September 15, 2020 |
On Anisotropic Diffusion Equations for Label Propagation Lisa-Maria Kreusser (University of Cambridge) |
Theory and Algorithms in Graph-based Learning |

September 15, 2020 |
Blind Hyperspectral Unmixing Based on Graph Total Variation Regularization Yifei Lou (University of Texas at Dallas) |
Theory and Algorithms in Graph-based Learning |

September 16, 2020 |
When Labelling Hurts: Learning to Classify Large-Scale Data with Minimal Supervision Angelica Aviles-Rivero (University of Cambridge) |
Theory and Algorithms in Graph-based Learning |

September 16, 2020 |
Bias-Variance Tradeoffs in Joint Spectral Embeddings Daniel Sussman (Boston University) |
Theory and Algorithms in Graph-based Learning |

September 16, 2020 |
Computational Complexity and Forbidden Graph Patterns Puck Rombach (University of Vermont) |
Theory and Algorithms in Graph-based Learning |

September 17, 2020 |
L-Infinity Variational Problems on Graphs: Applications and Continuum Limits Leon Bungert (Friedrich-Alexander-Universität Erlangen-Nürnberg), Tim Roith (Friedrich-Alexander-Universität Erlangen-Nürnberg) |
Theory and Algorithms in Graph-based Learning |

September 17, 2020 |
Vertex Nomination, Consistent Estimation, and Adversarial Modification Vince Lyzinski (University of Maryland) |
Theory and Algorithms in Graph-based Learning |

September 17, 2020 |
Community Detection Using Total Variation and Surface Tension Zach Boyd (University of North Carolina, Chapel Hill) |
Theory and Algorithms in Graph-based Learning |

September 17, 2020 |
On Wasserstein Gradient Flows and the Search of Neural Network Architectures Nicolas Garcia Trillos (University of Wisconsin, Madison) |
Theory and Algorithms in Graph-based Learning |

September 18, 2020 |
Learning Restricted Boltzmann Machines Ankur Moitra (Massachusetts Institute of Technology) |
Theory and Algorithms in Graph-based Learning |

September 18, 2020 |
Learning Discrete Graphical Models: Exact & Neural Network Assisted Methods Marc Vuffray (Los Alamos National Laboratory) |
Theory and Algorithms in Graph-based Learning |

September 18, 2020 |
Learning Ill-Conditioned Gaussian Graphical Models Raghu Meka (University of California, Los Angeles) |
Theory and Algorithms in Graph-based Learning |

September 18, 2020 |
SIAM Internship Panel Montie Avery (University of Minnesota, Twin Cities) |
Industrial Problems Seminar |

September 22, 2020 |
Matrix Denoising with Weighted Loss William Leeb (University of Minnesota, Twin Cities) |
Data Science Seminar |

September 25, 2020 |
The Technical and Organizational Challenges of Data Science Catherine (Katy) Micek (3M) |
Industrial Problems Seminar |

September 29, 2020 |
Multi-Perspective, Simultaneous Embedding and Theoretically Guaranteed Projected Power Method for the Multi-way Matching Problem Vahan Huroyan (University of Arizona) |
Data Science Seminar |

October 02, 2020 |
Combinatorial Algorithms for National Security Cynthia Phillips (Sandia National Laboratories) |
Industrial Problems Seminar |

October 06, 2020 |
Large-Scale Semi-supervised Learning via Graph Structure Learning over High-dense Points Li Wang (University of Texas at Arlington) |
Data Science Seminar |

October 13, 2020 |
Geometric Methods in Statistics, Optimization, and Sampling Tyler Maunu (Massachusetts Institute of Technology) |
Data Science Seminar |

October 16, 2020 |
Systems Modeling in Biopharma Helen Moore (Applied BioMath) |
Industrial Problems Seminar |

October 20, 2020 |
How COVID-19 has Changed the World and What the Future Holds Michael Osterholm (University of Minnesota, Twin Cities) |
Data Science Seminar |

October 23, 2020 |
An Introduction to Image Compression, Old and New Chris Finlay (Deep Render) |
Industrial Problems Seminar |

October 27, 2020 |
Clustering High-dimensional Data with Path Metrics: A Balance of Density and Geometry Anna Little (The University of Utah) |
Data Science Seminar |

October 30, 2020 |
Estimating the Impact of Travel, Rest, and Playing at Home in the National Football League Tom Bliss (National Football League (NFL)) |
Industrial Problems Seminar |

November 03, 2020 |
Machine Learning Methods for Solving High-dimensional Mean-field Game Systems Levon Nurbekyan (University of California, Los Angeles) |
Data Science Seminar |

November 06, 2020 |
Active Community Detection with Maximal Expected Model Change Dan Kushnir (Nokia Bell Labs) |
Industrial Problems Seminar |

November 09, 2020 |
The Quadratic Wasserstein Metric for Inverse Data Matching Problems Yunan Yang (New York University) |
Optimal Control, Optimal Transport, and Data Science |

November 09, 2020 |
Learned Adversarial Regularisers Carola Schoenlieb (University of Cambridge (Cambridge, GB)) |
Optimal Control, Optimal Transport, and Data Science |

