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Convex Combinatorial Optimization [PDF]
Discrete & Computational Geometry, 2003 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
Onn, Shmuel, Rothblum, Uriel G.
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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.
Onn, Shmuel
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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
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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 ...
Jain, Prateek, Kar, Purushottam
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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
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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
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Quasi Semi and Pseudo Semi (p,E)-Convexity in Non-Linear Optimization Programming
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2023 The class of quasi semi -convex functions and pseudo semi -convex functions are presented in this paper by combining the class of -convex functions with the class of quasi semi -convex functions and pseudo semi -convex functions, respectively.
Revan I. Hazim, Saba N. Majeed
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Optimization Method for Wide Beam Sonar Transmit Beamforming
Sensors, 2022 Imaging and mapping sonars such as forward-looking sonars (FLS) and side-scan sonars (SSS) are sensors frequently used onboard autonomous underwater vehicles.
Louise Rixon Fuchs +2 more
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Private stochastic convex optimization: optimal rates in linear time [PDF]
Symposium on the Theory of Computing, 2020 We study differentially private (DP) algorithms for stochastic convex optimization: the problem of minimizing the population loss given i.i.d. samples from a distribution over convex loss functions. A recent work of Bassily et al.
V. Feldman, Tomer Koren, Kunal Talwar
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