In this mathematical study, we delve into the realm of statistical inference and introduce a novel approach to variational non-Bayesian inference.
This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Authors: U Jin Choi, Department of mathematical science, Korea Advanced Institute of Science and Technology & ujchoi@kaist.ac.kr; Kyung Soo Rim, Department of mathematics, Sogang University & ksrim@sogang.ac.kr.
Bharath A. Saha and S. Kurtek, A geometric variational approach to bayesian inference, Journal of the American Statistical Association 115 , no. 530, 822–835. P. Alquier and J. Ridgway, Concentration of tempered posteriors and of their variational approximations, The Annals of Statistics 48 , no. 3, 1475–1497. A. R. Barron and C. Sheu, Approximation of density functions by sequences of exponential families, The Annals of Statistics 19 , no. 3, 1347–1369. C. M. Bishop and M. E.
Bharath A. Saha and S. Kurtek, A geometric variational approach to bayesian inference, Journal of the American Statistical Association 115 , no. 530, 822–835. P. Alquier and J. Ridgway, Concentration of tempered posteriors and of their variational approximations, The Annals of Statistics 48 , no. 3, 1475–1497. A. R. Barron and C. Sheu, Approximation of density functions by sequences of exponential families, The Annals of Statistics 19 , no. 3, 1347–1369. C. M. Bishop and M. E.
Philippines Latest News, Philippines Headlines
Similar News:You can also read news stories similar to this one that we have collected from other news sources.
Variational Non-Bayesian Inference: Coefficients From an Ergodic ProcessIn this mathematical study, we delve into the realm of statistical inference and introduce a novel approach to variational non-Bayesian inference.
Read more »
Predictive Power Unleashed by MIT’s Advanced Bayesian OptimizationScience, Space and Technology News 2024
Read more »
Gene trajectory inference for single-cell data by optimal transport metricsSingle-cell RNA sequencing has been widely used to investigate cell state transitions and gene dynamics of biological processes. Current strategies to infer the sequential dynamics of genes in a process typically rely on constructing cell pseudotime through cell trajectory inference.
Read more »
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Conclusion & ReferencesThis paper investigates how the configuration of on-device hardware affects energy consumption for neural network inference with regular fine-tuning.
Read more »
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Predictor AnalysisThis paper investigates how the configuration of on-device hardware affects energy consumption for neural network inference with regular fine-tuning.
Read more »
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices: Architecture OverviewThis paper investigates how the configuration of on-device hardware affects energy consumption for neural network inference with regular fine-tuning.
Read more »