommendations to Reduce Hospital Readmission.

Arunkumar Bagavathi, Angelina A. Tzacheva

Proceedings of the 20th IEEE International Conference on Information Reuse and Integration for Data Science, 2019

Extracting Cryptocurrency Price Movements from the Reddit Network Sentiment.

Stephen Wooley, Andrew Edmonds, Arunkumar Bagavathi, Siddharth Krishnan

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music Concert.

Arunkumar Bagavathi, Siddharth Krishnan, Sanjay Subrahmanyan, S. L. Narasimhan

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Examining untempered social media: analyzing cascades of polarized conversations.

Arunkumar Bagavathi, Pedram Bashiri, Shannon Reid, Matthew Phillips, Siddharth Krishnan

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

2018

Actionable pattern discovery for Sentiment Analysis on Twitter Data in clustered environment.

Jaishree Ranganathan, Allen S. Irudayaraj, Arunkumar Bagavathi, Angelina A. Tzacheva

J. Intell. Fuzzy Syst., 2018

MultiNet: Scalable Multilayer Network Embeddings.

Arunkumar Bagavathi, Siddharth Krishnan

CoRR, 2018

Actionable Pattern Mining - A Scalable Data Distribution Method Based on Information Granules.

Arunkumar Bagavathi, Abhishek Tripathi, Angelina A. Tzacheva, Zbigniew W. Ras

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Data distribution method for scalable actionable pattern mining.

Arunkumar Bagavathi, Varun Rao, Angelina A. Tzacheva

Proceedings of the First International Conference on Data Science, 2018

Multi-Net: A Scalable Multiplex Network Embedding Framework.

Arunkumar Bagavathi, Siddharth Krishnan

Proceedings of the Complex Networks and Their Applications VII, 2018

In Search of Actionable Patterns of Lowest Cost - A Scalable Action Graph Method.

Angelina A. Tzacheva, Arunkumar Bagavathi, Sharath C. B. Suryanarayanaprasad

Proceedings of the First IEEE International Conference on Artificial Intelligence and Knowledge Engineering, 2018

2017

Discovery of Action Rules at Lowest Cost in Spark.

Angelina A. Tzacheva, Arunkumar Bagavathi, Lavanya Ayila

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017

SARGS method for distributed actionable pattern mining using spark.

Arunkumar Bagavathi, Pranava Mummoju, Katarzyna A. Tarnowska, Angelina A. Tzacheva, Zbigniew W. Ras

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017