Results 91 to 100 of about 741,105 (343)

TreeGrad: Transferring Tree Ensembles to Neural Networks

, 2019
Gradient Boosting Decision Tree (GBDT) are popular machine learning algorithms with implementations such as LightGBM and in popular machine learning toolkits like Scikit-Learn.
C Siu, DH Wolpert, F Pedregosa, JA Blackard, JH Friedman, K Nakai, L Breiman, SK Murthy   +7 more
core   +1 more source

Naturally Derived Donor‐π‐Acceptor Compounds for Efficient Long‐Wavelength LEDs/Sunlight‐Induced Polymerization and High‐Precision Multiple 3D Printing

Advanced Functional Materials, EarlyView.
Two novel donor–π–acceptor photoinitiators enable ultrafast long‐wavelength photopolymerization under blue/green LEDs and sunlight. Effective at low intensities and concentrations, they overcome slow kinetics and permit rapid 3D printing via DLW, DLP, and LCD methods.
Ji Feng, Tong Gao, Fabrice Morlet‐Savary, Michael Schmitt, Céline Dietlin, Jing Zhang, Pu Xiao, Frédéric Dumur, Jean‐Patrick Joly, Jacques Lalevée   +9 more
wiley   +1 more source

A case of in-streaming-learning: how to program with Z-tree software to design experiments on economic decision making

Eduser, 2019
In this paper, we present a real in-streaming case of learning about how to program with the z-tree software to design experiments on economic decision making for the members of the NECE Research Unit in Business Sciences, in Portugal.This
Nuria Hernández-León, Ricardo Rodrigues, Mario Diogo   +2 more
doaj   +1 more source

Global Evaluation for Decision Tree Learning

, 2022
We transfer distances on clusterings to the building process of decision trees, and as a consequence extend the classical ID3 algorithm to perform modifications based on the global distance of the tree to the ground truth--instead of considering single leaves.
Spaeh, Fabian, Kosub, Sven
openaire   +2 more sources

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery

Heliyon
Objective: By constructing a predictive model using machine learning and deep learning technologies, we aim to understand the risk factors for postoperative intestinal obstruction in laparoscopic colorectal cancer patients, and establish an effective ...
Cheng-Mao Zhou, HuiJuan Li, Qiong Xue, Jian-Jun Yang, Yu Zhu   +4 more
doaj   +1 more source

Digital Discovery of Synthesizable Metal−Organic Frameworks via Molecular Dynamics‑Informed, High‑Fidelity Deep Learning

Advanced Functional Materials, EarlyView.
Tabular foundation model interrogates the synthetic likelihood of metal−organic frameworks. Abstract Metal–organic frameworks (MOFs) are celebrated for their chemical and structural versatility, and in‑silico screening has significantly accelerated their discovery; yet most hypothetical MOFs (hMOFs) never reach the bench because their synthetic ...
Xiaoyu Wu, Rui Zheng, Quan Liu, Jianwen Jiang   +3 more
wiley   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Electron–Matter Interactions During Electron Beam Nanopatterning

Advanced Functional Materials, EarlyView.
This article reviews the electron–matter interactions important to nanopatterning with electron beam lithography (EBL). Electron–matter interactions, including secondary electron generation routes, polymer radiolysis, and electron beam induced charging, are discussed.
Camila Faccini de Lima, Prathiba Thamizhavel, Taylor J. Woehl   +2 more
wiley   +1 more source

Learning Optimal Dynamic Treatment Regime from Observational Clinical Data through Reinforcement Learning

Machine Learning and Knowledge Extraction
In medicine, dynamic treatment regimes (DTRs) have emerged to guide personalized treatment decisions for patients, accounting for their unique characteristics. However, existing methods for determining optimal DTRs face limitations, often due to reliance
Seyum Abebe, Irene Poli, Roger D. Jones, Debora Slanzi   +3 more
doaj   +1 more source