8 papers
A Spectral Boundary for Independence Learnability
Senhan Yao, Yuxin Zhou
Learning independence is fundamental to statistical inference and machine learning, yet learning independence between entire time series by a test remains challenging when only a s…
Strongly Consistent Estimation of the Extended -Sum of -Mixing Coefficients from a Single Trajectory
Senhan Yao
Khaleghi and Lugosi asked whether the sum of the -mixing (uniform-mixing) coefficients of a real-valued discrete-time stationary ergodic process can be consistently estimated fr…
Independence Is Not Always Consistently Testable
Senhan Yao
We study the problem of testing independence between the coordinate processes of a jointly stationary ergodic binary process from finite observations. We prove that no test is poin…
Uniform Testability Implies Asymmetric Testability
Senhan Yao
We prove a filtration-level conversion from uniform fixed-time testing to all-sample one-sided error control and uniform future-tail control. Given an adapted deterministic binary…
Weak but Not Strong Asymptotic Testability
Senhan Yao
We construct two fixed disjoint families of stationary ergodic binary process distributions for which a weakly asymptotically consistent test exists, but no strongly asym…
Invariance Entropy in the Dust
Senhan Yao
We answer negatively two natural general forms of Kawan's questions on invariance entropy for control systems, open for more than fifteen years, by a single construction. We show t…
A Less Conservative Sufficient Condition for PID Stabilization of Scalar Second-Order Nonlinear Uncertain Systems
Senhan Yao
This letter studies robust set-point regulation of scalar second-order nonlinear uncertain systems using a classical PID controller with constant gains. The scalar second-order mod…
On the Fundamental Limit of the Stochastic Gradient Identification Algorithm Under Non-Persistent Excitation
Senhan Yao, Longxu Zhang
Stochastic gradient (SG) methods are fundamental to system identification and machine learning, enabling online parameter estimation in large-scale and streaming-data settings. As…