2022

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, and Vikas Kumar. "Inductive Conformal Recommender System." Knowledge-Based Systems (2022).

Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, and Vikas Kumar. "A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data." Information Systems 107 (2022): 102002.

Abhishek Majumder, Joy Lal Sarkar, Bibudhendu Pati, Ramasamy V, Chhabi Rani Panigrahi, Sudipta Roy, Vikas Kumar. "MERIT: Multi-Itinerary Tourist Recommendation Engine for Industrial Internet of Things." A4E, INFOCOM, 2022.

2021

Nitesh Sukhwani, Venkateswara Rao Kagita, Vikas Kumar, and Sanjaya Kumar Panda. "Efficient Computation of Top-K Skyline Objects in Data Set With Uncertain Preferences." International Journal of Data Warehousing and Mining (IJDWM) 17, no. 3 (2021): 68-80.

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Haris Aziz, and Vikas Kumar. "Committee Selection using Attribute Approvals." In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems, pp. 683-691. 2021.

Rasmikanta Pati, Arun K Pujari, Padmavati Gahan, and Vikas Kumar. "Independent Component Analysis: A Review, with Emphasis on Commonly used Algorithms and Contrast Function." Computación y Sistemas 25, no. 1 (2021).

2019

Sowmini Devi Veeramachaneni, Arun K Pujari, Vineet Padmanabhan, and Vikas Kumar. "A maximum margin matrix factorization based transfer learning approach for cross-domain recommendation." Applied Soft Computing 85 (2019): 105751.

Prasad Bhavana, Vikas Kumar, and Vineet Padmanabhan. "Block based singular value decomposition approach to matrix factorization for recommender systems." arXiv preprint arXiv:1907.07410 (2019).

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, and Vikas Kumar. "Skyline recommendation with uncertain preferences." Pattern Recognition Letters 125 (2019): 446-452.

Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, and Venkateswara Rao Kagita. "Group preserving label embedding for multi-label classification." Pattern Recognition 90 (2019): 23-34.

Arun K Pujari, Ansh Mittal, Anshuman Padhi, Anshul Jain, Mukesh Jadon, and Vikas Kumar. "Debiasing gender biased hindi words with word-embedding." In Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence, pp. 450-456. 2019.

Rasmikanta Pati, Vikas Kumar, and Arun K. Pujari. "Gradient-based swarm optimization for ICA." In Progress in Advanced Computing and Intelligent Engineering, pp. 225-235. Springer, Singapore, 2019.

2018

Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, and Venkateswara Rao Kagita. "Multi-label classification using hierarchical embedding." Expert Systems with Applications 91 (2018): 263-269.

2017

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, and Vikas Kumar. "Conformal recommender system." Information Sciences 405 (2017): 157-174.

Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, and Vineet Padmanabhan. "Collaborative filtering using multiple binary maximum margin matrix factorizations." Information Sciences 380 (2017): 1-11.

Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, and Vineet Padmanabhan. "Proximal maximum margin matrix factorization for collaborative filtering." Pattern Recognition Letters 86 (2017): 62-67.

2016

Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar, and Sandeep Kumar Sahu. "Threshold-based direct computation of skyline objects for database with uncertain preferences." In Pacific Rim International Conference on Artificial Intelligence, pp. 193-205. Springer, Cham, 2016.

K. H. Salman, Arun K. Pujari, Vikas Kumar, and Sowmini Devi Veeramachaneni. "Combining swarm with gradient search for maximum margin matrix factorization." In Pacific Rim International Conference on Artificial Intelligence, pp. 167-179. Springer, Cham, 2016.

2015

Sandeep Kumar Sahu, Arun K Pujari, Venkateswara Rao Kagita, Vikas Kumar, and Vineet Padmanabhan. "GP-SVM: Tree structured multiclass SVM with greedy partitioning." In 2015 International Conference on Information Technology (ICIT), pp. 142-147. IEEE, 2015.

Sandeep Kumar Sahu, Arun K Pujari, Vikas Kumar, Venkateswara Rao Kagita, and Vineet Padmanabhan. "Greedy partitioning based tree structured multiclass SVM for Odia OCR." In 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp. 1-4. IEEE, 2015.

1. Project Title: Hybrid Deep Architecture for Semi-Supervised Recommender System
   Project Duration: 2 years
   Funding Agency: Science and Engineering Research Board
   Role: Principal Investigator
   Status: Ongoing
   

   *Soon I will advertise for a Junior Research Fellow (JRF) position.

   
   
2. Project Title: Latent Factor Transfer for Cross-Domain Recommendation
   Project Duration: 2 years
   Funding Agency: University Grants Commission
   Role: Principal Investigator
   Status: Sanctioned
   
   
3. Project Title: Semi-Supervised Recommender System
   Project Duration: 1 year
   Funding Agency: Faculty Research Programme Grant - IoE, University of Delhi
   Role: Principal Investigator
   Status: Ongoing