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Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance

Journal of machine learning research, 2010
Information theoretic measures form a fundamental class of measures for comparing clusterings, and have recently received increasing interest. Nevertheless, a number of questions concerning their properties and inter-relationships remain unresolved.
X. Nguyen, J. Epps, J. Bailey
semanticscholar +1 more source

Root Mean Square Layer Normalization

Neural Information Processing Systems, 2019
Layer normalization (LayerNorm) has been successfully applied to various deep neural networks to help stabilize training and boost model convergence because of its capability in handling re-centering and re-scaling of both inputs and weight matrix ...
Biao Zhang, Rico Sennrich
semanticscholar +1 more source

Normalization

Ever Looser Union?, 2020
Focusing on the 2004 and 2007 Eastern enlargement of the European Union, this chapter traces the ‘normalization’ of differentiated integration after new countries become member states. The chapter explains pre-accession tensions between demands of member
F. Schimmelfennig, Thomas Winzen
semanticscholar +1 more source

Advanced Normalization Tools (ANTs)

, 2020
B. Avants, N. Tustison, Hans J. Johnson
semanticscholar +1 more source

Normalization of Tumor Vasculature: An Emerging Concept in Antiangiogenic Therapy

Science, 2005
R. Jain
semanticscholar +1 more source

Investigating the impact of data normalization on classification performance

Applied Soft Computing, 2020
Dalwinder Singh, Birmohan Singh
semanticscholar +1 more source

Dropout vs. batch normalization: an empirical study of their impact to deep learning