Group Recommender Systems: A Virtual User Approach Based on Precedence Mining. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan (Australasian Conference on Artificial Intelligence, 2013)

Precedence Mining in Group Recommender Systems. - Venkateswara Rao Kagita; Vineet Padmanabhan; Arun K. Pujari (PReMI, 2013)

Collaborative filtering by PSO-based MMMF. - Sowmini Devi V.; Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan (SMC, 2014)

Bi-directional Search for Skyline Probability. - Arun K. Pujari; Venkateswara Rao Kagita; Anubhuti Garg; Vineet Padmanabhan (CALDAM, 2015)

A Novel Social-Choice Strategy for Group Modeling in Recommender Systems. - Venkateswara Rao Kagita; Krishna Charan Meka; Vineet Padmanabhan (ICIT, 2015)

GP-SVM: Tree Structured Multiclass SVM with Greedy Partitioning. - Sandeep Kumar Sahu; Arun K. Pujari; Venkateswara Rao Kagita; Vikas Kumar 003; Vineet Padmanabhan (ICIT, 2015)

Recommender system algorithms: A comparative analysis based on monotonicity. - Tadiparthi V. R. Himabindu; Vineet Padmanabhan; Venkateswara Rao Kagita; Arun K. Pujari (ICAPR, 2015)

Greedy partitioning based tree structured multiclass SVM for Odia OCR. - Sandeep Kumar Sahu; Arun K. Pujari; Vikas Kumar 003; Venkateswara Rao Kagita; Vineet Padmanabhan (NCVPRIPG, 2015)

Virtual user approach for group recommender systems using precedence relations. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan (Inf. Sci., 2015)

Efficient computation for probabilistic skyline over uncertain preferences. - Arun K. Pujari; Venkateswara Rao Kagita; Anubhuti Garg; Vineet Padmanabhan (Inf. Sci., 2015)

Threshold-Based Direct Computation of Skyline Objects for Database with Uncertain Preferences. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003; Sandeep Kumar Sahu (PRICAI, 2016)

Bounds on skyline probability for databases with uncertain preferences. - Arun K. Pujari; Vineet Padmanabhan; Venkateswara Rao Kagita (Int. J. Approx. Reason., 2017)

Conformal recommender system. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Sandeep Kumar Sahu; Vikas Kumar 003 (Inf. Sci., 2017)

Collaborative filtering using multiple binary maximum margin matrix factorizations. - Vikas Kumar 003; Arun K. Pujari; Sandeep Kumar Sahu; Venkateswara Rao Kagita; Vineet Padmanabhan (Inf. Sci., 2017)

Proximal maximum margin matrix factorization for collaborative filtering. - Vikas Kumar 003; Arun K. Pujari; Sandeep Kumar Sahu; Venkateswara Rao Kagita; Vineet Padmanabhan (Pattern Recognit. Lett., 2017)

Multi-label classification using hierarchical embedding. - Vikas Kumar 003; Arun K. Pujari; Vineet Padmanabhan; Sandeep Kumar Sahu; Venkateswara Rao Kagita (Expert Syst. Appl., 2018)

Committee Selection with Attribute Level Preferences. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (CoRR, 2019)

Group preserving label embedding for multi-label classification. - Vikas Kumar 003; Arun K. Pujari; Vineet Padmanabhan; Venkateswara Rao Kagita (Pattern Recognit., 2019)

Skyline recommendation with uncertain preferences. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (Pattern Recognit. Lett., 2019)

Committee Selection using Attribute Approvals. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Haris Aziz 001; Vikas Kumar 003 (AAMAS, 2021)

Efficient Computation of Top-K Skyline Objects in Data Set With Uncertain Preferences. - Nitesh Sukhwani; Venkateswara Rao Kagita; Vikas Kumar 003; Sanjaya Kumar Panda (Int. J. Data Warehous. Min., 2021)

Inductive conformal recommender system. - Venkateswara Rao Kagita; Arun K. Pujari; Vineet Padmanabhan; Vikas Kumar 003 (Knowl. Based Syst., 2022)

On Robustness of Finetuned Transformer-based NLP Models. - Pavan Kalyan Reddy Neerudu; Subba Reddy Oota; Mounika Marreddy; Venkateswara Rao Kagita; Manish Gupta 001 (EMNLP (Findings), 2023)

Data augmentation for recommender system: A semi-supervised approach using maximum margin matrix factorization. - Shamal Shaikh; Venkateswara Rao Kagita; Vikas Kumar 003; Arun K. Pujari (CoRR, 2023)

Cross-domain Recommender Systems via Multimodal Domain Adaptation. - Ramya Kamani; Vikas Kumar 003; Venkateswara Rao Kagita (CoRR, 2023)

Conformal Group Recommender System. - Venkateswara Rao Kagita; Anshuman Singh; Vikas Kumar 003; Pavan Kalyan Reddy Neerudu; Arun K. Pujari; Rohit Kumar Bondugula (CoRR, 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., 2023)

gCDR: A Group Aided Cross-Domain Recommendation Framework. - Adamya Shyam; Kavita Kanwar; Vikas Kumar 003; Venkateswara Rao Kagita (BDA, 2024)

Approval-Based Committee Voting under Uncertainty. - Haris Aziz 001; Venkateswara Rao Kagita; Baharak Rastegari; Mashbat Suzuki (CoRR, 2024)

UniRecSys: A unified framework for personalized, group, package, and package-to-group recommendations. - Adamya Shyam; Vikas Kumar 003; Venkateswara Rao Kagita; Arun K. Pujari (Knowl. Based Syst., 2024)

Data augmentation and refinement for recommender system: A semi-supervised approach using maximum margin matrix factorization. - Shamal Shaikh; Venkateswara Rao Kagita; Vikas Kumar 003; Arun K. Pujari (Expert Syst. Appl., 2024)

Cross-domain recommender systems via multimodal domain adaptation. - Adamya Shyam; Ramya Kamani; Venkateswara Rao Kagita; Vikas Kumar 003 (Comput. Electr. Eng., 2025)

Social Welfare Maximization in Approval-Based Committee Voting under Uncertainty. - Haris Aziz 001; Yuhang Guo; Venkateswara Rao Kagita; Baharak Rastegari; Mashbat Suzuki (CoRR, 2025)

Geometric Preference Elicitation for Minimax Regret Optimization in Uncertainty Matroids. - Aditya Sai Ellendula; Arun K. Pujari; Vikas Kumar 003; Venkateswara Rao Kagita (CoRR, 2025)