K-Medoids For K-Means Seeding

1 code implementation • NeurIPS 2017 • James Newling, François Fleuret

We run experiments showing that algorithm clarans (Ng et al., 2005) finds better K-medoids solutions than the Voronoi iteration algorithm.

Data Structures and Algorithms

A Sub-Quadratic Exact Medoid Algorithm

no code implementations • 23 May 2016 • James Newling, François Fleuret

We present a new algorithm, trimed, for obtaining the medoid of a set, that is the element of the set which minimises the mean distance to all other elements.

Nested Mini-Batch K-Means

1 code implementation • NeurIPS 2016 • James Newling, François Fleuret

A new algorithm is proposed which accelerates the mini-batch k-means algorithm of Sculley (2010) by using the distance bounding approach of Elkan (2003).

Fast K-Means with Accurate Bounds

2 code implementations • 8 Feb 2016 • James Newling, François Fleuret

We propose a novel accelerated exact k-means algorithm, which performs better than the current state-of-the-art low-dimensional algorithm in 18 of 22 experiments, running up to 3 times faster.

Clustering Vector Quantization (k-means problem)

Results from the Supernova Photometric Classification Challenge

1 code implementation • 5 Aug 2010 • Richard Kessler, Bruce Bassett, Pavel Belov, Vasudha Bhatnagar, Heather Campbell, Alex Conley, Joshua A. Frieman, Alexandre Glazov, Santiago Gonzalez-Gaitan, Renee Hlozek, Saurabh Jha, Stephen Kuhlmann, Martin Kunz, Hubert Lampeitl, Ashish Mahabal, James Newling, Robert C. Nichol, David Parkinson, Ninan Sajeeth Philip, Dovi Poznanski, Joseph W. Richards, Steven A. Rodney, Masao Sako, Donald P. Schneider, Mathew Smith, Maximilian Stritzinger, Melvin Varughese

A spectroscopically confirmed subset was provided for training.

Cosmology and Nongalactic Astrophysics