Topics in Approximate Inference
نویسنده
چکیده
This monograph provides a brief introduction on approximate inference and goes in depth for a selected list of related topics. Many of the presented materials are adapted from my published papers, my research notes during PhD, and my (draft) PhD thesis. I expect to keep updating this list of topics to include new techniques.
منابع مشابه
Accurate Inference for the Mean of the Poisson-Exponential Distribution
Although the random sum distribution has been well-studied in probability theory, inference for the mean of such distribution is very limited in the literature. In this paper, two approaches are proposed to obtain inference for the mean of the Poisson-Exponential distribution. Both proposed approaches require the log-likelihood function of the Poisson-Exponential distribution, but the exact for...
متن کاملApproximate additive and quadratic mappings in 2-Banach spaces and related topics
Won{Gil Park [Won{Gil Park, J. Math. Anal. Appl., 376 (1) (2011) 193{202] proved the Hyers{Ulam stability of the Cauchy functional equation, the Jensen functional equation and the quadraticfunctional equation in 2{Banach spaces. One can easily see that all results of this paper are incorrect.Hence the control functions in all theorems of this paper are not correct. In this paper, we correctthes...
متن کاملEvaluation of the Efficiency of the Adaptive Neuro Fuzzy Inference System (ANFIS) in the Modeling of the Ionosphere Total Electron Content Time Series Case Study: Tehran Permanent GPS Station
Global positioning system (GPS) measurements provide accurate and continuous 3-dimensional position, velocity and time data anywhere on or above the surface of the earth, anytime, and in all weather conditions. However, the predominant ranging error source for GPS signals is an ionospheric error. The ionosphere is the region of the atmosphere from about 60 km to more than 1500 km above the eart...
متن کاملRelative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on approximate posterior inference methods such as variational inference or Gibbs sampling. There has been much research in designing better approximations, but there is yet little theoretical understanding of which of t...
متن کاملLow-dimensional Embeddings for Interpretable Anchor-based Topic Inference
The anchor words algorithm performs provably efficient topic model inference by finding an approximate convex hull in a high-dimensional word co-occurrence space. However, the existing greedy algorithm often selects poor anchor words, reducing topic quality and interpretability. Rather than finding an approximate convex hull in a high-dimensional space, we propose to find an exact convex hull i...
متن کامل