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LDA*: A Robust and Large-scale Topic Modeling System

Summary: Systematic study of samplers (AliasLDA, F+LDA, LightLDA, WarpLDA) with a hybrid, document-length–aware approach for robust, large-scale topic modeling. Asymmetric parameter-server architecture shifts computation to the server, reduces communication bottlenecks in large deployments, delivering up to 10x gains over prior systems. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11425
Venue
VLDB
Year
2017
Pagerank
4.1945683e-05
Overall Rank
11,795 | 17.95%
DOI
-

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
328 An Architecture for Parallel Topic Models 2010 VLDB 0.0002728514
1,942 Heterogeneity-aware Distributed Parameter Servers 2017 SIGMOD 0.00010012691
6,014 WarpLDA: a Cache Efficient O(1) Algorithm for Latent Dirichlet Allocation 2016 VLDB 5.2415551e-05
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