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no code implementations • ICML 2020 • Rohit Agrawal, Thibaut Horel

The families of f-divergences (e. g. the Kullback-Leibler divergence) and Integral Probability Metrics (e. g. total variation distance or maximum mean discrepancies) are commonly used in optimization and estimation.

no code implementations • 10 Jun 2020 • Rohit Agrawal, Thibaut Horel

The families of $f$-divergences (e. g. the Kullback-Leibler divergence) and Integral Probability Metrics (e. g. total variation distance or maximum mean discrepancies) are widely used to quantify the similarity between probability distributions.

no code implementations • NeurIPS 2016 • Thibaut Horel, Yaron Singer

We study the problem of maximizing a function that is approximately submodular under a cardinality constraint.

no code implementations • 4 Oct 2015 • Panos Toulis, Thibaut Horel, Edoardo M. Airoldi

Exact implementations of the proximal Robbins-Monro procedure are challenging, but we show that approximate implementations lead to procedures that are easy to implement, and still dominate classical procedures by achieving numerical stability, practically without tradeoffs.

no code implementations • 21 May 2015 • Jean Pouget-Abadie, Thibaut Horel

In the Network Inference problem, one seeks to recover the edges of an unknown graph from the observations of cascades propagating over this graph.

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