Vikas Kumar

43 papers A 1B 2Journal 34Unranked 6
YearRankTypeTitle / Venue / Authors
2026 J jnl
DReX: An Explainable Deep Learning-based Multimodal Recommendation Framework.
CoRR
Adamya Shyam, Venkateswara Rao Kagita, Bharti Rana, Vikas Kumar
2026 J jnl
GrIT: Group Informed Transformer for Sequential Recommendation.
CoRR
Adamya Shyam, Venkateswara Rao Kagita, Bharti Rana, Vikas Kumar
2025 J jnl
AugAbEx : Way Forward for Extractive Case Summarization.
CoRR
Purnima Bindal, Vikas Kumar, Sagar Rathore, Vasudha Bhatnagar
2025 J jnl
Cross-domain recommender systems via multimodal domain adaptation.
Comput. Electr. Eng.
Adamya Shyam, Ramya Kamani, Venkateswara Rao Kagita, Vikas Kumar
2025 J jnl
Geometric Preference Elicitation for Minimax Regret Optimization in Uncertainty Matroids.
CoRR
Aditya Sai Ellendula, Arun K. Pujari, Vikas Kumar, Venkateswara Rao Kagita
2025 J jnl
Personalized summarization of scientific scholarly texts.
Expert Syst. Appl.
Alka Khurana, Vasudha Bhatnagar, Vikas Kumar
2024 J jnl
Citation-Based Summarization of Landmark Judgments.
CoRR
Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar, Parikshet Sirohi, Ashwini Siwal
2024 J jnl
Data augmentation and refinement for recommender system: A semi-supervised approach using maximum margin matrix factorization.
Expert Syst. Appl.
Shamal Shaikh, Venkateswara Rao Kagita, Vikas Kumar, Arun K. Pujari
2024 — conf
Deep dive into language traits of AI-generated Abstracts.
COMAD/CODS
Vikas Kumar, Amisha Bharti, Devanshu Verma, Vasudha Bhatnagar
2024 J jnl
Human Centered AI for Indian Legal Text Analytics.
CoRR
Sudipto Ghosh, Devanshu Verma, Balaji Ganesan, Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar
2024 — conf
InLegalLLaMA: Indian Legal Knowledge Enhanced Large Language Model.
LKM@IJCAI
Sudipto Ghosh, Devanshu Verma, Balaji Ganesan, Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar
2024 J jnl
Infusing Knowledge into Large Language Models with Contextual Prompts.
CoRR
Kinshuk Vasisht, Balaji Ganesan, Vikas Kumar, Vasudha Bhatnagar
2024 J jnl
UniRecSys: A unified framework for personalized, group, package, and package-to-group recommendations.
Knowl. Based Syst.
Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita, Arun K. Pujari
2024 — conf
gCDR: A Group Aided Cross-Domain Recommendation Framework.
BDA
Adamya Shyam, Kavita Kanwar, Vikas Kumar, Venkateswara Rao Kagita
2023 J jnl
Conformal Group Recommender System.
CoRR
Venkateswara Rao Kagita, Anshuman Singh, Vikas Kumar, Pavan Kalyan Reddy Neerudu, Arun K. Pujari, Rohit Kumar Bondugula
2023 J jnl
Cross-domain Recommender Systems via Multimodal Domain Adaptation.
CoRR
Ramya Kamani, Vikas Kumar, Venkateswara Rao Kagita
2023 J jnl
Data augmentation for recommender system: A semi-supervised approach using maximum margin matrix factorization.
CoRR
Shamal Shaikh, Venkateswara Rao Kagita, Vikas Kumar, Arun K. Pujari
2023 J jnl
Deep dive into language traits of AI-generated Abstracts.
CoRR
Vikas Kumar, Amisha Bharti, Devanshu Verma, Vasudha Bhatnagar
2023 J jnl
I Want This, Not That: Personalized Summarization of Scientific Scholarly Texts.
CoRR
Vasudha Bhatnagar, Alka Khurana, Vikas Kumar
2023 J jnl
UniRecSys: A Unified Framework for Personalized, Group, Package, and Package-to-Group Recommendations.
CoRR
Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita, Arun K. Pujari
2022 J jnl
A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data.
Inf. Syst.
Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2022 J jnl
Inductive conformal recommender system.
Knowl. Based Syst.
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2022 — conf
MERIT: Multi-Itinerary Tourist Recommendation Engine for Industrial Internet of Things.
INFOCOM Workshops
Abhishek Majumder, Joy Lal Sarkar, Bibudhendu Pati, Chhabi Rani Panigrahi, V. Ramasamy, Sudipta Roy, Vikas Kumar
2022 J jnl
Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data.
CoRR
Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2021 J jnl
A Hinge-Loss based Codebook Transfer for Cross-Domain Recommendation with Nonoverlapping Data.
CoRR
Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2021 A conf
Committee Selection using Attribute Approvals.
AAMAS
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Haris Aziz, Vikas Kumar
2021 J jnl
Efficient Computation of Top-K Skyline Objects in Data Set With Uncertain Preferences.
Int. J. Data Warehous. Min.
Nitesh Sukhwani, Venkateswara Rao Kagita, Vikas Kumar, Sanjaya Kumar Panda
2021 J jnl
Independent Component Analysis: A Review, with Emphasis on Commonly used Algorithms and Contrast Function.
Computación y Sistemas
Rasmikanta Pati, Arun K. Pujari, Padmavati Gahan, Vikas Kumar
2021 J jnl
Inductive Conformal Recommender System.
CoRR
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2019 J jnl
A Maximum Margin Matrix Factorization based Transfer Learning Approach for Cross-Domain Recommendation.
Appl. Soft Comput.
Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2019 J jnl
Block based Singular Value Decomposition approach to matrix factorization for recommender systems.
CoRR
Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan
2019 J jnl
Committee Selection with Attribute Level Preferences.
CoRR
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2019 J jnl
Group preserving label embedding for multi-label classification.
Pattern Recognit.
Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita
2019 J jnl
Skyline recommendation with uncertain preferences.
Pattern Recognit. Lett.
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar
2018 J jnl
Group Preserving Label Embedding for Multi-Label Classification.
CoRR
Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita
2018 J jnl
Multi-label classification using hierarchical embedding.
Expert Syst. Appl.
Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Venkateswara Rao Kagita
2017 J jnl
Collaborative filtering using multiple binary maximum margin matrix factorizations.
Inf. Sci.
Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan
2017 J jnl
Conformal recommender system.
Inf. Sci.
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Vikas Kumar
2017 J jnl
Proximal maximum margin matrix factorization for collaborative filtering.
Pattern Recognit. Lett.
Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan
2016 B conf
Combining Swarm with Gradient Search for Maximum Margin Matrix Factorization.
PRICAI
K. H. Salman, Arun K. Pujari, Vikas Kumar, Sowmini Devi Veeramachaneni
2016 B conf
Threshold-Based Direct Computation of Skyline Objects for Database with Uncertain Preferences.
PRICAI
Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar, Sandeep Kumar Sahu
2015 — conf
GP-SVM: Tree Structured Multiclass SVM with Greedy Partitioning.
ICIT
Sandeep Kumar Sahu, Arun K. Pujari, Venkateswara Rao Kagita, Vikas Kumar, Vineet Padmanabhan
2015 — conf
Greedy partitioning based tree structured multiclass SVM for Odia OCR.
NCVPRIPG
Sandeep Kumar Sahu, Arun K. Pujari, Vikas Kumar, Venkateswara Rao Kagita, Vineet Padmanabhan