Statistical Learning
Using Embeddings to Correct for Unobserved Confounding in Networks
Victor Veitch, Yixin Wang, David Blei
We consider causal inference in the presence of unobserved confounding.
Estimating Convergence of Markov chains with L-Lag Couplings
Niloy Biswas, Pierre E. Jacob, Paul Vanetti
Neural Information Processing Systems http://nips.cc/
Fast Parallel Algorithms for Statistical Subset Selection Problems
Neural Information Processing Systems http://nips.cc/
This Looks Like That: Deep Learning for Interpretable Image Recognition
Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, Jonathan K. Su
Neural Information Processing Systems http://nips.cc/
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
Neural Information Processing Systems http://nips.cc/
A unified variance-reduced accelerated gradient method for convex optimization
Guanghui Lan, Zhize Li, Yi Zhou
We propose a novel randomized incremental gradient algorithm, namely, V Ariance-Reduced Accelerated Gradient ( Varag), for finite-sum optimization.
Nonparametric Contextual Bandits in Metric Spaces with Unknown Metric
Nirandika Wanigasekara, Christina Yu
The decision maker must select an action based on the context and all past observations.
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Cross-sectional Learning of Extremal Dependence among Financial Assets
We show its flexible tail dependence structure through simulation.