1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.IR2024
LiMAML: Personalization of Deep Recommender Models via Meta Learning
Ruofan Wang, Prakruthi Prabhakar, Gaurav Srivastava +10
In the realm of recommender systems, the ubiquitous adoption of deep neural networks has emerged as a dominant paradigm for modeling diverse business objectives. As user bases cont…
cs.LG2023★ 1 cited
Multi-view Sparse Laplacian Eigenmaps for nonlinear Spectral Feature Selection
Gaurav Srivastava, Mahesh Jangid
The complexity of high-dimensional datasets presents significant challenges for machine learning models, including overfitting, computational complexity, and difficulties in interp…