Point process estimation with Mirror Prox algorithms
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Publication:2019904
DOI10.1007/s00245-019-09634-6zbMath1461.60033OpenAlexW2990042492WikidataQ126665316 ScholiaQ126665316MaRDI QIDQ2019904
Le Song, Niao He, Zaid Harchaoui, Yichen Wang
Publication date: 22 April 2021
Published in: Applied Mathematics and Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00245-019-09634-6
Uses Software
Cites Work
- Unnamed Item
- Smooth minimization of non-smooth functions
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- On the ergodic convergence rates of a first-order primal-dual algorithm
- Gradient methods for minimizing composite functions
- Smoothing proximal gradient method for general structured sparse regression
- Minimizing finite sums with the stochastic average gradient
- On stochastic mirror-prox algorithms for stochastic Cartesian variational inequalities: randomized block coordinate and optimal averaging schemes
- A first-order primal-dual algorithm for convex problems with applications to imaging
- Randomized primal-dual proximal block coordinate updates
- An efficient primal dual prox method for non-smooth optimization
- Mirror Prox algorithm for multi-term composite minimization and semi-separable problems
- Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
- Lectures on Modern Convex Optimization
- Option Pricing with a General Marked Point Process
- The Ordered Subsets Mirror Descent Optimization Method with Applications to Tomography
- Optimization with Sparsity-Inducing Penalties
- Efficiency of Coordinate Descent Methods on Huge-Scale Optimization Problems
- Stochastic Block Mirror Descent Methods for Nonsmooth and Stochastic Optimization
- Tracking Dynamic Point Processes on Networks
- An Accelerated HPE-Type Algorithm for a Class of Composite Convex-Concave Saddle-Point Problems
- Robust Stochastic Approximation Approach to Stochastic Programming
- Image deblurring with Poisson data: from cells to galaxies
- Entropic Proximal Mappings with Applications to Nonlinear Programming
- Bregman Monotone Optimization Algorithms
- First-Order Methods in Optimization
- Relatively Smooth Convex Optimization by First-Order Methods, and Applications
- Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization
- Optimal Primal-Dual Methods for a Class of Saddle Point Problems
- Self-Exciting Point Process Modeling of Crime
- Fast Gradient-Based Algorithms for Constrained Total Variation Image Denoising and Deblurring Problems
- Restoration of Poissonian Images Using Alternating Direction Optimization
- This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice
- Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
- Composite Self-Concordant Minimization
- Proximité et dualité dans un espace hilbertien
- A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications
- Derivatives pricing with marked point processes using tick-by-tick data
- Convex analysis and monotone operator theory in Hilbert spaces