상세정보
Export to Refworks부가기능
Sparse modeling : theory, algorithms, and applications
상세 프로파일
| 자료유형 | 단행본 |
|---|---|
| 서명/저자사항 | Sparse modeling : theory, algorithms, and applications/ Irina Rish, Genady Ya. Grabarnik. |
| 개인저자 | Rish, Irina,1969- author. Grabarnik, Genady Ya,author, |
| 형태사항 | 1 online resource (xviii, 231 pages): illustrations (some color). |
| 총서사항 | Chapman & Hall/CRC machine learning & pattern recognition series |
| 기타형태 저록 | Print version: Rish, Irina, 1969- Sparse modeling. Boca Raton, FL : CRC Press : Taylor & Francis Group, 2015 9781439828694 |
| ISBN | 9781439828700 1439828709 1322667411 9781322667416 1439828695 9781439828694 |
| 서지주기 | Includes bibliographical references. |
| 내용주기 | 1. Introduction -- 2. Sparse recovery : problem formulations -- 3. Theoretical results (deterministic part) -- 4. Theoretical results (probabilistic part) -- 5. Algorithms for sparse recovery problems -- 6. Beyond LASSO : structured sparsity -- 7. Beyond LASSO : other loss functions -- 8. Sparse graphical models -- 9. Sparse matrix factorization : dictionary learning and beyond. |
| 요약 | Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing. Sparse Modeling: Theory, Algorithms, and Applications provides an introduction to the growing field of sparse modeling, including application examples, problem formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery. |
| 일반주제명 | Mathematical models. Sampling (Statistics) Data reduction. Sparse matrices. SCIENCE --System Theory. TECHNOLOGY & ENGINEERING --Operations Research. Data reduction. Mathematical models. Sampling (Statistics) Sparse matrices. |
| 언어 | 영어 |
| 바로가기 |  |
