5 citations · 14 across the 12 of their papers we have counts for
8 papers · 1 filter
Welfarist Formulations for Diverse Similarity Search
Siddharth Barman, Nirjhar Das, Shivam Gupta +1
Nearest Neighbor Search (NNS) is a fundamental problem in data structures with wide-ranging applications, such as web search, recommendation systems, and, more recently, retrieval-…
Graph-Based Algorithms for Diverse Similarity Search
Piyush Anand, Piotr Indyk, Ravishankar Krishnaswamy +4
Nearest neighbor search is a fundamental data structure problem with many applications in machine learning, computer vision, recommendation systems and other fields. Although the m…
Instance Based Approximations to Profile Maximum Likelihood
Nima Anari, Moses Charikar, Kirankumar Shiragur +1
In this paper we provide a new efficient algorithm for approximately computing the profile maximum likelihood (PML) distribution, a prominent quantity in symmetric property estimat…
The Bethe and Sinkhorn Permanents of Low Rank Matrices and Implications for Profile Maximum Likelihood
Nima Anari, Moses Charikar, Kirankumar Shiragur +1
In this paper we consider the problem of computing the likelihood of the profile of a discrete distribution, i.e., the probability of observing the multiset of element frequencies,…
A General Framework for Symmetric Property Estimation
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
In this paper we provide a general framework for estimating symmetric properties of distributions from i.i.d. samples. For a broad class of symmetric properties we identify the eas…
Efficient Profile Maximum Likelihood for Universal Symmetric Property Estimation
Moses Charikar, Kirankumar Shiragur, Aaron Sidford
Estimating symmetric properties of a distribution, e.g. support size, coverage, entropy, distance to uniformity, are among the most fundamental problems in algorithmic statistics.…