New learning.

2003

100 citations recorded by the source corpus.

Subfields: Demography, Education, Museology

Citations in the corpus

• Deep learning in neural networks: An overview (2014, neutral): “Many UL methods are designed to maximize entropy-related, i nformation-theoretic (Boltzmann, 1909; Shannon, 1948; Kullback and Leibler, 1951) objectives (e.g ., Linsker, 1988; Barlow et al., 1989; MacKay and Miller, 1990; Plumbley, 1991; Schmidhuber, 1992b,c; Sc hraudolph and Sejnowski, 1993; Redlic”
• Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition (2012, unknown): “Furthermore , the images are grouped by tracks to preserve temporal information , which may be exploited by algorithms that are capable of using privileged information (Vapnik and Vashist, 2009).”