14 citations · 58 across the 43 of their papers we have counts for
4 papers · 1 filter
NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks
Sepanta Zeighami, Cyrus Shahabi, Vatsal Sharan
Range aggregate queries (RAQs) are an integral part of many real-world applications, where, often, fast and approximate answers for the queries are desired. Recent work has studied…
Efficient Convex Optimization Requires Superlinear Memory
Annie Marsden, Vatsal Sharan, Aaron Sidford +1
We show that any memory-constrained, first-order algorithm which minimizes -dimensional, -Lipschitz convex functions over the unit ball to accuracy using…
KL Divergence Estimation with Multi-group Attribution
Parikshit Gopalan, Nina Narodytska, Omer Reingold +2
Estimating the Kullback-Leibler (KL) divergence between two distributions given samples from them is well-studied in machine learning and information theory. Motivated by considera…
On the Statistical Complexity of Sample Amplification
Brian Axelrod, Shivam Garg, Yanjun Han +2
The ``sample amplification'' problem formalizes the following question: Given i.i.d. samples drawn from an unknown distribution , when is it possible to produce a larger set…