64 citations · 81 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
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…
Probabilistic Matrix Factorization for Automated Machine Learning
Nicolo Fusi, Rishit Sheth, Huseyn Melih Elibol
In order to achieve state-of-the-art performance, modern machine learning techniques require careful data pre-processing and hyperparameter tuning. Moreover, given the ever increas…
Monte Carlo Structured SVI for Two-Level Non-Conjugate Models
Rishit Sheth, Roni Khardon
The stochastic variational inference (SVI) paradigm, which combines variational inference, natural gradients, and stochastic updates, was recently proposed for large-scale data ana…