1 citations · 2 across the 4 of their papers we have counts for
4 papers
Quasi-Monte Carlo Beyond Hardy-Krause
Nikhil Bansal, Haotian Jiang
The classical approaches to numerically integrating a function are Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods. MC methods use random samples to evaluate and have…
Learning across Data Owners with Joint Differential Privacy
Yangsibo Huang, Haotian Jiang, Daogao Liu +3
In this paper, we study the setting in which data owners train machine learning models collaboratively under a privacy notion called joint differential privacy [Kearns et al., 2018…
A Brief Survey on the Approximation Theory for Sequence Modelling
Haotian Jiang, Qianxiao Li, Zhong Li +1
We survey current developments in the approximation theory of sequence modelling in machine learning. Particular emphasis is placed on classifying existing results for various mode…
Decomposable Non-Smooth Convex Optimization with Nearly-Linear Gradient Oracle Complexity
Sally Dong, Haotian Jiang, Yin Tat Lee +2
Many fundamental problems in machine learning can be formulated by the convex program \[ \min_{θ\in R^d}\ \sum_{i=1}^{n}f_{i}(θ), \] where each is a convex, Lipschitz functio…