We meet at 10:00am on Fridays in Gates 8115 (The Conference Hall in the Corner). This page is maintained by Don Sheehy. Email him (dsheehy@cs.cmu.edu) with any paper suggestions.
We meet at 10:00am on Fridays in Gates 8115 (The Conference Hall in the Corner). This page is maintained by Don Sheehy. Email him (dsheehy@cs.cmu.edu) with any paper suggestions.
| Date | Paper | Presenter |
| 4/2 |
Topological Persistence and Simplification
Herbert Edelsbrunner, David Letscher, and Afra Zomorodian |
Don Sheehy |
| 4/9 |
Dimension Detection via Slivers
Siu-Wing Cheng and Man-Kwun Chiu |
Todd Phillips |
| 4/16 |
Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
Mikhail Belkin and Partha Niyogi |
Babis Tsourakakis |
| 4/30 |
Spectral Methods for Dimensionality Reduction
Lawrence K. Saul, Kilian Q. Weinberger, Fei Sha, Jihun Ham, and Daniel D. Lee |
Field Cady |
| 5/7 |
Continued from last week
Spectral Methods |
Field Cady |
| 5/14 |
A Duality View of Spectral Methods for Dimensionality Reduction
L. Xiao, J. Sun, and S. Boyd The paper addresses Maximum Variance Unfolding in particular and relates the method to a family of spectral techniques for finding low dimensional euclidean embeddings of high dimensional data (represented by an input graph). The original paper for MVU can be found here: Unsupervised learning of image manifolds by semidefinite programming |
Dave Tolliver |
| 5/21 |
Fitting a Graph to Vector Data
Samuel I. Daitch, Jonathan Kelner, and Daniel A. Spielman |
Babis Tsourakakis |
| 5/28 |
Reconstruction Using Witness Complexes
Leonidas J. Guibas and Steve Y. Oudot Their later paper with Jean-Daniel Boissonat (listed below) generalized this result to arbitrary dimensions. |
Don Sheehy |
| 6/25 |
Learning the structure of manifolds using random projections
Yoav Freund, Sanjoy Dasgupta, Mayank Kabra, and Nakul Verma See also the journal version. |
Liu Yang |
| 7/2 |
Triangulating Topological Spaces
Herbert Edelsbrunner and Nimish R. Shah |
Don Sheehy |
| 7/16 |
From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians
Hein, M., J. Audibert and U. von Luxburg See also the journal version. |
Liu Yang |
| 9/11 |
Computing Betti Numbers via Combinatorial Laplacians
Joel Friedman This brings together two popular topics for this reading group, Betti numbers and Laplacians. I believe it is identical, but there is also the Version from STOC. |
Don Sheehy |
| 9/18 |
Inferring Tree Models for Oncogenesis from Comparative Genome Hybridization Data
Richard Desper, Feng Jiang, Olli-P. Kallioniemi, Holger Moch, Christos Papadimitriou, and Alejandro Schaffer |
Babis Tsourakakis |
| 10/2 |
Continued from last time: Inferring Tree Models for Oncogenesis from Comparative Genome Hybridization Data
Richard Desper, Feng Jiang, Olli-P. Kallioniemi, Holger Moch, Christos Papadimitriou, and Alejandro Schaffer |
Babis Tsourakakis |
| 10/9 |
A Unified View of Kernel k-means, Spectral Clustering and Graph Cuts
Inderjit Dhillon, Yuqiang Guan and Brian Kulis |
Kanat Tangwongsan |
| 10/23 |
Discrete Laplace Operator on Meshed Surfaces
Mikhail Belkin, Jian Sun, and Yusu Wang |
Luis Coelho |
| 11/6 |
Disk Packings and Planar Separators
Dan Spielman and Sheng-Hua Teng |
Todd Phillips |
| 1 |
Manifold Reconstruction from Point Samples
Siu-Wing Cheng, Tamal K. Dey, and Edgar A. Ramos |
| 2 |
Towards Persistence-Based Reconstruction in Euclidean Spaces
Frederic Chazal and Steven Y. Oudot |
| 3 |
Analysis of Scalar Fields over Point Cloud Data
Frederic Chazal, Leonidas J. Guibas, Steven Y. Oudot, and Primoz Skraba |
| 4 |
Manifold Reconstruction in Arbitrary Dimensions Using Witness Complexes
Jean-Daniel Boissonnat, Leonidas J. Guibas, and Steven Y. Oudot |
| 5 |
Colored Maximum Variance Unfolding
Le Song, Alex Smola, Karsten Borgwardt, and Arthur Gretton |
| 6 |
Tighter Bounds for Random Projections of Manifolds
Kenneth L. Clarkson |