529 citations · 2.8k across the 74 of their papers we have counts for
4 papers · 1 filter
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
Pratik Chaudhari, Anna Choromanska, Stefano Soatto +6
This paper proposes a new optimization algorithm called Entropy-SGD for training deep neural networks that is motivated by the local geometry of the energy landscape. Local extrema…
Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes
Carlo Baldassi, Christian Borgs, Jennifer Chayes +4
In artificial neural networks, learning from data is a computationally demanding task in which a large number of connection weights are iteratively tuned through stochastic-gradien…
Discovering Neuronal Cell Types and Their Gene Expression Profiles Using a Spatial Point Process Mixture Model
Furong Huang, Animashree Anandkumar, Christian Borgs +6
Cataloging the neuronal cell types that comprise circuitry of individual brain regions is a major goal of modern neuroscience and the BRAIN initiative. Single-cell RNA sequencing c…
Sparse exchangeable graphs and their limits via graphon processes
Christian Borgs, Jennifer T. Chayes, Henry Cohn +1
In a recent paper, Caron and Fox suggest a probabilistic model for sparse graphs which are exchangeable when associating each vertex with a time parameter in . Here w…