Minimal Learning Machine: Theoretical Results and Clustering-Based
Reference Point Selection

v1v2 (latest)

Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection

22 September 2019

J. Hämäläinen

Alisson S. C. Alencar

T. Kärkkäinen

C. L. C. Mattos

A. H. S. Júnior

Joao P. P. Gomes

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Papers citing "Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection"

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Title
A review on distance based time series classification A. Abanda U. Mori Jose A. Lozano AI4TS 57 248 0 12 Jun 2018
Scalable Prototype Selection by Genetic Algorithms and Hashing Yenisel Plasencia-Calaña M. Orozco-Alzate Heydi Méndez-Vázquez Edel García-Reyes R. Duin 28 1 0 26 Dec 2017
Randomized Clustered Nystrom for Large-Scale Kernel Machines Farhad Pourkamali Anaraki Stephen Becker 65 33 0 20 Dec 2016
Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations Itay Hubara Matthieu Courbariaux Daniel Soudry Ran El-Yaniv Yoshua Bengio MQ 160 1,870 0 22 Sep 2016
A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm M. E. Celebi H. Kingravi Patricio A. Vela 100 1,124 0 10 Sep 2012
Similarity-based Learning via Data Driven Embeddings Purushottam Kar Prateek Jain FedML 149 38 0 22 Dec 2011