Examining and Reducing the Influence of Sampling Errors on Feedback-Driven Optimizations.
Mingzhou ZhouBo WuXipeng ShenYaoqing GaoGraham YiuPublished in: ACM Trans. Archit. Code Optim. (2016)
Keyphrases
- monte carlo
- sampling algorithm
- random sampling
- significantly reduced
- real world
- data mining
- information retrieval
- data driven
- user feedback
- sparse sampling
- power reduction
- main factors
- error propagation
- sampling methods
- individual differences
- factors influencing
- markov chain monte carlo
- estimation error
- database
- recommender systems
- artificial neural networks
- lower bound
- feature selection
- social networks
- real time