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Found 13 papers, 1 papers with code
One-sided Frank-Wolfe algorithms for saddle problems
In case $h^*$ is the indicator function of a linear constraint and function $f$ is quadratic, we show a $O(1/n^2)$ convergence rate on the dual objective, requiring $O(n \log n)$ calls of $lmo$.
Optimization and Control
Solving relaxations of MAP-MRF problems: Combinatorial in-face Frank-Wolfe directions
We consider the problem of solving LP relaxations of MAP-MRF inference problems, and in particular the method proposed recently in (Swoboda, Kolmogorov 2019; Kolmogorov, Pock 2021).
MAP inference via Block-Coordinate Frank-Wolfe Algorithm
We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference in structured energy minimization problems.
Efficient Optimization for Rank-based Loss Functions
We provide a complete characterization of the loss functions that are amenable to our algorithm, and show that it includes both AP and NDCG based loss functions.
Total variation on a tree
We consider the problem of minimizing the continuous valued total variation subject to different unary terms on trees and propose fast direct algorithms based on dynamic programming to solve these problems.
A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly max-Oracle
Structural support vector machines (SSVMs) are amongst the best performing models for structured computer vision tasks, such as semantic image segmentation or human pose estimation.
Combining pattern-based CRFs and weighted context-free grammars
We propose a {\em Grammatical Pattern-Based CRF model }(\GPB) that combines the two in a natural way.
Proceedings of The 38th Annual Workshop of the Austrian Association for Pattern Recognition (ÖAGM), 2014
The 38th Annual Workshop of the Austrian Association for Pattern Recognition (\"OAGM) will be held at IST Austria, on May 22-23, 2014.
Potts model, parametric maxflow and k-submodular functions
Furthermore, the output of our algorithm allows to speed-up the subsequent alpha expansion for the unlabeled part, or can be used as it is for time-critical applications.
A new look at reweighted message passing
We propose a new family of message passing techniques for MAP estimation in graphical models which we call {\em Sequential Reweighted Message Passing} (SRMP).
Simplifying Energy Optimization using Partial Enumeration
Energies with high-order non-submodular interactions have been shown to be very useful in vision due to their high modeling power.
Inference algorithms for pattern-based CRFs on sequence data
(Komodakis & Paragios, 2009) gave an $O(n L)$ algorithm for computing the MAP.
Generalized roof duality and bisubmodular functions
We say that the relaxation is {\em totally half-integral} if $\hat f(\bx)$ is a polyhedral function with half-integral extreme points $\bx$, and this property is preserved after adding an arbitrary combination of constraints of the form $x_i=x_j$, $x_i=1-x_j$, and $x_i=\gamma$ where $\gamma\in\{0, 1,\frac{1}{2}\}$ is a constant.
