Evolution Of Activation Functions for Neural Architecture Search
The introduction of the ReLU function in neural network architectures yielded substantial improvements over sigmoidal activation functions and allowed for the training of deep networks. Ever since, the search for new activation functions in neural networks has been an active research topic. However,...
محفوظ في:
| المؤلف الرئيسي: | Nader, Andrew (author) |
|---|---|
| التنسيق: | masterThesis |
| منشور في: |
2020
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/10725/13847 https://doi.org/10.26756/th.2022.373 http://libraries.lau.edu.lb/research/laur/terms-of-use/thesis.php |
| الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Modeling Software System Interactions Using Temporal Graphs and Graph Neural Networks
حسب: Germanos, Manuella
منشور في: (2022) -
A low degree vertex elimination with high degree vertex selection heuristic for strongly connected dominating and absorbent sets in wireless Ad-Hoc networks. (c2011)
حسب: Markarian, Christine Hovsep
منشور في: (2016) -
A memristive all-inclusive hypernetwork for parallel analog deployment of full search space architectures
حسب: Bo Lyu (16522643)
منشور في: (2024) -
On Single Source Reachability Improvement
حسب: Alkak, Hashem
منشور في: (2022) -
An Adapted Load-Balancing implementation for Sharded Blockchains
حسب: Daou, David Halim
منشور في: (2024)