{
"item_title" : "Algorithms for Sparsity-Constrained Optimization",
"item_author" : [" Sohail Bahmani "],
"item_description" : "This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a greedy algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.",
"item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/31/901/880/3319018809_b.jpg",
"price_data" : {
"retail_price" : "169.99", "online_price" : "169.99", "our_price" : "169.99", "club_price" : "169.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : ""
}
}
Algorithms for Sparsity-Constrained Optimization
Overview
This thesis demonstrates techniques that provide faster and more accurate solutions to a variety of problems in machine learning and signal processing. The author proposes a "greedy" algorithm, deriving sparse solutions with guarantees of optimality. The use of this algorithm removes many of the inaccuracies that occurred with the use of previous models.
This item is Non-Returnable
Customers Also Bought
Details
- ISBN-13: 9783319018805
- ISBN-10: 3319018809
- Publisher: Springer
- Publish Date: October 2013
- Dimensions: 9.2 x 6.2 x 0.5 inches
- Shipping Weight: 0.85 pounds
- Page Count: 107
Related Categories
