Vikas Kumar

According to our database, Vikas Kumar authored at least 31 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• 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

Citation-Based Summarization of Landmark Judgments.

Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar, Parikshet Sirohi, Ashwini Siwal

CoRR, 2024

Human Centered AI for Indian Legal Text Analytics.

Sudipto Ghosh, Devanshu Verma, Balaji Ganesan, Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar

CoRR, 2024

Infusing Knowledge into Large Language Models with Contextual Prompts.

Kinshuk Vasisht, Balaji Ganesan, Vikas Kumar, Vasudha Bhatnagar

CoRR, 2024

Deep dive into language traits of AI-generated Abstracts.

Vikas Kumar, Amisha Bharti, Devanshu Verma, Vasudha Bhatnagar

Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

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

I Want This, Not That: Personalized Summarization of Scientific Scholarly Texts.

Vasudha Bhatnagar, Alka Khurana, Vikas Kumar

CoRR, 2023

2022

Inductive conformal recommender system.

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

Knowl. Based Syst., 2022

A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data.

Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

Inf. Syst., 2022

Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data.

Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

CoRR, 2022

MERIT: Multi-Itinerary Tourist Recommendation Engine for Industrial Internet of Things.

Abhishek Majumder, Joy Lal Sarkar, Bibudhendu Pati, Chhabi Rani Panigrahi, V. Ramasamy, Sudipta Roy, Vikas Kumar

Proceedings of the IEEE INFOCOM 2022, 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

Independent Component Analysis: A Review, with Emphasis on Commonly used Algorithms and Contrast Function.

Rasmikanta Pati, Arun K. Pujari, Padmavati Gahan, Vikas Kumar

Computación y Sistemas, 2021

A Hinge-Loss based Codebook Transfer for Cross-Domain Recommendation with Nonoverlapping Data.

Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

CoRR, 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

Block based Singular Value Decomposition approach to matrix factorization for recommender systems.

Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan

CoRR, 2019

Committee Selection with Attribute Level Preferences.

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

CoRR, 2019

A Maximum Margin Matrix Factorization based Transfer Learning Approach for Cross-Domain Recommendation.

Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar

Appl. Soft Comput., 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

2016

Combining Swarm with Gradient Search for Maximum Margin Matrix Factorization.

K. H. Salman, Arun K. Pujari, Vikas Kumar, Sowmini Devi Veeramachaneni

Proceedings of the PRICAI 2016: Trends in Artificial Intelligence, 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

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

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