Workshops

The Convergence of Big Data and Extreme Simulation

Data-Driven Multifidelity Methods for Monte Carlo Estimation and Beyond

Detecting psychiatric disorders with statistical learning tailored to brain activity

Numerical Laboratories: the Road to Exascale

Public Lecture - Green Family Lecture Series: “Sailing Through Data: Discoveries and Mirages”

Sparse grids and their impact on HPC and Big Data

Manifold learning by sparse grid methods

Numerical data mining with sparse grids at extreme scale

Big Data Meets Large-Scale Visualization

Extreme Data Management Analysis and Visualization for Exascale Supercomputers and Experimental Facilities

Importance Sampling in High Dimensions via Hashing

Non-linear dimension reduction in the age of big data

Is non-convex optimization really hard? A couple of recent stories

A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression

Randomized projection methods for reducing communication in matrix computations

Model Inversion and Data Assimilation for Decision-Making in an Uncertain but Data-Rich World

Scalable algorithms for optimal training data for Bayesian inference of large scale models

Converged Ecosystem for Data Analytics and Extreme-Scale Computing

Ray: A System for Distributed AI

Public Lecture - Green Family Lecture Series: “The Knockoffs Framework: New Statistical Tools for Replicable Selections”

A Stochastic Generator of Global Monthly Wind Energy with Tukey g-and-h Autoregressive Processes

Optimization Methods for Large Scale Distributed Deep Learning

Probabilistic data fusion and physics-informed machine learning: A new paradigm for modeling and computation under uncertainty