Results 71 to 80 of about 7,967,373 (246)
Dianxin kexue, 2018 Aiming at prediction of telecom customer churn,a novel method was proposed to increase the prediction accuracy with the missing data based on the Bayesian network.This method used k-nearest neighbor algorithm to fill the missing data and adds two types ...
Yuxiang ZHAO +3 more
doaj
Learning Stable Task Sequences from Demonstration with Linear Parameter Varying Systems and Hidden Markov Models [PDF]
The problem of acquiring multiple tasks from demonstration is typi- cally divided in two sequential processes: (1) the segmentation or identification of different subgoals/subtasks and (2) a separate learning process that parameterizes a control policy ...
Billard, Aude, Medina, Jose R.
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective We aim to comprehensively analyze how regional tumor and edema characteristics are associated with clinical presentations and survival outcomes in a large cohort of glioblastoma patients. Methods Patients with IDH‐wildtype glioblastoma who received brain MRI from 2010 to 2023 were included.
Daniel J. Zhou +16 more
wiley +1 more source
A reaction network scheme for hidden Markov model parameter learning. [PDF]
J R Soc Interface, 2023 Wiuf C +3 more
europepmc +1 more source
Situated Poetry Learning Using Multimedia Resource Sharing Approach
, 2013 [[abstract]]Educators have emphasized the importance of situating students in an authentic learning environment. By using such approach, teachers can encourage students to learn Chinese poems by browsing content resources and relevant online multimedia ...
core
Pengembangan E-Modul Interaktif pada Materi Gelombang Bunyi Berbasis Problem Based Learning [PDF]
This study aims to develop an interactive e-module based on problem-based learning for teaching physics, specifically focusing on sound waves. The research method employed is Research and Development (R&D) utilizing a modified 4D development model ...
Ziveria, Mira +3 more
core +1 more source
Screening Routine Clinical Notes for Epilepsy Surgery Candidates Using Large Language Models
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Epilepsy surgery is severely underutilized despite proven efficacy, with substantial under‐referral of eligible patients in routine clinical practice. This study evaluated the potential role of large language models (LLMs) as decision‐support tools for screening unstructured clinical notes to identify epilepsy surgery candidates and ...
Uriel Fennig +9 more
wiley +1 more source
智能科学与技术学报, 2022 In multi-agent reinforcement learning, parameter sharing can effectively alleviate the inefficiency of learning caused by non-stationarity.However, maintaining the same policy forall agents during learning may have detrimental effects.To solve this ...
Han WANG, Yang YU, Yuan JIANG
doaj
Reinforcement Learning for Ramp Control: An Analysis of Learning Parameters
Promet (Zagreb), 2016 Reinforcement Learning (RL) has been proposed to deal with ramp control problems under dynamic traffic conditions; however, there is a lack of sufficient research on the behaviour and impacts of different learning parameters.
Chao Lu, Jie Huang, Jianwei Gong
doaj +1 more source
Structural Changes in Nonlocal Denoising Models Arising Through Bi-Level Parameter Learning. [PDF]
Appl Math Optim, 2023 Davoli E +3 more
europepmc +1 more source