Towards on-node Machine Learning for Ultra-low-power Sensors Using Asynchronous Σ Δ Streams.
Patricia Gonzalez-GuerreroTommy Tracy IIXinfei GuoRahul SreekumarMarzieh LenjaniKevin SkadronMircea R. StanPublished in: ACM J. Emerg. Technol. Comput. Syst. (2020)
Keyphrases
- machine learning
- ultra low power
- real time
- sensed data
- sensor networks
- data streams
- sensor data
- machine learning methods
- natural language processing
- pattern recognition
- data fusion
- active learning
- machine learning algorithms
- machine learning approaches
- text mining
- explanation based learning
- computer science
- computer vision
- statistical methods
- learning tasks
- sliding window
- learning systems
- inductive logic programming
- low power
- knowledge acquisition
- learning algorithm
- information extraction
- support vector machine
- reinforcement learning
- artificial intelligence
- computational intelligence
- leaf nodes
- model selection
- text classification
- mobile robot
- decision trees
- feature selection
- data mining