40 citations · 63 across the 7 of their papers we have counts for
7 papers
Cellular Automata: From Structural Principles to Transport and Correlation Methods
Mihir Metkar, Neha Sah, Yichen Zhou
Cellular automata (CA) are discrete-time dynamical systems with local update rules on a lattice. Despite their elementary definition, CA support a wide spectrum of macroscopic phen…
Nearly Instance-Optimal Parameter Recovery from Many Trajectories via Hellinger Localization
Eliot Shekhtman, Yichen Zhou, Ingvar Ziemann +2
Learning from temporally-correlated data is a core facet of modern machine learning. Yet our understanding of sequential learning remains incomplete, particularly in the multi-traj…
Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction
Yicheng Zhou, Pengfei Wang, Hao Dong +4
Urban traffic speed prediction aims to estimate the future traffic speed for improving urban transportation services. Enormous efforts have been made to exploit Graph Neural Networ…
Tree Boosted Varying Coefficient Models
Yichen Zhou, Giles Hooker
This paper investigates the integration of gradient boosted decision trees and varying coefficient models. We introduce the tree boosted varying coefficient framework which justifi…
Approximation Trees: Statistical Stability in Model Distillation
Yichen Zhou, Zhengze Zhou, Giles Hooker
This paper examines the stability of learned explanations for black-box predictions via model distillation with decision trees. One approach to intelligibility in machine learning…
Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution
Yichen Zhou, Giles Hooker
This paper examines a novel gradient boosting framework for regression. We regularize gradient boosted trees by introducing subsampling and employ a modified shrinkage algorithm so…