2 citations · 7 across the 14 of their papers we have counts for
4 papers · 1 filter
Geometric Preference Elicitation for Minimax Regret Optimization in Uncertainty Matroids
Aditya Sai Ellendula, Arun K Pujari, Vikas Kumar +1
This paper presents an efficient preference elicitation framework for uncertain matroid optimization, where precise weight information is unavailable, but insights into possible we…
Inductive Conformal Recommender System
Venkateswara Rao Kagita, Arun K Pujari, Vineet Padmanabhan +1
Traditional recommendation algorithms develop techniques that can help people to choose desirable items. However, in many real-world applications, along with a set of recommendatio…
Block based Singular Value Decomposition approach to matrix factorization for recommender systems
Prasad Bhavana, Vikas Kumar, Vineet Padmanabhan
With the abundance of data in recent years, interesting challenges are posed in the area of recommender systems. Producing high quality recommendations with scalability and perform…
Group Preserving Label Embedding for Multi-Label Classification
Vikas Kumar, Arun K Pujari, Vineet Padmanabhan +1
Multi-label learning is concerned with the classification of data with multiple class labels. This is in contrast to the traditional classification problem where every data instanc…