Reliable edge machine learning hardware for scientific applications.
Tommaso BaldiJavier CamposBenjamin HawksJennifer NgadiubaNhan TranDaniel DiazJavier M. DuarteRyan KastnerAndres MezaMelissa QuinnanOlivia WengCaleb GeniesseAmir GholamiMichael W. MahoneyVladimir LoncarPhilip C. HarrisJoshua AgarShuyu QinPublished in: CoRR (2024)
Keyphrases
- machine learning
- hardware and software
- low cost
- edge information
- edge detection
- inductive learning
- decision trees
- natural language processing
- learning tasks
- machine learning methods
- machine learning algorithms
- text classification
- scientific data
- real time
- weighted graph
- feature selection
- computer vision
- active learning
- information extraction
- text mining
- neural network
- machine learning approaches
- artificial intelligence
- learning algorithm
- cost effective
- vlsi implementation
- computing power
- data sets
- embedded systems
- explanation based learning
- edge map
- hardware implementation
- learning problems
- data types
- pattern recognition
- image processing
- learning systems
- data analysis
- computer science
- data structure
- reinforcement learning
- information systems
- multiple scales
- high end
- data mining
- parallel hardware