Lectures on Nonsmooth Optimization
Qinian Jin
роЬрпВро▓рпИ 2025 ┬╖ Texts in Applied Mathematics рокрпБродрпНродроХроорпН 82 ┬╖ Springer Nature
рооро┐ройрпНрокрпБродрпНродроХроорпН
560
рокроХрпНроХроЩрпНроХро│рпН
reportро░рпЗроЯрпНроЯро┐роЩрпНроХрпБроХро│рпБроорпН роХро░рпБродрпНродрпБроХро│рпБроорпН роЪро░ро┐рокро╛ро░рпНроХрпНроХрокрпНрокроЯрпБро╡родро┐ро▓рпНро▓рпИ┬ароорпЗро▓рпБроорпН роЕро▒ро┐роХ
роЗроирпНрод рооро┐ройрпНрокрпБродрпНродроХродрпНродрпИрокрпН рокро▒рпНро▒ро┐
This book provides an in-depth exploration of nonsmooth optimization, covering foundational algorithms, theoretical insights, and a wide range of applications. Nonsmooth optimization, characterized by nondifferentiable objective functions or constraints, plays a crucial role across various fields, including machine learning, imaging, inverse problems, statistics, optimal control, and engineering. Its scope and relevance continue to expand, as many real-world problems are inherently nonsmooth or benefit significantly from nonsmooth regularization techniques. This book covers a variety of algorithms for solving nonsmooth optimization problems, which are foundational and recent. It first introduces basic facts on convex analysis and subdifferetial calculus, various algorithms are then discussed, including subgradient methods, mirror descent methods, proximal algorithms, alternating direction method of multipliers, primal dual splitting methods and semismooth Newton methods. Moreover, error bound conditions are discussed and the derivation of linear convergence is illustrated. A particular chapter is delved into first order methods for nonconvex optimization problems satisfying the Kurdyka-Lojasiewicz condition. The book also addresses the rapid evolution of stochastic algorithms for large-scale optimization. This book is written for a wide-ranging audience, including senior undergraduates, graduate students, researchers, and practitioners who are interested in gaining a comprehensive understanding of nonsmooth optimization.
роЖроЪро┐ро░ро┐ропро░рпН роХрпБро▒ро┐рокрпНрокрпБ
Qinian Jin graduated from Anhui Normal University in China with a bachelor degree and obtained his PhD degree from the Department of Mathematics at Rutgers University, New Brunswick, USA. He then joined the Mathematical Sciences Institute at Australian National University in 2011. His research was supported by Australian Research Council (ARC) and he was awarded the Future Fellowship from ARC. His research interest covers inverse problems, numerical analysis, optimization, partial differential equations, geometric analysis. In particular his recent research focuses on using nonsmooth optimization technique to design algorithms for solving ill-posed inverse problems. He has published about 70 papers on international journals.
роЗроирпНрод рооро┐ройрпНрокрпБродрпНродроХродрпНродрпИ роородро┐рокрпНрокро┐роЯрпБроЩрпНроХро│рпН
роЙроЩрпНроХро│рпН роХро░рпБродрпНродрпИрокрпН рокроХро┐ро░ро╡рпБроорпН.
рокроЯро┐рокрпНрокродрпБ роХрпБро▒ро┐родрпНрод родроХро╡ро▓рпН
ро╕рпНрооро╛ро░рпНроЯрпНроГрокрпЛройрпНроХро│рпН рооро▒рпНро▒рпБроорпН роЯрпЗрокрпНро▓рпЖроЯрпНроХро│рпН
Android рооро▒рпНро▒рпБроорпН iPad/iPhoneроХрпНроХро╛рой Google Play рокрпБроХрпНро╕рпН роЖрокрпНро╕рпИ роиро┐ро▒рпБро╡рпБроорпН. роЗродрпБ родро╛ройро╛роХро╡рпЗ роЙроЩрпНроХро│рпН роХрогроХрпНроХрпБроЯройрпН роТродрпНродро┐роЪрпИроХрпНроХрпБроорпН рооро▒рпНро▒рпБроорпН роОроЩрпНроХро┐ро░рпБроирпНродро╛ро▓рпБроорпН роЖройрпНро▓рпИройро┐ро▓рпН роЕро▓рпНро▓родрпБ роЖроГрокрпНро▓рпИройро┐ро▓рпН рокроЯро┐роХрпНроХ роЕройрпБроородро┐роХрпНроХрпБроорпН.
ро▓рпЗрокрпНроЯро╛рокрпНроХро│рпН рооро▒рпНро▒рпБроорпН роХроорпНрокрпНропрпВроЯрпНроЯро░рпНроХро│рпН
Google Playропро┐ро▓рпН ро╡ро╛роЩрпНроХро┐роп роЖроЯро┐ропрпЛ рокрпБродрпНродроХроЩрпНроХро│рпИ роЙроЩрпНроХро│рпН роХроорпНрокрпНропрпВроЯрпНроЯро░ро┐ройрпН ро╡ро▓рпИ роЙро▓ро╛ро╡ро┐ропро┐ро▓рпН роХрпЗроЯрпНроХро▓ро╛роорпН.
рооро┐ройрпНро╡ро╛роЪро┐рокрпНрокрпБ роЪро╛родройроЩрпНроХро│рпН рооро▒рпНро▒рпБроорпН рокро┐ро▒ роЪро╛родройроЩрпНроХро│рпН
Kobo роЗ-ро░рпАроЯро░рпНроХро│рпН рокрпЛройрпНро▒ роЗ-роЗроЩрпНроХрпН роЪро╛родройроЩрпНроХро│ро┐ро▓рпН рокроЯро┐роХрпНроХ, роГрокрпИро▓рпИрокрпН рокродро┐ро╡ро┐ро▒роХрпНроХро┐ роЙроЩрпНроХро│рпН роЪро╛родройродрпНродро┐ро▒рпНроХрпБ рооро╛ро▒рпНро▒ро╡рпБроорпН. роЖродро░ро┐роХрпНроХрокрпНрокроЯрпБроорпН роЗ-ро░рпАроЯро░рпНроХро│рпБроХрпНроХрпБ роГрокрпИро▓рпНроХро│рпИ рооро╛ро▒рпНро▒, роЙродро╡ро┐ роорпИропродрпНродро┐ройрпН ро╡ро┐ро░ро┐ро╡ро╛рой ро╡ро┤ро┐роорпБро▒рпИроХро│рпИрокрпН рокро┐ройрпНрокро▒рпНро▒ро╡рпБроорпН.
