The Linda model, based on a shared, associative, object memory, through which processes communicate "anonymously," is appropriate (we believe) to a wide range of significant AI applications. In this article we discuss software architectures for data filtering and mining built using Linda.doi:10.1016/B978-0-444-81704-4.50021...
OLAP systems are often used for performing business decisions, data mining, and carrying out complex calculations. Unlike OLTP systems, which act as a single source of truth, OLAP systems use historical data which is out of date. However, OLAP systems will often have additional data that isn’...
有趣的是,SDH项目的所谓data-intensive算法主要是指“machine learning and data science algorithms that process large volumes of data and are characterized by their usage of intense linear algebra, graph search operations and their associated data-transformation operators.”看来这方面的需求确实强劲啊。
Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-...
MiningEmotionsCyberbullying is disturbing and troubling online misconduct. It appears in various forms and is usually in a textual format in most social networks. Intelligent systems are necessary for automated detection of these incidents. Some of the recent experiments have tackled this issue with ...
Since there would be a variable number of available measurement stations at different times, the input graphs would not be the same at different times, but with a variable number of nodes. This was desirable, as it meant that we did not have to discard the data for all stations or ...
- Performance of data processing - Protocols, security and control of data integrity Algorithms, data exploration and knowledge bases - Knowledge bases - Expert systems and artificial intelligence - Data mining and knowledge discovery - Data extraction and data integration ...
Nonetheless, the superiority of transformers compared to CNNs has not been established yet in small datasets, where CNNs can still outperform transformer-based architectures due to the requirement of a large amount of data to exploit the full capacity of this type of architecture. Thus, the ...
Alambda architectureis a scalable, fault-tolerant data-processing architecture that is designed to handle large quantities of data by exploiting both stream and batch processing methods.Data partitioninginvolves physically dividing a dataset into separate data stores on a distributed processing cluster. ...
As such, the property of the tensor to keep the spatial information intact by removing the need to vectorize can be utilized. This helps in reducing the parameter size to a large extent, thus making it possible to learn discriminative models when the amount of training data is less. Pattern...