Results 1 to 10 of about 4,550,557 (247)
Convex Matroid Optimization [PDF]
SIAM Journal on Discrete Mathematics, 2002 We consider a problem of optimizing convex functionals over matroid bases. It is richly expressive and captures certain quadratic assignment and clustering problems.
Shmuel Onn
core +8 more sources
Convex Combinatorial Optimization [PDF]
Discrete & Computational Geometry, 2004 We introduce the convex combinatorial optimization problem, a far reaching generalization of the standard linear combinatorial optimization problem. We show that it is strongly polynomial time solvable over any edge-guaranteed family, and discuss several
Shmuel Onn, Uriel G. Rothblum
core +11 more sources
Quasi-Herglotz functions and convex optimization [PDF]
Royal Society Open Science, 2020 We introduce the set of quasi-Herglotz functions and demonstrate that it has properties useful in the modelling of non-passive systems. The linear space of quasi-Herglotz functions constitutes a natural extension of the convex cone of Herglotz functions.
Y. Ivanenko +5 more
doaj +10 more sources
Implementable tensor methods in unconstrained convex optimization. [PDF]
Math Program, 2021 In this paper we develop new tensor methods for unconstrained convex optimization, which solve at each iteration an auxiliary problem of minimizing convex multivariate polynomial.
Nesterov Y.
europepmc +2 more sources
Non-convex Optimization for Machine Learning [PDF]
Found. Trends Mach. Learn., 2017 A vast majority of machine learning algorithms train their models and perform inference by solving optimization problems. In order to capture the learning and prediction problems accurately, structural constraints such as sparsity or low rank are ...
Prateek Jain, Purushottam Kar
semanticscholar +3 more sources
Convex Optimization in R [PDF]
Journal of Statistical Software, 2014 Convex optimization now plays an essential role in many facets of statistics. We briefly survey some recent developments and describe some implementations of these methods in R .
Roger Koenker, Ivan Mizera
doaj +4 more sources
Optimization of Convex Risk Functions [PDF]
SSRN Electronic Journal, 2004 We consider optimization problems involving convex risk functions. By employing techniques of convex analysis and optimization theory in vector spaces of measurable functions, we develop new representation theorems for risk models, and optimality and duality theory for problems with convex risk functions.
Andrzej Ruszczyński, Alexander Shapiro
openalex +5 more sources
Convex and Non-Convex Optimization under Generalized Smoothness [PDF]
Neural Information Processing Systems, 2023 Classical analysis of convex and non-convex optimization methods often requires the Lipshitzness of the gradient, which limits the analysis to functions bounded by quadratics.
Haochuan Li +4 more
semanticscholar +1 more source
Motion planning around obstacles with convex optimization [PDF]
Science Robotics, 2022 From quadrotors delivering packages in urban areas to robot arms moving in confined warehouses, motion planning around obstacles is a core challenge in modern robotics.
Tobia Marcucci +3 more
semanticscholar +1 more source
Convex projection and convex multi-objective optimization [PDF]
Journal of Global Optimization, 2021 AbstractIn this paper we consider a problem, called convex projection, of projecting a convex set onto a subspace. We will show that to a convex projection one can assign a particular multi-objective convex optimization problem, such that the solution to that problem also solves the convex projection (and vice versa), which is analogous to the result ...
Gabriela Kováčová, Birgit Rudloff
openaire +4 more sources