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Geometric Methods in Optimization and Sampling Reunion
Program
Geometric Methods in Optimization and Sampling
Location
Calvin Lab auditorium
Date
Tuesday, Jan. 10
–
Thursday, Jan. 12, 2023
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Workshop & Symposia
Geometric Methods in Optimization and Sampling Reunion
Secondary tabs
The Workshop
Schedule
(active tab)
All talks are listed in Pacific Time. Schedule subject to change.
Tuesday, Jan. 10, 2023
9
–
9:25 a.m.
Coffee and Check In
9:25
–
9:30 a.m.
Opening Remarks
9:25
–
9:30 a.m.
Opening Remarks
9:30
–
10:15 a.m.
The Restricted Gaussian Oracle as a Proximity Operator for Sampling
Adil Salim (KAUST)
10:15
–
11 a.m.
Convergence in KL Divergence of the Inexact Langevin Algorithm with Application to Score-based Generative Models
Andre Wibisono (Yale University)
11
–
11:30 a.m.
Break
11:30 a.m.
–
12:15 p.m.
Quantization of Measures via Interacting Particle-based Optimization
Dejan Slepcev (Carnegie Mellon University)
12:15
–
2 p.m.
Lunch
2
–
2:45 p.m.
High-dimensional Scaling Limits of Least-square Online SGD Iterates and Its Fluctuations
Krishnakumar Balasubramanian (UC Davis)
2:45
–
3:30 p.m.
Lower Bounds for Sampling: Dimension Two and Gaussians
Sinho Chewi (Massachusetts Institute of Technology)
3:30
–
4 p.m.
Break
4
–
5 p.m.
Reception
Wednesday, Jan. 11, 2023
9
–
9:30 a.m.
Coffee and Check In
9:30
–
10:15 a.m.
Feature Learning in Two-layer Neural Networks
Murat Erdogdu (University of Toronto)
10:15
–
11 a.m.
Score-based Generative Modeling: Convergence Theory
Holden Lee (Duke University)
11
–
11:30 a.m.
Break
11:30 a.m.
–
12:15 p.m.
TBA
Augusto Gerolin (University of Ottawa)
12:15
–
2 p.m.
Lunch
2
–
2:45 p.m.
The Ensemble Kalman Filter in the Near-Gaussian Setting
Franca Hoffmann (California Institute of Technology)
2:45
–
3:30 p.m.
Geometric Methods in Private Convex Optimization
Kevin Tian (Microsoft Research)
3:30
–
5 p.m.
Break + Discussion
Thursday, Jan. 12, 2023
9
–
9:30 a.m.
Coffee and Check In
9:30
–
10:15 a.m.
Geometry Aware Exploratory Data Analysis
Paromita Dubey (Stanford)
10:15
–
11 a.m.
A Proximal Algorithm for Sampling
Yongxin Chen (Georgia Institute of Technology)
11
–
11:30 a.m.
Break
11:30 a.m.
–
12:15 p.m.
Analysis of Adversarial Robustness and of Other Problems in Modern Machine Learning
Nicolas Garcia Trillos (University of Wisconsin Madison)
12:15
–
2 p.m.
Lunch
2
–
2:45 p.m.
The Geometry of Adversarial Training - Nonlocal Regularization and Gamma-Convergence
Leon Bungert (University of Bonn)
2:45
–
3:30 p.m.
TBA
Aram-Alexandre Pooladian (New York University)
3:30
–
5 p.m.
Break + Discussion
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