November 09, 2020 |
Graphical Optimal Transport Yongxin Chen (Georgia Institute of Technology) |
Optimal Control, Optimal Transport, and Data Science |

November 09, 2020 |
Summarizing and Analyzing Data using Optimal Transport Justin Solomon (Massachusetts Institute of Technology) |
Optimal Control, Optimal Transport, and Data Science |

November 10, 2020 |
Deep Learning and Optimal Control Weinan E (Princeton University) |
Optimal Control, Optimal Transport, and Data Science |

November 10, 2020 |
On The Convergence of MMD GANs: A Theory via Parametric Kernelized Gradient Flows Youssef Mroueh (IBM) |
Optimal Control, Optimal Transport, and Data Science |

November 10, 2020 |
Mathematical Approaches to Deep Learning: Model Uncertainty, Robustness and Regularization Adam Oberman (McGill University) |
Optimal Control, Optimal Transport, and Data Science |

November 10, 2020 |
Natural Graph Wavelet Packets Naoki Saito (University of California, Davis) |
Data Science Seminar |

November 10, 2020 |
A PDE Interpretation of Prediction with Expert Advice Nadejda Drenska (University of Minnesota, Twin Cities) |
Optimal Control, Optimal Transport, and Data Science |

November 11, 2020 |
Streaming Computation of Optimal Weak Transport Barycenters Elsa Cazelles (Institut de Recherche en Informatique de Toulouse - IRIT) |
Optimal Control, Optimal Transport, and Data Science |

November 11, 2020 |
Streaming Computation of Optimal Weak Transport Barycenters Elsa Cazelles (Institut de Recherche en Informatique de Toulouse - IRIT) |
Optimal Control, Optimal Transport, and Data Science |

November 11, 2020 |
Streaming Computation of Optimal Weak Transport Barycenters Elsa Cazelles (University of Chile) |
Optimal Control, Optimal Transport, and Data Science |

November 11, 2020 |
Optimal Control of Fluid Transport Networks Anatoly Zlotnik (Los Alamos National Laboratory) |
Optimal Control, Optimal Transport, and Data Science |

November 11, 2020 |
Active Learning and Optimal Experimental Design Eldad Haber (University of British Columbia) |
Optimal Control, Optimal Transport, and Data Science |

November 11, 2020 |
A Fast Approach to Optimal Transport: The Back-and-forth Method Matthew Jacobs (University of California, Los Angeles) |
Optimal Control, Optimal Transport, and Data Science |

November 12, 2020 |
Wasserstein Control of Mirror Langevin Monte Carlo Kelvin Shuangjian Zhang (École Normale Supérieure) |
Optimal Control, Optimal Transport, and Data Science |

November 12, 2020 |
Stochastic Methods for Optimal Transport in Machine Learning Applications Aude Genevay (Massachusetts Institute of Technology) |
Optimal Control, Optimal Transport, and Data Science |

November 12, 2020 |
Prediction with Expert Advice: A PDE Perspective on a Model Problem from Online Machine Learning Robert Kohn (New York University) |
Optimal Control, Optimal Transport, and Data Science |

November 12, 2020 |
Information in Mean Field Control Aaron Palmer (University of British Columbia) |
Optimal Control, Optimal Transport, and Data Science |

November 13, 2020 |
Gradient Flows in the Wasserstein Metric: From Discrete to Continuum via Regularization Katy Craig (University of California, Santa Barbara) |
Optimal Control, Optimal Transport, and Data Science |

November 13, 2020 |
Lecture Ivana Seric (Philadelphia 76ers) |
Industrial Problems Seminar |

November 17, 2020 |
Fast Statistical and Geometric Distances Between Families of Distributions Alexander Cloninger (University of California, San Diego) |
Data Science Seminar |

November 24, 2020 |
Lecture Gal Mishne (University of California, San Diego) |
Data Science Seminar |

December 01, 2020 |
Lecture Xiuyuan Cheng (Duke University) |
Data Science Seminar |

December 04, 2020 |
Lecture Julie Thompson (Boston Scientific) |
Industrial Problems Seminar |

December 08, 2020 |
Lecture Matthew Hirn (Michigan State University) |
Data Science Seminar |

December 15, 2020 |
Lecture Barak Sober (Duke University) |
Data Science Seminar |

January 19, 2021 |
Lecture Dimitris Giannakis (Courant Institute of Mathematical Sciences) |
Data Science Seminar |

January 22, 2021 |
Lecture Edo Liberty (HyperCube) |
Industrial Problems Seminar |

January 26, 2021 |
Lecture Amir Sagiv (Columbia University) |
Data Science Seminar |

January 29, 2021 |
Lecture Hany Farag (Canadian Imperial Bank of Commerce (CIBC)) |
Industrial Problems Seminar |

February 02, 2021 |
Lecture Wenjing Liao (Georgia Institute of Technology) |
Data Science Seminar |

February 09, 2021 |
Lecture Kenth Monsen (Telenor) |
Data Science Seminar |

February 23, 2021 |
Lecture Facundo Mémoli (The Ohio State University) |
Data Science Seminar |

March 02, 2021 |
Lecture Jianfeng Lu (Duke University) |
Data Science Seminar |

March 19, 2021 |
Lecture Daniel Kaslovsky (Automox) |
Industrial Problems Seminar |