Results 301 to 310 of about 2,291,078 (312)

Active Sampling for Learning Interpretable Surrogate Machine Learning Models

2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020
The use of machine learning methods to inform consequential decisions is increasingly expanding across many fields. As a result, the ability to interpret these models has become to a greater extent crucial to increase the related-technologies acceptance level and reliability. In this paper, we propose an active sampling approach for learning accurately
Katharina Morik, Amal Saadallah
openaire   +2 more sources

The extreme learning machine learning algorithm with tunable activation function

Neural Computing and Applications, 2012
In this paper, we propose an extreme learning machine (ELM) with tunable activation function (TAF-ELM) learning algorithm, which determines its activation functions dynamically by means of the differential evolution algorithm based on the input data. The main objective is to overcome the problem dependence of fixed slop of the activation function in ...
Xuewen Rong, Bin Li, Yibin Li
openaire   +2 more sources

Improving high-impact bug report prediction with combination of interactive machine learning and active learning

Information and Software Technology, 2021
Xiaoxue Wu, Wei Zheng, Xiang Chen, Yu Zhao, Tingting Yu, Dejun Mu   +5 more
semanticscholar   +1 more source

Spatial-prior generalized fuzziness extreme learning machine autoencoder-based active learning for hyperspectral image classification

, 2020
Muhammad Ahmad, Sidrah Shabbir, D. Oliva, M. Mazzara, Salvatore Distefano   +4 more
semanticscholar   +1 more source

Accelerated discovery of CO2 electrocatalysts using active machine learning

Nature, 2020
M. Zhong, Kevin Tran, Yimeng Min, Chuanhao Wang, Ziyun Wang, C. Dinh, Phil de Luna, Zongqian Yu, A. Rasouli, Peter Brodersen, Song Sun, O. Voznyy, Chih-Shan Tan, M. Askerka, Fanglin Che, Min Liu, A. Seifitokaldani, Y. Pang, S. Lo, Alexander H. Ip, Zachary W. Ulissi, E. Sargent   +21 more
semanticscholar   +1 more source

Active Learning for Improving Machine Learning of Student Explanatory Essays

2018
There is an increasing emphasis, especially in STEM areas, on students’ abilities to create explanatory descriptions. Holistic, overall evaluations of explanations can be performed relatively easily with shallow language processing by humans or computers.
Simon Hughes, M. Anne Britt, Peter Hastings   +2 more
openaire   +1 more source

Sequential active learning using meta-cognitive extreme learning machine

Neurocomputing, 2016
Yong Zhang, M. Er
semanticscholar   +1 more source

Active learning relevant vector machine for reliability analysis

, 2021
T. Z. Li, Q. Pan, Daniel Dias
semanticscholar   +1 more source

Bridging the complexity gap in computational heterogeneous catalysis with machine learning

Nature Catalysis, 2023
Tianyou Mou, H. Pillai, Siwen Wang, Mingyu Wan, Xue Han, Neil M. Schweitzer, Fanglin Che, Hongliang Xin   +7 more
semanticscholar   +1 more source

Machine learning for activity pattern detection

Journal of Intelligent Transportation Systems, 2022
Natalia Selini Hadjidimitriou, Guido Cantelmo, Constantinos Antoniou   +2 more
openaire   +1 more source