18 citations · 112 across the 31 of their papers we have counts for
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Methods for Estimation of Convex Sets
Victor-Emmanuel Brunel
In the framework of shape constrained estimation, we review methods and works done in convex set estimation. These methods mostly build on stochastic and convex geometry, empirical…
Rates of estimation for determinantal point processes
Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet +1
Determinantal point processes (DPPs) have wide-ranging applications in machine learning, where they are used to enforce the notion of diversity in subset selection problems. Many e…
Uniform deviation and moment inequalities for random polytopes with general densities in arbitrary convex bodies
Victor-Emmanuel Brunel
We prove an exponential deviation inequality for the convex hull of a finite sample of i.i.d. random points with a density supported on an arbitrary convex body in , $d\geq 2…
Learning Determinantal Point Processes with Moments and Cycles
John Urschel, Victor-Emmanuel Brunel, Ankur Moitra +1
Determinantal Point Processes (DPPs) are a family of probabilistic models that have a repulsive behavior, and lend themselves naturally to many tasks in machine learning where retu…
Maximum likelihood estimation of determinantal point processes
Victor-Emmanuel Brunel, Ankur Moitra, Philippe Rigollet +1
Determinantal point processes (DPPs) have wide-ranging applications in machine learning, where they are used to enforce the notion of diversity in subset selection problems. Many e…