activity
20162021
collaborators

8 papers

cs.AI2021

Convex Combination Belief Propagation Algorithms

Anna Grim, Pedro Felzenszwalb

We present new message passing algorithms for performing inference with graphical models. Our methods are designed for the most difficult inference problems where loopy belief prop…

cs.CV2021

Direct Estimation of Appearance Models for Segmentation

Jeova F. S. Rocha Neto, Pedro Felzenszwalb, Marilyn Vazquez

Image segmentation algorithms often depend on appearance models that characterize the distribution of pixel values in different image regions. We describe a new approach for estima…

math.OC2020

Clustering with Semidefinite Programming and Fixed Point Iteration

Pedro Felzenszwalb, Caroline Klivans, Alice Paul

We introduce a novel method for clustering using a semidefinite programming (SDP) relaxation of the Max k-Cut problem. The approach is based on a new methodology for rounding the s…

math.OC2020

Iterated Linear Optimization

Pedro Felzenszwalb, Caroline Klivans, Alice Paul

We introduce a fixed point iteration process built on optimization of a linear function over a compact domain. We prove the process always converges to a fixed point and explore th…

cs.CV2020

Spectral Image Segmentation with Global Appearance Modeling

Jeova F. S. Rocha Neto, Pedro F. Felzenszwalb

We introduce a new spectral method for image segmentation that incorporates long range relationships for global appearance modeling. The approach combines two different graphs, one…

math.CO2019

Flow-firing processes

Pedro Felzenszwalb, Caroline Klivans

We consider a discrete non-deterministic flow-firing process for rerouting flow on the edges of a planar complex. The process is an instance of higher-dimensional chip-firing. In t…