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ORCIDVikas Kumar 0003
Person information
- affiliation: University of Delhi, New Delhi, India
- affiliation (PhD 2019): University of Hyderabad, India
Other persons with the same name
- Vikas Kumar — disambiguation page
- Vikas Kumar 0001
![[0000-0002-8062-7123]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-8062-7123")
— University of the West of England, Bristol Business School, UK (and 3 more) - Vikas Kumar 0002 — DA-IICT Gandhinagar, India
- Vikas Kumar 0004 — Universitat Rovira i Virgili, Department of Chemical Engineering, Tarragona, Spain
- Vikas Kumar 0005 — Sharda University, School of Business Studies, Greater Noida, India
- Vikas Kumar 0006 — Lovely Professional University, Department of Food Technology and Nutrition, Jalandhar, India (and 1 more)
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2020 – today
- 2024
[j12]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)- [c7]Vikas Kumar, Amisha Bharti, Devanshu Verma, Vasudha Bhatnagar:
Deep dive into language traits of AI-generated Abstracts. COMAD/CODS 2024: 237-241 - [i14]Kinshuk Vasisht, Balaji Ganesan, Vikas Kumar, Vasudha Bhatnagar:
Infusing Knowledge into Large Language Models with Contextual Prompts. CoRR abs/2403.01481 (2024) - [i13]Sudipto Ghosh, Devanshu Verma, Balaji Ganesan, Purnima Bindal, Vikas Kumar, Vasudha Bhatnagar:
Human Centered AI for Indian Legal Text Analytics. CoRR abs/2403.10944 (2024) - 2023
- [i12]Vasudha Bhatnagar, Alka Khurana, Vikas Kumar:
I Want This, Not That: Personalized Summarization of Scientific Scholarly Texts. CoRR abs/2306.09604 (2023) - [i11]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) - [i10]Ramya Kamani, Vikas Kumar, Venkateswara Rao Kagita:
Cross-domain Recommender Systems via Multimodal Domain Adaptation. CoRR abs/2306.13887 (2023) - [i9]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) - [i8]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) - [i7]Vikas Kumar, Amisha Bharti, Devanshu Verma, Vasudha Bhatnagar:
Deep dive into language traits of AI-generated Abstracts. CoRR abs/2312.10617 (2023) - 2022
- [j11]Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data. Inf. Syst. 107: 102002 (2022) - [j10]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Inductive conformal recommender system. Knowl. Based Syst. 250: 109108 (2022) - [c6]Abhishek Majumder, Joy Lal Sarkar, Bibudhendu Pati, Chhabi Rani Panigrahi, V. Ramasamy, Sudipta Roy, Vikas Kumar:
MERIT: Multi-Itinerary Tourist Recommendation Engine for Industrial Internet of Things. INFOCOM Workshops 2022: 1-6 - [i6]Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data. CoRR abs/2203.13995 (2022) - 2021
- [j9]Rasmikanta Pati, Arun K. Pujari, Padmavati Gahan, Vikas Kumar:
Independent Component Analysis: A Review, with Emphasis on Commonly used Algorithms and Contrast Function. Computación y Sistemas 25(1) (2021) - [j8]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) - [c5]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Haris Aziz, Vikas Kumar:
Committee Selection using Attribute Approvals. AAMAS 2021: 683-691 - [i5]Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
A Hinge-Loss based Codebook Transfer for Cross-Domain Recommendation with Nonoverlapping Data. CoRR abs/2108.01473 (2021) - [i4]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Inductive Conformal Recommender System. CoRR abs/2109.08949 (2021)
2010 – 2019
- 2019
- [j7]Sowmini Devi Veeramachaneni, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
A Maximum Margin Matrix Factorization based Transfer Learning Approach for Cross-Domain Recommendation. Appl. Soft Comput. 85 (2019) - [j6]Vikas Kumar, Arun K. Pujari, Vineet Padmanabhan, Venkateswara Rao Kagita:
Group preserving label embedding for multi-label classification. Pattern Recognit. 90: 23-34 (2019) - [j5]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Skyline recommendation with uncertain preferences. Pattern Recognit. Lett. 125: 446-452 (2019) - [i3]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Vikas Kumar:
Committee Selection with Attribute Level Preferences. CoRR abs/1901.10064 (2019) - [i2]Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan:
Block based Singular Value Decomposition approach to matrix factorization for recommender systems. CoRR abs/1907.07410 (2019) - 2018
- [j4]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
- [j3]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) - [j2]Venkateswara Rao Kagita, Arun K. Pujari, Vineet Padmanabhan, Sandeep Kumar Sahu, Vikas Kumar:
Conformal recommender system. Inf. Sci. 405: 157-174 (2017) - [j1]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
- [c4]K. H. Salman, Arun K. Pujari, Vikas Kumar, Sowmini Devi Veeramachaneni:
Combining Swarm with Gradient Search for Maximum Margin Matrix Factorization. PRICAI 2016: 167-179 - [c3]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
- [c2]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 - [c1]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
Coauthor Index
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last updated on 2024-04-09 20:39 CEST by the dblp team
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