Report
Transfer between long-term and short-term memory using Conceptors
| العنوان: | Transfer between long-term and short-term memory using Conceptors |
|---|---|
| المؤلفون: | Strock, Anthony, Rougier, Nicolas, Hinaut, Xavier |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science Nonlinear Sciences Quantitative Biology Statistics |
| مصطلحات موضوعية: | Computer Science - Neural and Evolutionary Computing, Computer Science - Machine Learning, Nonlinear Sciences - Adaptation and Self-Organizing Systems, Quantitative Biology - Neurons and Cognition, Statistics - Machine Learning |
| الوصف: | We introduce a recurrent neural network model of working memory combining short-term and long-term components. e short-term component is modelled using a gated reservoir model that is trained to hold a value from an input stream when a gate signal is on. e long-term component is modelled using conceptors in order to store inner temporal patterns (that corresponds to values). We combine these two components to obtain a model where information can go from long-term memory to short-term memory and vice-versa and we show how standard operations on conceptors allow to combine long-term memories and describe their effect on short-term memory. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2003.11640 |
| رقم الانضمام: | edsarx.2003.11640 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |