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20182021
most citedExtreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products

16 citations · 18 across the 2 of their papers we have counts for

collaborators

5 papers

cs.DS20212 cited

Fast Parallel Algorithms for Euclidean Minimum Spanning Tree and Hierarchical Spatial Clustering

Yiqiu Wang, Shangdi Yu, Yan Gu +1

This paper presents new parallel algorithms for generating Euclidean minimum spanning trees and spatial clustering hierarchies (known as HDBSCAN). Our approach is based on gene…

cs.DS2020

A Parallel Batch-Dynamic Data Structure for the Closest Pair Problem

Yiqiu Wang, Shangdi Yu, Yan Gu +1

We propose a theoretically-efficient and practical parallel batch-dynamic data structure for the closest pair problem. Our solution is based on a serial dynamic closest pair data s…

cs.DS2019

Theoretically-Efficient and Practical Parallel DBSCAN

Yiqiu Wang, Yan Gu, Julian Shun

The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks. There are fast sequential algorithms for D…

cs.LG201916 cited

Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M Products

Tharun Medini, Qixuan Huang, Yiqiu Wang +2

In the last decade, it has been shown that many hard AI tasks, especially in NLP, can be naturally modeled as extreme classification problems leading to improved precision. However…

cs.DC2018

Extreme Classification in Log Memory

Qixuan Huang, Yiqiu Wang, Tharun Medini +1

We present Merged-Averaged Classifiers via Hashing (MACH) for K-classification with ultra-large values of K. Compared to traditional one-vs-all classifiers that require O(Kd) memor…