3 papers
cs.LG2020
Direct loss minimization algorithms for sparse Gaussian processes
Yadi Wei, Rishit Sheth, Roni Khardon
The paper provides a thorough investigation of Direct loss minimization (DLM), which optimizes the posterior to minimize predictive loss, in sparse Gaussian processes. For the conj…
stat.ML2020
Weighted Meta-Learning
Diana Cai, Rishit Sheth, Lester Mackey +1
Meta-learning leverages related source tasks to learn an initialization that can be quickly fine-tuned to a target task with limited labeled examples. However, many popular meta-le…
stat.ML2019
Feature Gradients: Scalable Feature Selection via Discrete Relaxation
Rishit Sheth, Nicolo Fusi
In this paper we introduce Feature Gradients, a gradient-based search algorithm for feature selection. Our approach extends a recent result on the estimation of learnability in the…