Venkateswara Rao Kagita

According to our database, Venkateswara Rao Kagita authored at least 30 papers between 2013 and 2024.

Collaborative distances:

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

2024

Data augmentation and refinement for recommender system: A semi-supervised approach using maximum margin matrix factorization.

Shamal Shaikh, Venkateswara Rao Kagita, Vikas Kumar, Arun K. Pujari

Expert Syst. Appl., March, 2024

UniRecSys: A unified framework for personalized, group, package, and package-to-group recommendations.

Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita, Arun K. Pujari

Knowl. Based Syst., 2024

Approval-Based Committee Voting under Uncertainty.

Haris Aziz, Venkateswara Rao Kagita, Baharak Rastegari, Mashbat Suzuki

CoRR, 2024

2023

High-performance computing for static security assessment of large power systems.

Venkateswara Rao Kagita, Sanjaya Kumar Panda, Ram Krishan, P. Deepak Reddy, Jabba Aswanth

Connect. Sci., December, 2023

Conformal Group Recommender System.

Venkateswara Rao Kagita, Anshuman Singh, Vikas Kumar, Pavan Kalyan Reddy Neerudu, Arun K. Pujari, Rohit Kumar Bondugula

CoRR, 2023

Cross-domain Recommender Systems via Multimodal Domain Adaptation.

Ramya Kamani, Vikas Kumar, Venkateswara Rao Kagita

CoRR, 2023

Data augmentation for recommender system: A semi-supervised approach using maximum margin matrix factorization.

Shamal Shaikh, Venkateswara Rao Kagita, Vikas Kumar, Arun K. Pujari

CoRR, 2023

On Robustness of Finetuned Transformer-based NLP Models.

Pavan Kalyan Reddy Neerudu, Subba Reddy Oota, Mounika Marreddy, Venkateswara Rao Kagita, Manish Gupta

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

Inductive conformal recommender system.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

Knowl. Based Syst., 2022

2021

Efficient Computation of Top-K Skyline Objects in Data Set With Uncertain Preferences.

Nitesh Sukhwani, Venkateswara Rao Kagita, Vikas Kumar, Sanjaya Kumar Panda

Int. J. Data Warehous. Min., 2021

Committee Selection using Attribute Approvals.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Haris Aziz, Vikas Kumar

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2019

Skyline recommendation with uncertain preferences.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

Pattern Recognit. Lett., 2019

Group preserving label embedding for multi-label classification.

Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita

Pattern Recognit., 2019

Committee Selection with Attribute Level Preferences.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

CoRR, 2019

2018

Multi-label classification using hierarchical embedding.

Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Venkateswara Rao Kagita

Expert Syst. Appl., 2018

2017

Proximal maximum margin matrix factorization for collaborative filtering.

Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan

Pattern Recognit. Lett., 2017

Collaborative filtering using multiple binary maximum margin matrix factorizations.

Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan

Inf. Sci., 2017

Conformal recommender system.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Vikas Kumar

Inf. Sci., 2017

Bounds on skyline probability for databases with uncertain preferences.

Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita

Int. J. Approx. Reason., 2017

2016

Threshold-Based Direct Computation of Skyline Objects for Database with Uncertain Preferences.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar, Sandeep Kumar Sahu

Proceedings of the PRICAI 2016: Trends in Artificial Intelligence, 2016

2015

Efficient computation for probabilistic skyline over uncertain preferences.

Arun K. Pujari, Venkateswara Rao Kagita, Anubhuti Garg, Vineet Padmanabhan

Inf. Sci., 2015

Virtual user approach for group recommender systems using precedence relations.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan

Inf. Sci., 2015

Greedy partitioning based tree structured multiclass SVM for Odia OCR.

Sandeep Kumar Sahu, Arun K. Pujari, Vikas Kumar, Venkateswara Rao Kagita, Vineet Padmanabhan

Proceedings of the 2015 Fifth National Conference on Computer Vision, 2015

Recommender system algorithms: A comparative analysis based on monotonicity.

Tadiparthi V. R. Himabindu, Vineet Padmanabhan, Venkateswara Rao Kagita, Arun K. Pujari

Proceedings of the Eighth International Conference on Advances in Pattern Recognition, 2015

GP-SVM: Tree Structured Multiclass SVM with Greedy Partitioning.

Sandeep Kumar Sahu, Arun K. Pujari, Venkateswara Rao Kagita, Vikas Kumar, Vineet Padmanabhan

Proceedings of the 2015 International Conference on Information Technology, 2015

A Novel Social-Choice Strategy for Group Modeling in Recommender Systems.

Venkateswara Rao Kagita, Krishna Charan Meka, Vineet Padmanabhan

Proceedings of the 2015 International Conference on Information Technology, 2015

Bi-directional Search for Skyline Probability.

Arun K. Pujari, Venkateswara Rao Kagita, Anubhuti Garg, Vineet Padmanabhan

Proceedings of the Algorithms and Discrete Applied Mathematics, 2015

2014

Collaborative filtering by PSO-based MMMF.

Sowmini Devi V., Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan

Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014

2013

Precedence Mining in Group Recommender Systems.

Venkateswara Rao Kagita, Vineet Padmanabhan, Arun K. Pujari

Proceedings of the Pattern Recognition and Machine Intelligence, 2013

Group Recommender Systems: A Virtual User Approach Based on Precedence Mining.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan

Proceedings of the AI 2013: Advances in Artificial Intelligence, 2013