activity
20172026
most citedIs Simple Better? Revisiting Non-linear Matrix Factorization for Learning Incomplete Ratings

9 citations · 9 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SI2026

Modeling Duelling Contagions of True and False Information in the Face of Inherent Individual biases

Vaibhav Krishna, Hirokazu Shirado, Feng Fu +1

Advanced digital communication has revolutionized how people create and consume information, making information diffusion an important topic of research for domains from public hea…

cs.SI2025

Countering the Forgetting of Novel Health Information with 'Social Boosting'

Vaibhav Krishna, Nicholas A. Christakis

To mitigate the adverse effects of low-quality or false information, studies have shown the effectiveness of various intervention techniques through debunking or so-called pre-bunk…

cs.IR2022

Simplifying Sparse Expert Recommendation by Revisiting Graph Diffusion

Vaibhav Krishna, Nino Antulov-Fantulin

Community Question Answering (CQA) websites have become valuable knowledge repositories where individuals exchange information by asking and answering questions. With an ever-incre…

cs.SI2022

Topic Community Based Temporal Expertise for Question Routing

Vaibhav Krishna, Vaiva Vasiliauskaite, Nino Antulov-Fantulin

Question Routing in Community-based Question Answering websites aims at recommending newly posted questions to potential users who are most likely to provide "accepted answers". Mo…

cs.LG2020

Augmenting Organizational Decision-Making with Deep Learning Algorithms: Principles, Promises, and Challenges

Yash Raj Shrestha, Vaibhav Krishna, Georg von Krogh

The current expansion of theory and research on artificial intelligence in management and organization studies has revitalized the theory and research on decision-making in organiz…

cs.LG2017★ 9 cited

Is Simple Better? Revisiting Non-linear Matrix Factorization for Learning Incomplete Ratings

Vaibhav Krishna, Tian Guo, Nino Antulov-Fantulin

Matrix factorization techniques have been widely used as a method for collaborative filtering for recommender systems. In recent times, different variants of deep learning algorith…