activity
20152022
most citedOnline Adaptive Principal Component Analysis and Its extensions

5 citations · 8 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG2022

Online Convex Optimization with Long Term Constraints for Predictable Sequences

Deepan Muthirayan, Jianjun Yuan, Pramod P. Khargonekar

In this paper, we investigate the framework of Online Convex Optimization (OCO) for online learning. OCO offers a very powerful online learning framework for many applications. In…

math.OC2021

Adaptive Gradient Online Control

Deepan Muthirayan, Jianjun Yuan, Pramod P. Khargonekar

In this work we consider the online control of a known linear dynamic system with adversarial disturbance and adversarial controller cost. The goal in online control is to minimize…

cs.LG2020

Online Convex Optimization in Changing Environments and its Application to Resource Allocation

Jianjun Yuan

In the era of the big data, we create and collect lots of data from all different kinds of sources: the Internet, the sensors, the consumer market, and so on. Many of the data are…

cs.LG2019

Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond

Jianjun Yuan, Andrew Lamperski

Recursive least-squares algorithms often use forgetting factors as a heuristic to adapt to non-stationary data streams. The first contribution of this paper rigorously characterize…

cs.LG20195 cited

Online Adaptive Principal Component Analysis and Its extensions

Jianjun Yuan, Andrew Lamperski

We propose algorithms for online principal component analysis (PCA) and variance minimization for adaptive settings. Previous literature has focused on upper bounding the static ad…

cs.LG2018

Online convex optimization for cumulative constraints

Jianjun Yuan, Andrew Lamperski

We propose the algorithms for online convex optimization which lead to cumulative squared constraint violations of the form ,…