290 citations · 1.8k across the 59 of their papers we have counts for
4 papers · 2 filters
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…
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…
Optimal rates of estimation for multi-reference alignment
Afonso S. Bandeira, Philippe Rigollet, Jonathan Weed
In this paper, we establish optimal rates of adaptive estimation of a vector in the multi-reference alignment model, a problem with important applications in fields such as signal…
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…