105 citations · 118 across the 13 of their papers we have counts for
14 papers
Task-Aware Multi-Expert Architecture For Lifelong Deep Learning
Jianyu Wang, Jacob Nean-Hua Sheikh, Cat P. Le +1
Lifelong deep learning (LDL) trains neural networks to learn sequentially across tasks while preserving prior knowledge. We propose Task-Aware Multi-Expert (TAME), a continual lear…
FedGTEA: Federated Class-Incremental Learning with Gaussian Task Embedding and Alignment
Haolin Li, Hoda Bidkhori
We introduce a novel framework for Federated Class Incremental Learning, called Federated Gaussian Task Embedding and Alignment (FedGTEA). FedGTEA is designed to capture task-speci…
Robust Quickest Change Detection with Sampling Control
Yingze Hou, Hoda Bidkhori, Taposh Banerjee
The problem of quickest detection of a change in the distribution of a sequence of random variables is studied. The objective is to detect the change with the minimum possible dela…
Robust Quickest Change Detection in Multi-Stream Non-Stationary Processes
Yingze Hou, Hoda Bidkhori, Taposh Banerjee
The problem of robust quickest change detection (QCD) in non-stationary processes under a multi-stream setting is studied. In classical QCD theory, optimal solutions are developed…
Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions
Patrick Kuiper, Ali Hasan, Wenhao Yang +4
The goal of this paper is to develop distributionally robust optimization (DRO) estimators, specifically for multidimensional Extreme Value Theory (EVT) statistics. EVT supports us…
Robust Quickest Change Detection in Non-Stationary Processes
Yingze Hou, Yousef Oleyaeimotlagh, Rahul Mishra +2
Optimal algorithms are developed for robust detection of changes in non-stationary processes. These are processes in which the distribution of the data after change varies with tim…