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Arunkumar Bagavathi
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2020 – today
- 2024
- [c22]S. M. Rafiuddin
, Mohammed Rakib
, Sadia Kamal
, Arunkumar Bagavathi
:
Exploiting Adaptive Contextual Masking for Aspect-Based Sentiment Analysis. PAKDD (6) 2024: 147-159 - [i16]S. M. Rafiuddin, Mohammed Rakib, Sadia Kamal, Arunkumar Bagavathi:
Exploiting Adaptive Contextual Masking for Aspect-Based Sentiment Analysis. CoRR abs/2402.13722 (2024) - 2023
- [c21]Sadia Kamal, Jimmy Hartford, Jeremy Willis, Arunkumar Bagavathi:
Learning Unbiased News Article Representations: A Knowledge-Infused Approach. ICMLA 2023: 639-646 - [c20]Srinath Sai Tripuraneni, Sadia Kamal, Arunkumar Bagavathi:
Quantitative Analysis of Forecasting Models: In the Aspect of Online Political Bias. ICMLA 2023: 1295-1299 - [i15]Srinath Sai Tripuraneni, Sadia Kamal, Arunkumar Bagavathi
:
Quantitative Analysis of Forecasting Models: In the Aspect of Online Political Bias. CoRR abs/2309.05589 (2023) - [i14]Sadia Kamal, Jimmy Hartford, Jeremy Willis, Arunkumar Bagavathi
:
Learning Unbiased News Article Representations: A Knowledge-Infused Approach. CoRR abs/2309.05981 (2023) - [i13]Sadia Kamal, Brenner Little, Jade Gullic, Trevor Harms, Kristin Olofsson, Arunkumar Bagavathi:
Modeling Political Orientation of Social Media Posts: An Extended Analysis. CoRR abs/2311.12323 (2023) - [i12]Farhan Tanvir, Khaled Mohammed Saifuddin, Tanvir Hossain, Arunkumar Bagavathi, Esra Akbas:
HeTriNet: Heterogeneous Graph Triplet Attention Network for Drug-Target-Disease Interaction. CoRR abs/2312.00189 (2023) - 2022
- [c19]Sadia Kamal, Jade Gullic, Arunkumar Bagavathi
:
Modeling Polarization on Social Media Posts: A Heuristic Approach Using Media Bias. ISMIS 2022: 35-43 - [i11]Sai Narayanan, Sathyanarayanan N. Aakur, Priyadharsini Ramamurthy, Arunkumar Bagavathi
, Vishalini Ramnath, Akhilesh Ramachandran:
Scalable Pathogen Detection from Next Generation DNA Sequencing with Deep Learning. CoRR abs/2212.00015 (2022) - 2021
- [c18]Prasad Hajare, Sadia Kamal, Siddharth Krishnan, Arunkumar Bagavathi
:
A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches. ICMLA 2021: 239-243 - [c17]Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi
, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis. ICDM (Workshops) 2021: 500-507 - [c16]Sathyanarayanan N. Aakur, Sai Narayanan, Vineela Indla, Arunkumar Bagavathi
, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
MG-NET: Leveraging Pseudo-imaging for Multi-modal Metagenome Analysis. MICCAI (5) 2021: 592-602 - [c15]Vineela Indla, Vennela Indla, Sai Narayanan, Akhilesh Ramachandran, Arunkumar Bagavathi
, Vishalini Laguduva Ramnath, Sathyanarayanan N. Aakur:
Sim2Real for Metagenomes: Accelerating Animal Diagnostics with Adversarial Co-training. PAKDD (1) 2021: 164-175 - [c14]Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
Unsupervised Gaze Prediction in Egocentric Videos by Energy-based Surprise Modeling. VISIGRAPP (5: VISAPP) 2021: 935-942 - [i10]Sathyanarayanan N. Aakur, Sai Narayanan, Vineela Indla, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
MG-NET: Leveraging Pseudo-Imaging for Multi-Modal Metagenome Analysis. CoRR abs/2107.09883 (2021) - [i9]Prasad Hajare, Sadia Kamal, Siddharth Krishnan, Arunkumar Bagavathi:
A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches. CoRR abs/2109.09014 (2021) - [i8]Sathyanarayanan N. Aakur, Vineela Indla, Vennela Indla, Sai Narayanan, Arunkumar Bagavathi, Vishalini Laguduva Ramnath, Akhilesh Ramachandran:
Metagenome2Vec: Building Contextualized Representations for Scalable Metagenome Analysis. CoRR abs/2111.08001 (2021) - 2020
- [j3]Angelina A. Tzacheva, Ramya A. Shankar, Sridharan Ramachandran, Arunkumar Bagavathi
:
Action Rules of Lowest Cost and Action Set Correlations. Fundam. Informaticae 172(4): 399-412 (2020) - [j2]Angelina A. Tzacheva, Jaishree Ranganathan, Arunkumar Bagavathi:
