59 citations · 220 across the 28 of their papers we have counts for
5 papers · 1 filter
Online Learning of Optimal Sequential Testing Policies
Qiyuan Chen, Raed Al Kontar
This paper studies an online learning problem that seeks optimal testing policies for a stream of subjects, each of whom can be evaluated through a sequence of candidate tests draw…
ALBATROSS: Cheap Filtration Based Geometry via Stochastic Sub-Sampling
Andrew J. Stier, Naichen Shi, Raed Al Kontar +2
Topological data analysis (TDA) detects geometric structure in biological data. However, many TDA algorithms are memory intensive and impractical for massive datasets. Here, we int…
A Collaborative Process Parameter Recommender System for Fleets of Networked Manufacturing Machines -- with Application to 3D Printing
Weishi Wang, Sicong Guo, Chenhuan Jiang +5
Fleets of networked manufacturing machines of the same type, that are collocated or geographically distributed, are growing in popularity. An excellent example is the rise of 3D pr…
Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language Models
Haoyi Song, Ruihan Ji, Naichen Shi +2
Large language models (LLMs) have transformed natural language processing, but their reliable deployment requires effective uncertainty quantification (UQ). Existing UQ methods are…
LLINBO: Trustworthy LLM-in-the-Loop Bayesian Optimization
Chih-Yu Chang, Milad Azvar, Chinedum Okwudire +1
Bayesian optimization (BO) is a sequential decision-making tool widely used for optimizing expensive black-box functions. Recently, Large Language Models (LLMs) have shown remarkab…