Search Results for author: Chung Shue Chen

Found 5 papers, 2 papers with code

LLM-Assisted Light: Leveraging Large Language Model Capabilities for Human-Mimetic Traffic Signal Control in Complex Urban Environments

1 code implementation13 Mar 2024 Maonan Wang, Aoyu Pang, Yuheng Kan, Man-on Pun, Chung Shue Chen, Bo Huang

Specifically, a hybrid framework that augments LLMs with a suite of perception and decision-making tools is proposed, facilitating the interrogation of both the static and dynamic traffic information.

Decision Making Language Modelling +3

Experimental Comparison of Ensemble Methods and Time-to-Event Analysis Models Through Integrated Brier Score and Concordance Index

no code implementations12 Mar 2024 Camila Fernandez, Chung Shue Chen, Chen Pierre Gaillard, Alonso Silva

Time-to-event analysis is a branch of statistics that has increased in popularity during the last decades due to its many application fields, such as predictive maintenance, customer churn prediction and population lifetime estimation.

Interference Management in 5G and Beyond Networks

no code implementations3 Jan 2024 Nessrine Trabelsi, Lamia Chaari Fourati, Chung Shue Chen

In order to manage this level of growth and meet these requirements, the fifth-generation (5G) mobile communications network is envisioned as a revolutionary advancement combining various improvements to previous mobile generation networks and new technologies, including the use of millimeter wavebands (mm-wave), massive multiple-input multipleoutput (mMIMO) multi-beam antennas, network densification, dynamic Time Division Duplex (TDD) transmission, and new waveforms with mixed numerologies.

Management

Experimental Comparison of Semi-parametric, Parametric, and Machine Learning Models for Time-to-Event Analysis Through the Concordance Index

1 code implementation13 Mar 2020 Camila Fernandez, Chung Shue Chen, Pierre Gaillard, Alonso Silva

In this paper, we make an experimental comparison of semi-parametric (Cox proportional hazards model, Aalen's additive regression model), parametric (Weibull AFT model), and machine learning models (Random Survival Forest, Gradient Boosting with Cox Proportional Hazards Loss, DeepSurv) through the concordance index on two different datasets (PBC and GBCSG2).

BIG-bench Machine Learning regression

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