How easy is matching 2D line models using local search?

How Easy is Matching 2D Line Models Using Local Search?

Local search is a well established and highly ef fective method for solving complex combinatorial optimiza tion problems Here local search is adapted to solve di cult geometric matching problems Matching is posed as the problem of nding the optimal many to many correspon dence mapping between a line segment model and image line segments Image data is assumed to be fragmented noisy and cluttered...

Multi-Dimensional Prefix Matching Using Line Search

With the increasing popularity of firewalls, virtual private networks (VPNs) and Quality of Service (QoS) routing, packet classification becomes increasingly important in the Internet. The high-performance solutions known so far strongly rely on certain properties of the filter database to match against, such as a small number of distinct prefixes or the absence of conflicts. In this paper, we ...

Pose-Invariant 2D Face Recognition by Matching Using Graphical Models

Easy Hyperparameter Search Using Optunity

Optunity is a free software package dedicated to hyperparameter optimization. It contains various types of solvers, ranging from undirected methods to direct search, particle swarm and evolutionary optimization. The design focuses on ease of use, flexibility, code clarity and interoperability with existing software in all machine learning environments. Optunity is written in Python and contains...

Local Search Approaches in Stable Matching Problems

The stable marriage (SM) problem has a wide variety of practical applications, ranging from matching resident doctors to hospitals, to matching students to schools or, more generally, to any two-sided market. In the classical formulation, n men and n women express their preferences (via a strict total order) over the members of the other sex. Solving an SM problem means finding a stable marriag...