Christopher Quinn — accepted AI-conference papers

2024

Unsupervised Change Point Detection in Multivariate Time Series

Daoping Wu, Suhas Gundimeda, Shaoshuai Mou, Christopher Quinn

AISTATS 2024poster

We consider the challenging problem of unsupervised change point detection in multivariate time series when the number of change points is unknown. Our method eliminates the user’s need for careful parameter tuning, enhancing its practicality and usability. Our approach identifies time series segmen…

Cited by 1 Source ↗PDF ↗Scholar ↗

2023

Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback

Fares Fourati, Vaneet Aggarwal, Christopher Quinn, Mohamed-Slim Alouini

AISTATS 2023poster

We investigate the problem of unconstrained combinatorial multi-armed bandits with full-bandit feedback and stochastic rewards for submodular maximization. Previous works investigate the same problem assuming a submodular and monotone reward function. In this work, we study a more general problem, i…

Cited by 18 Source ↗PDF ↗Scholar ↗