<p>This book focuses on the advanced soft computational and probabilistic methods that the authors have published over the past few years. It describes theoretical results and applications, and discusses how various uncertainty measures β probability, plausibility and belief measures β can be treate
Scientific Data Ranking Methods: Theory and Applications
β Scribed by Manuela Pavan and Roberto Todeschini (Eds.)
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Leaves
- 215
- Series
- Data Handling in Science and Technology 27
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
<span>1. Multivariate Linear Regression.- 2. Reduced-Rank Regression Model.- 3. Reduced-Rank Regression Models with Two Sets of Regressors.- 4. Reduced-Rank Regression Model with Autoregressive Errors.- 5. Multiple Time Series Modeling with Reduced Ranks.- 6. The Growth Curve Model and Reduced-Rank
<p><i>Tensors for Data Processing: Theory, Methods and Applications</i> presents both classical and state-of-the-art methods on tensor computation for data processing, covering computation theories, processing methods, computing and engineering applications, with an emphasis on techniques for data p
Tensors for Data Processing (2021) [Liu] [9780128244470]