Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

Subjects: “…AutoML…”
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Imaging Estimation for Liver Damage Using Automated Approach Based on Genetic Programming by David Herrera-Sánchez, Héctor-Gabriel Acosta-Mesa, Efrén Mezura-Montes, Socorro Herrera-Meza, Eduardo Rivadeneyra-Domínguez, Isaac Zamora-Bello, María Fernanda Almanza-Domínguez

Subjects: “…AutoML…”
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A Supervised Machine Learning-Based Approach for Task Workload Prediction in Manufacturing: A Case Study Application by Valentina De Simone, Valentina Di Pasquale, Joanna Calabrese, Salvatore Miranda, Raffaele Iannone

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Optimizing Knowledge Transfer Graph for Deep Collaborative Learning by Soma Minami, Naoki Okamoto, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi

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Enhancing Office Comfort with Personal Comfort Systems: A Data-Driven Machine Learning Approach by Paulina Wegertseder-Martinez, Silvia E. Restrepo-Medina, Roberto Aedo-García, Raul Soto-Concha

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A Pipeline for Multivariate Time Series Forecasting of Gas Consumption in Pelletization Process by Thadeu Pezzin Melo, Jefferson Andrade, Karin Satie Komati

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Automated reinforcement learning for sequential ordering problem using hyperparameter optimization and metalearning by André Luiz Carvalho Ottoni

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Distilling Diverse Knowledge for Deep Ensemble Learning by Naoki Okamoto, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi

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An Interpretable and Generalizable Machine Learning Model for Predicting Asthma Outcomes: Integrating AutoML and Explainable AI Techniques by Salman Mahmood, Raza Hasan, Saqib Hussain, Rochak Adhikari

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A practical evaluation of AutoML tools for binary, multiclass, and multilabel classification by Marcelo V. C. Aragão, Augusto G. Afonso, Rafaela C. Ferraz, Rairon G. Ferreira, Sávio G. Leite, Felipe A. P. de Figueiredo, Samuel B. Mafra

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NiaAutoARM: Automated Framework for Constructing and Evaluating Association Rule Mining Pipelines by Uroš Mlakar, Iztok Fister, Iztok Fister

Subjects: “…AutoML…”
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Estimating vegetation indices and biophysical parameters for Central European temperate forests with Sentinel-1 SAR data and machine learning by Daniel Paluba, Bertrand Le Saux, Francesco Sarti, Přemysl Štych

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New hybrid features extracted from US images for breast cancer classification by Gigi Tăbăcaru, Simona Moldovanu, Dan Munteanu, Marian Barbu

Subjects: “…AutoML…”
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Lashing Force Prediction Model with Multimodal Deep Learning and AutoML for Stowage Planning Automation in Containerships by Chaemin Lee, Mun Keong Lee, Jae Young Shin

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Unbiased High-Precision Cloud Detection for Advanced Himawari Imager Using Automatic Machine Learning by Bochun Liu, Jinming Ge, Qingyu Mu, Chi Zhang, Xiaoyu Hu, Jiajing Du, Yanyan Wu, Bo Wang, Xiang Li, Jianping Huang, Qiang Fu

Subjects: “…Automatic machine learning (AutoML)…”
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Enhancing cerebral infarct classification by automatically extracting relevant fMRI features by Vitaly I. Dobromyslin, Wenjin Zhou, for the Alzheimer’s Disease Neuroimaging Initiative

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AutoML: A systematic review on automated machine learning with neural architecture search by Imrus Salehin, Md. Shamiul Islam, Pritom Saha, S.M. Noman, Azra Tuni, Md. Mehedi Hasan, Md. Abu Baten

Subjects: “…AutoML…”
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Automated Exploratory Clustering to Democratize Clustering Analysis by Georg Stefan Schlake, Max Pernklau, Christian Beecks

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El Rol de la Inteligencia Artificial en la Ciencia de Datos: Perspectivas Teóricas y Desafíos Emergentes by Anthony JeanPaul Reyes Risco, Juan Aurelio De La Cruz Gamarra, Marcelino Torres Villanueva

Subjects: “…AutoML…”
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Understanding the Role of Diversity in Ensemble-Based AutoML Methods for Classification Tasks by Salomey Osei, Andres R. Masegosa, Antonio D. Masegosa

Subjects: “…Automated machine learning (AutoML)…”
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