Microsoft Research
Title: Asymptotics of learning on dependent and structured random objects |
MIT
Title: Machine learning and causality: Building efficient, reliable models for decision-making |
MSR
Title: Ideal made real: machine learning with limited data and interpretable outputs |
MIT
Title: VCBART: Bayesian trees for varying coefficients |
Berkeley, CMU
Title: Breaking the Sample Size Barrier in Reinforcement Learning |
Princeton University
Title: Demystifying the Sample Efficiency of (Deep) Reinforcement Learning |
University of Washington
Title: Positive AI with Social Commonsense Models |
MIT
Title: Bridging Estimation and Decision Making |
Toyota Technological Institute at Chicago
Title: New Advances in (Adversarially) Robust and Secure Machine Learning |
Princeton University.
Title: Taming Nonconvexity in Statistical and Reinforcement Learning |
Carnegie Mellon University
Title: Data-Driven Transfer of Insight between Brains and AI Systems |
Stanford University
Title: Mobility Networks for Modeling the Spread of COVID-19: Explaining infection rates and informing reopening strategies |
The Wharton School, University of Pennsylvania
Title: Semiparametric Proximal Causal Inference |
UC Berkeley
Title: Distribution-Free, Risk-Controlling Prediction Sets |
University of Washington
Title: Marginal and multivariate rank-based tests of independence |
UW Madison College of Letters & Science
Title: A modern take on Huber regression |
University of Chicago
Solving PDEs with Deep Learning |
University of Michigan
Title: From Diagnosis to Treatment - Augmenting Clinical Decision Making with Artificial Intelligence |
University of Washington
Title: Reinforcement Learning in High Dimensional Systems |
Department of Statistics at Columbia University
Title: Mean Field Approximation in Bayesian Linear Regression |
University of Pennsylvania
Title: DNA Copy Number Profiling from Bulk Tissues to Single Cells |
Yale University School of Medicine
Title: Big Data Analytics Applied to the Molecular Basis of Human Traits and Diseases |
Yale University
Title: Reaching consensus: the power of few |
New York University
Title: Towards practical estimation of Brenier maps |
Columbia University
Title: Deep Networks and the Multiple Manifold Problem |
EPFL
Title: Analysis of gradient descent on wide two-layer ReLU neural networks |
Yale University
Title: On Bias and Discretization: Sampling under Isoperimetry via Langevin Algorithm |
Stanford University
Title: Algorithmic Thresholds for Optimizing Mean-Field Spin Glasses |
Stanford University
Title: Kernel Thinning and Stein Thinning |
University of Chicago.
Title: Minimax rates for sparse signal detection under correlation |
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