Practical Applications of Sparse Modeling
Irina Rish
Sold by ThriftBooks-Atlanta, AUSTELL, GA, U.S.A.
AbeBooks Seller since March 24, 2009
Used - Hardcover
Condition: Used - As new
Ships within U.S.A.
Quantity: 1 available
Add to basketSold by ThriftBooks-Atlanta, AUSTELL, GA, U.S.A.
AbeBooks Seller since March 24, 2009
Condition: Used - As new
Quantity: 1 available
Add to basketPages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less.
Seller Inventory # G0262027720I2N00
Key approaches in the rapidly developing area of sparse modeling, focusing on its application in fields including neuroscience, computational biology, and computer vision.
Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision.
Sparse modeling methods can improve the interpretability of predictive models and aid efficient recovery of high-dimensional unobserved signals from a limited number of measurements. Yet despite significant advances in the field, a number of open issues remain when sparse modeling meets real-life applications. The book discusses a range of practical applications and state-of-the-art approaches for tackling the challenges presented by these applications. Topics considered include the choice of method in genomics applications; analysis of protein mass-spectrometry data; the stability of sparse models in brain imaging applications; sequential testing approaches; algorithmic aspects of sparse recovery; and learning sparse latent models.
Contributors
A. Vania Apkarian, Marwan Baliki, Melissa K. Carroll, Guillermo A. Cecchi, Volkan Cevher, Xi Chen, Nathan W. Churchill, Rémi Emonet, Rahul Garg, Zoubin Ghahramani, Lars Kai Hansen, Matthias Hein, Katherine Heller, Sina Jafarpour, Seyoung Kim, Mladen Kolar, Anastasios Kyrillidis, Seunghak Lee, Aurelie Lozano, Matthew L. Malloy, Pablo Meyer, Shakir Mohamed, Alexandru Niculescu-Mizil, Robert D. Nowak, Jean-Marc Odobez, Peter M. Rasmussen, Irina Rish, Saharon Rosset, Martin Slawski, Stephen C. Strother, Jagannadan Varadarajan, Eric P. Xing
Irina Rish, Guillermo Cecchi, and Aurelie Lozao are Research Staff Members at IBM T. J. Watson Research Center, New York. Alexandru Niculescu-Mizil is a Researcher at the Machine Learning Department at NEC Labs America, Princeton, New Jersey.
"About this title" may belong to another edition of this title.
We guarantee the condition of every book as it's described
on the Abebooks website. If you're dissatisfied with your
purchase (Incorrect Book/Not as Described/Damaged) or if the
order hasn't arrived, you're eligible for a refund within 30
days of the estimated delivery date. If you've changed your
mind about a book that you've ordered, please use the "Ask
bookseller a question link to contact us" and we'll respond
as soon as possible.
All domestic Standard shipments are distributed from our warehouses by OSM, then handed off to the USPS for final delivery.
2-Day Shipping is delivered by FedEx, which does not deliver to PO boxes.
International shipments are tendered to the local postal service in the destination country for final delivery – We do not use courier services for international deliveries.
| Order quantity | 4 to 8 business days | 4 to 8 business days |
|---|---|---|
| First item | US$ 0.00 | US$ 0.00 |
Delivery times are set by sellers and vary by carrier and location. Orders passing through Customs may face delays and buyers are responsible for any associated duties or fees. Sellers may contact you regarding additional charges to cover any increased costs to ship your items.