Action rules for sentiment analysis using Twitter. Int. J. Soc. Netw. Min. 3(1): 35-51 (2020) - [c13]Joshua Melton, Arunkumar Bagavathi
, Siddharth Krishnan:
DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech Detection. ICMLA 2020: 1015-1022 - [c12]Sai Narayanan, Akhilesh Ramachandran, Sathyanarayanan N. Aakur, Arunkumar Bagavathi
:
GRaDL: A Framework for Animal Genome Sequence Classification with Graph Representations and Deep Learning. ICMLA 2020: 1297-1303 - [c11]Michael Ridenhour, Arunkumar Bagavathi
, Elaheh Raisi, Siddharth Krishnan:
Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models. SBP-BRiMS 2020: 202-212 - [i7]Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
Unsupervised Gaze Prediction in Egocentric Videos by Energy-based Surprise Modeling. CoRR abs/2001.11580 (2020) - [i6]Michael Ridenhour, Arunkumar Bagavathi, Elaheh Raisi, Siddharth Krishnan:
Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models. CoRR abs/2007.12724 (2020) - [i5]Sai Narayanan, Akhilesh Ramachandran, Sathyanarayanan N. Aakur, Arunkumar Bagavathi:
Genome Sequence Classification for Animal Diagnostics with Graph Representations and Deep Neural Networks. CoRR abs/2007.12791 (2020) - [i4]Joshua Melton, Arunkumar Bagavathi, Siddharth Krishnan:
DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech Detection. CoRR abs/2011.01861 (2020)
2010 – 2019
- 2019
- [c10]Arunkumar Bagavathi
, Pedram Bashiri, Shannon Reid, Matthew Phillips, Siddharth Krishnan:
Examining untempered social media: analyzing cascades of polarized conversations. ASONAM 2019: 625-632 - [c9]Stephen Wooley, Andrew Edmonds, Arunkumar Bagavathi
, Siddharth Krishnan:
Extracting Cryptocurrency Price Movements from the Reddit Network Sentiment. ICMLA 2019: 500-505 - [c8]Arunkumar Bagavathi
, Siddharth Krishnan, Sanjay Subrahmanyan, S. L. Narasimhan:
ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music Concert. ICMLA 2019: 1517-1522 - [c7]Arunkumar Bagavathi
, Angelina A. Tzacheva:
Scalable Action Mining for Recommendations to Reduce Hospital Readmission. IRI 2019: 159-166 - [i3]Arunkumar Bagavathi, Pedram Bashiri, Shannon Reid, Matthew Phillips, Siddharth Krishnan:
Examining Untempered Social Media: Analyzing Cascades of Polarized Conversations. CoRR abs/1906.04261 (2019) - [i2]Arunkumar Bagavathi, Siddharth Krishnan, Sanjay Subrahmanyan, S. L. Narasimhan:
ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music Concert. CoRR abs/1912.03769 (2019) - 2018
- [j1]Jaishree Ranganathan, Allen S. Irudayaraj, Arunkumar Bagavathi
, Angelina A. Tzacheva:
Actionable pattern discovery for Sentiment Analysis on Twitter Data in clustered environment. J. Intell. Fuzzy Syst. 34(5): 2849-2863 (2018) - [c6]Angelina A. Tzacheva, Arunkumar Bagavathi
, Sharath C. B. Suryanarayanaprasad:
In Search of Actionable Patterns of Lowest Cost - A Scalable Action Graph Method. AIKE 2018: 119-124 - [c5]Arunkumar Bagavathi
, Siddharth Krishnan:
Multi-Net: A Scalable Multiplex Network Embedding Framework. COMPLEX NETWORKS (2) 2018: 119-131 - [c4]Arunkumar Bagavathi
, Varun Rao, Angelina A. Tzacheva:
Data distribution method for scalable actionable pattern mining. DATA 2018: 3:1-3:7 - [c3]Arunkumar Bagavathi
, Abhishek Tripathi, Angelina A. Tzacheva, Zbigniew W. Ras:
Actionable Pattern Mining - A Scalable Data Distribution Method Based on Information Granules. ICMLA 2018: 32-39 - [i1]Arunkumar Bagavathi, Siddharth Krishnan:
MultiNet: Scalable Multilayer Network Embeddings. CoRR abs/1805.10172 (2018) - 2017
- [c2]Arunkumar Bagavathi
, Pranava Mummoju, Katarzyna A. Tarnowska
, Angelina A. Tzacheva, Zbigniew W. Ras:
SARGS method for distributed actionable pattern mining using spark. IEEE BigData 2017: 4272-4281 - [c1]Angelina A. Tzacheva, Arunkumar Bagavathi
, Lavanya Ayila:
Discovery of Action Rules at Lowest Cost in Spark. ICDM Workshops 2017: 87-94
Coauthor Index
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last updated on 2024-08-05 21:11 CEST by the dblp team
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