Flatiron Internal Conference: Flatiron-wide Algorithms and Mathematics

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Sessions*

Sampling Introductory Lecture

Welcome

Dimension Reduction and Factorization Short Talk

Optimization Introductory Lecture

Function Approximation and Differential Equations Introductory Lecture

Break

Optimization Short Talk

Sampling Short Talk

Dimension Reduction and Factorization Introductory Lecture

Deep Learning Introductory Lecture

Optimization Introductory Lecture 1

Deep Learning Short Talks

Function Approximation and Differential Equations Equations Short Talk

Elad Hazan

Optimization Introductory Lecture 1

Optimization Introductory Lecture 2

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Contributions*

A practical introduction to adjoint methods (in session "Optimization Short Talk")

Biological neural network algorithms (in session "Deep Learning Short Talks")

Clustering in low dimensions (in session "Dimension Reduction and Factorization Short Talk")

Deep Generative Modeling for Statistical and Quantum Physics (in session "Deep Learning Short Talks")

Fast algorithms for hierarchically structured matrices (in session "Dimension Reduction and Factorization Introductory Lecture")

Hierarchical Modeling and Stellar Velocities (in session "Sampling Short Talk")

Introduction to Deep Learning (in session "Deep Learning Introductory Lecture")

Introduction to Deep Learning (in session "Deep Learning Introductory Lecture")

Introduction to Integral Equation Methods (in session "Function Approximation and Differential Equations Equations Short Talk")

Introduction to interpolation, integration and spectral methods (in session "Function Approximation and Differential Equations Introductory Lecture")

Introduction to Markov chain Monte Carlo (in session "Sampling Introductory Lecture")

Introduction to Tensor Network Methods (in session "Dimension Reduction and Factorization Short Talk")

Optimization landscapes - a gentle multi-disciplinary introduction to optimization (in session "Optimization Introductory Lecture 1")

Overview of various methods to solve differential equations (in session "Function Approximation and Differential Equations Introductory Lecture")

PDEs: The long and the short. (in session "Function Approximation and Differential Equations Equations Short Talk")

Randomized linear algebra and matrix approximation (in session "Dimension Reduction and Factorization Short Talk")

Research Applications of Optimization: Data-Driven Spectroscopy (in session "Optimization Short Talk")

Scalable Bayesian Inference. (in session "Sampling Introductory Lecture")

Spectral Clustering and Dimensionality Reduction (in session "Dimension Reduction and Factorization Short Talk")

The quantum-ness in quantum Monte Carlo: mathematical and algorithmic implications (in session "Sampling Short Talk")

The why and how of nonnegative matrix factorization (in session "Dimension Reduction and Factorization Short Talk")

Tutorial: Optimization for Machine Learning (in session "Optimization Introductory Lecture 2")

Uncertainty Estimation with Neural Networks (in session "Deep Learning Short Talks")

Wavelets (in session "Function Approximation and Differential Equations Equations Short Talk")

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Events scheduled on*

10/30/19

10/31/19

11/1/19

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