Approaching Globally Optimal Energy Efficiency in Interference Networks via Machine Learning.
Bile PengKarl-Ludwig BesserRamprasad RaghunathEduard A. JorswieckPublished in: CoRR (2022)
Keyphrases
- globally optimal
- energy efficiency
- machine learning
- power consumption
- energy consumption
- wireless sensor networks
- data center
- packet delivery
- energy efficient
- sensor networks
- graph cuts
- energy saving
- response time
- power saving
- locally optimal
- energy conservation
- routing protocol
- power management
- energy management
- optimal decisions
- multipath
- energy aware
- smart home
- reinforcement learning
- computer vision
- traffic load
- surface segmentation
- sensor nodes
- global optimality
- data sets
- active learning
- mobile nodes
- data mining
- data transmission
- network structure
- expert systems
- semi supervised learning
- text classification
- markov random field
- network resources
- network connectivity
- computer networks
- database systems
- activity recognition
- query processing