no code implementations • 27 Apr 2024 • Evzenie Coupkova, Mireille Boutin
Given a classification problem and a family of classifiers, the Rashomon ratio measures the proportion of classifiers that yield less than a given loss.
no code implementations • 13 Oct 2023 • Mireille Boutin, Gregor Kemper
We fill a gap in the literature by giving a proof for the long-held belief that when $m \ge n+2$, the solution is unique for almost all user positions.
no code implementations • 11 Aug 2021 • Mireille Boutin, Evzenie Coupkova
In particular, our bounds imply that, unless the number of projections n is extremely large, there is a significant advantageous gap between the generalization error of the random projection approach and that of a linear classifier in the extended space.
no code implementations • 21 Aug 2020 • Alden Bradford, Tarun Yellamraju, Mireille Boutin
The different structures uncovered are found to persist as more points are added to the dataset.
no code implementations • 14 Sep 2019 • Mireille Boutin, Alden Bradford
We propose a model for a dataset in ${\mathbb R}^D$ that does not contain any clusters but yet is such that a projection of the points on a random one-dimensional subspace is likely to yield a clustering of the points.
no code implementations • 21 Aug 2018 • Haiyin Wang, Mireille Boutin, Jeffrey Trask, Jan Allebach
The trapping method they follow is based on a hardware-friendly technique proposed by J. Trask (JTHBCT03) which is too computationally expensive for software or firmware implementation.
no code implementations • 17 Jul 2018 • Christian Tendyck, Andrew Haddad, Mireille Boutin
Camera display reflections are an issue in bright light situations, as they may prevent users from correctly positioning the subject in the picture.
no code implementations • 17 Jul 2018 • Albert Parra, Andrew W. Haddad, Mireille Boutin, Edward J. Delp
The memory requirements of the application, including the database of images, are also well within the limits of the device.
no code implementations • 13 Jun 2018 • Tarun Yellamraju, Mireille Boutin
We propose a method to quantify and validate the dependencies of the outcome random variable on the various patterns contained in the observed random variable.
no code implementations • 13 Jun 2018 • Tarun Yellamraju, Jonas Hepp, Mireille Boutin
We propose classification benchmarks based on simple random projection heuristics.
no code implementations • 21 Sep 2012 • Mireille Boutin, Shanshan Huang
We define the Pascal triangle of a discrete (gray scale) image as a pyramidal arrangement of complex-valued moments and we explore its geometric significance.