Learning-augmented Online Algorithm for Two-level Ski-rental Problem

1 code implementation • 9 Feb 2024 • Keyuan Zhang, Zhongdong Liu, Nakjung Choi, Bo Ji

In this paper, we study the two-level ski-rental problem, where a user needs to fulfill a sequence of demands for multiple items by choosing one of the three payment options: paying for the on-demand usage (i. e., rent), buying individual items (i. e., single purchase), and buying all the items (i. e., combo purchase).

Atlas: Automate Online Service Configuration in Network Slicing

1 code implementation • 30 Oct 2022 • Qiang Liu, Nakjung Choi, Tao Han

First, we design a learning-based simulator to reduce the sim-to-real discrepancy, which is accomplished by a new parameter searching method based on Bayesian optimization.

Bayesian Optimization Safe Exploration +1

Regenerative Particle Thompson Sampling

no code implementations • 15 Mar 2022 • Zeyu Zhou, Bruce Hajek, Nakjung Choi, Anwar Walid

Particle Thompson sampling (PTS) is an approximation of Thompson sampling obtained by simply replacing the continuous distribution by a discrete distribution supported at a set of weighted static particles.

Thompson Sampling

OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning

no code implementations • 2 Nov 2021 • Qiang Liu, Nakjung Choi, Tao Han

As online learning is converged, OnSlicing reduces 12. 5% usage without any violations as compared to the state-of-the-art online DRL solution.

reinforcement-learning Reinforcement Learning (RL)