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ORCIDVenkateswara Rao Kagita
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2020 – today
- 2024
[j14]Shamal Shaikh
, Venkateswara Rao Kagita, Vikas Kumar, Arun K. Pujari:
Data augmentation and refinement for recommender system: A semi-supervised approach using maximum margin matrix factorization. Expert Syst. Appl. 238(Part B): 121967 (2024)- [j13]Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita, Arun K. Pujari:
UniRecSys: A unified framework for personalized, group, package, and package-to-group recommendations. Knowl. Based Syst. 289: 111552 (2024) - [i9]Hariz Aziz, Venkateswara Rao Kagita, Baharak Rastegari, Mashbat Suzuki:
Approval-Based Committee Voting under Uncertainty. CoRR abs/2407.19391 (2024) - 2023
- [j12]Venkateswara Rao Kagita, Sanjaya Kumar Panda, Ram Krishan, P. Deepak Reddy, Jabba Aswanth:
High-performance computing for static security assessment of large power systems. Connect. Sci. 35(1) (2023) - [c11]Pavan Kalyan Reddy Neerudu, Subba Reddy Oota, Mounika Marreddy, Venkateswara Rao Kagita, Manish Gupta:
On Robustness of Finetuned Transformer-based NLP Models. EMNLP (Findings) 2023: 7180-7195 - [i8]Pavan Kalyan Reddy Neerudu, Subba Reddy Oota, Mounika Marreddy, Venkateswara Rao Kagita, Manish Gupta:
On Robustness of Finetuned Transformer-based NLP Models. CoRR abs/2305.14453 (2023) - [i7]Shamal Shaikh, Venkateswara Rao Kagita, Vikas Kumar, Arun K. Pujari:
Data augmentation for recommender system: A semi-supervised approach using maximum margin matrix factorization. CoRR abs/2306.13050 (2023) - [i6]Ramya Kamani, Vikas Kumar, Venkateswara Rao Kagita:
Cross-domain Recommender Systems via Multimodal Domain Adaptation. CoRR abs/2306.13887 (2023) - [i5]Venkateswara Rao Kagita, Anshuman Singh, Vikas Kumar, Pavan Kalyan Reddy Neerudu, Arun K. Pujari, Rohit Kumar Bondugula:
Conformal Group Recommender System. CoRR abs/2307.12034 (2023) - [i4]Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita, Arun K. Pujari:
UniRecSys: A Unified Framework for Personalized, Group, Package, and Package-to-Group Recommendations. CoRR abs/2308.04247 (2023) - 2022
- [j11]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Inductive conformal recommender system. Knowl. Based Syst. 250: 109108 (2022) - 2021
- [j10]Nitesh Sukhwani, Venkateswara Rao Kagita, Vikas Kumar, Sanjaya Kumar Panda:
Efficient Computation of Top-K Skyline Objects in Data Set With Uncertain Preferences. Int. J. Data Warehous. Min. 17(3): 68-80 (2021) - [c10]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Haris Aziz, Vikas Kumar:
Committee Selection using Attribute Approvals. AAMAS 2021: 683-691 - [i3]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Inductive Conformal Recommender System. CoRR abs/2109.08949 (2021)
2010 – 2019
- 2019
- [j9]Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita:
Group preserving label embedding for multi-label classification. Pattern Recognit. 90: 23-34 (2019) - [j8]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Skyline recommendation with uncertain preferences. Pattern Recognit. Lett. 125: 446-452 (2019) - [i2]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Committee Selection with Attribute Level Preferences. CoRR abs/1901.10064 (2019) - 2018
- [j7]Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Venkateswara Rao Kagita:
Multi-label classification using hierarchical embedding. Expert Syst. Appl. 91: 263-269 (2018) - [i1]Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita:
Group Preserving Label Embedding for Multi-Label Classification. CoRR abs/1812.09910 (2018) - 2017
- [j6]Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita:
Bounds on skyline probability for databases with uncertain preferences. Int. J. Approx. Reason. 80: 199-213 (2017) - [j5]Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan:
Collaborative filtering using multiple binary maximum margin matrix factorizations. Inf. Sci. 380: 1-11 (2017) - [j4]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Vikas Kumar:
Conformal recommender system. Inf. Sci. 405: 157-174 (2017) - [j3]Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan:
Proximal maximum margin matrix factorization for collaborative filtering. Pattern Recognit. Lett. 86: 62-67 (2017) - 2016
- [c9]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar, Sandeep Kumar Sahu:
Threshold-Based Direct Computation of Skyline Objects for Database with Uncertain Preferences. PRICAI 2016: 193-205 - 2015
- [j2]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan:
Virtual user approach for group recommender systems using precedence relations. Inf. Sci. 294: 15-30 (2015) - [j1]Arun K. Pujari, Venkateswara Rao Kagita, Anubhuti Garg, Vineet Padmanabhan:
Efficient computation for probabilistic skyline over uncertain preferences. Inf. Sci. 324: 146-162 (2015) - [c8]Arun K. Pujari, Venkateswara Rao Kagita, Anubhuti Garg, Vineet Padmanabhan:
Bi-directional Search for Skyline Probability. CALDAM 2015: 250-261 - [c7]Sandeep Kumar Sahu, Arun K. Pujari, Venkateswara Rao Kagita, Vikas Kumar, Vineet Padmanabhan:
GP-SVM: Tree Structured Multiclass SVM with Greedy Partitioning. ICIT 2015: 142-147 - [c6]Venkateswara Rao Kagita, Krishna Charan Meka, Vineet Padmanabhan:
A Novel Social-Choice Strategy for Group Modeling in Recommender Systems. ICIT 2015: 153-158 - [c5]Tadiparthi V. R. Himabindu, Vineet Padmanabhan, Venkateswara Rao Kagita, Arun K. Pujari:
Recommender system algorithms: A comparative analysis based on monotonicity. ICAPR 2015: 1-6 - [c4]Sandeep Kumar Sahu, Arun K. Pujari, Vikas Kumar, Venkateswara Rao Kagita, Vineet Padmanabhan:
Greedy partitioning based tree structured multiclass SVM for Odia OCR. NCVPRIPG 2015: 1-4 - 2014
- [c3]Sowmini Devi V., Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan:
Collaborative filtering by PSO-based MMMF. SMC 2014: 569-574 - 2013
- [c2]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan:
Group Recommender Systems: A Virtual User Approach Based on Precedence Mining. Australasian Conference on Artificial Intelligence 2013: 434-440 - [c1]Venkateswara Rao Kagita, Vineet Padmanabhan, Arun K. Pujari:
Precedence Mining in Group Recommender Systems. PReMI 2013: 701-707
Coauthor Index
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last updated on 2024-08-25 19:11 CEST by the dblp team
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