Results 91 to 100 of about 1,804,722 (202)
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs. [PDF]
J Am Stat Assoc, 2023 Chen Y, Fan J, Wang B, Yan Y.
europepmc +1 more source
Saddle Points of Partial Augmented Lagrangian Functions
Mathematical and Computational ApplicationsIn this paper, we study a class of optimization problems with separable constraint structures, characterized by a combination of convex and nonconvex constraints.
Longfei Huang +3 more
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Penalized Convex Estimation in Dynamic Location Models
Journal of Time Series Analysis, EarlyView.ABSTRACT This paper studies L1$$ {L}^1 $$‐penalized estimation for location models yt=mt+ϵt$$ {y}_t={m}_t+{\epsilon}_t $$, where mt$$ {m}_t $$ is defined by a possibly non‐Markovian recursion and ϵt$$ {\epsilon}_t $$ is a martingale difference sequence with possibly time‐varying conditional variance.
Reda Alami Chentoufi
wiley +1 more source
, 2017 Primal or dual strong-duality (or min-sup, inf-max duality) in nonconvex optimization is revisited in view of recent literature on the subject, establishing, in particular, new characterizations for the second case.
Flores-Bazan, Fabian +7 more
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Sparse Causal Dynamic Linear Regression
Journal of Time Series Analysis, EarlyView.ABSTRACT We develop a sparse causal dynamic regression framework for long multivariate time series. With very long time series, the potentially large number of lags and leads in a dynamic regression model often makes time‐domain estimation numerically unstable or intractable.
Rui Huang, Kung‐Sik Chan
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Proportional Nash solutions - A new and procedural analysis of nonconvex bargaining problems [PDF]
This paper studies the Nash solution to nonconvex bargaining problems. The Nash solution in such a context is typically multi-valued. We introduce a procedure to exclude some options recommended by the Nash solution. The procedure is based on the idea of
Yoshihara, Naoki, Xu, Yongsheng
core
Big Network Analytics Based on Nonconvex Optimization
, 2015 The scientific problems that Big Data faces may be network scientific problems. Network analytics contributes a great deal to networked Big Data processing.
Maoguo Gong +3 more
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High-dimensional Cost-constrained Regression via Nonconvex Optimization. [PDF]
Technometrics, 2022 Yu G, Fu H, Liu Y.
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The fundamental theorem of asset pricing with and without transaction costs
Mathematical Finance, Volume 35, Issue 2, Page 567-609, April 2025.Abstract We prove a version of the fundamental theorem of asset pricing (FTAP) in continuous time that is based on the strict no‐arbitrage condition and that is applicable to both frictionless markets and markets with proportional transaction costs. We consider a market with a single risky asset whose ask price process is higher than or equal to its ...
Christoph Kühn
wiley +1 more source
Smith chart-based particle swarm optimization algorithm for multi-objective engineering problems [PDF]
Iranian Journal of Numerical Analysis and OptimizationParticle swarm optimization (PSO) is a widely recognized bio-inspired algorithm for systematically exploring solution spaces and iteratively iden-tifying optimal points.
A. Falloun, Y. Dursun, A. Ait Madi
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