Memorization and Association on a Realistic Neural Model
نویسندگان
چکیده
منابع مشابه
Memorization and Association on a Realistic Neural Model
A central open question of computational neuroscience is to identify the data structures and algorithms that are used in mammalian cortex to support successive acts of the basic cognitive tasks of memorization and association. This letter addresses the simultaneous challenges of realizing these two distinct tasks with the same data structure, and doing so while respecting the following four bas...
متن کاملAdaptive self-organization in a realistic neural network model.
Information processing in complex systems is often found to be maximally efficient close to critical states associated with phase transitions. It is therefore conceivable that also neural information processing operates close to criticality. This is further supported by the observation of power-law distributions, which are a hallmark of phase transitions. An important open question is how neura...
متن کاملA Fuzzy Realistic Mobility Model for Ad hoc Networks
Realistic mobility models can demonstrate more precise evaluation results because their parameters are closer to the reality. In this paper a realistic Fuzzy Mobility Model has been proposed. This model has rules which are changeable depending on nodes and environmental conditions. It seems that this model is more complete than other mobility models.After simulation, it was found out that not o...
متن کاملa study on insurer solvency by panel data model: the case of iranian insurance market
the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.
The Secret Sharer: Measuring Unintended Neural Network Memorization & Extracting Secrets
Machine learning models based on neural networks and deep learning are being rapidly adopted for many purposes. What those models learn, and what they may share, is a significant concern when the training data may contain secrets and the models are public—e.g., when a model helps users compose text messages using models trained on all users’ messages. This paper presents exposure, a simple-to-c...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Computation
سال: 2005
ISSN: 0899-7667,1530-888X
DOI: 10.1162/0899766053019890