| LDR | | 02537nam u200409 4500 |
| 001 | | 000000418983 |
| 005 | | 20190215163318 |
| 008 | | 181129s2017 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438122178 |
| 035 | |
▼a (MiAaPQ)AAI10902849 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a S. K., Minhazul Islam. |
| 245 | 10 |
▼a Automatic Discovery of Latent Clusters in General Regression Models. |
| 260 | |
▼a [S.l.]:
▼b University of Florida.,
▼c 2017. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2017. |
| 300 | |
▼a 108 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B. |
| 500 | |
▼a Adviser: Arunava Banerjee. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Florida, 2017. |
| 520 | |
▼a We present a flexible nonparametric Bayesian framework for automatic detection of local clusters in general regression models. The models are built using techniques that are now considered standard in statistical parameter estimation literature, |
| 520 | |
▼a In the first part of this thesis, we formulate all traditional versions of the infinite mixture of GLM models under the Dirichlet Process framework. We study extensively two different inference techniques for these models, namely, variational in |
| 520 | |
▼a In the second part, we present a flexible nonparametric generative model for multigroup regression that detects latent common clusters of groups. We name this "Infinite MultiGroup Generalized Linear Model" (iMG-GLM). We present two versions of t |
| 520 | |
▼a In the third part, we present a flexible nonparametric generative model for multilevel regression that strikes an automatic balance between identifying common effects across groups while respecting their idiosyncrasies. We name it "Infinite Mixt |
| 520 | |
▼a For the final problem we present a framework that shows how infinite mixtures of Linear Regression (Dirichlet Process mixtures) can be used to design a new denoising technique in the domain of time series data that presumes a model for the uncor |
| 590 | |
▼a School code: 0070. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a University of Florida. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-11B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0070 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2017 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000415
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |