216 citations · 327 across the 10 of their papers we have counts for
Showing 2014Show all
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stat.ML2014★ 15 cited
LightLDA: Big Topic Models on Modest Compute Clusters
Jinhui Yuan, Fei Gao, Qirong Ho +6
When building large-scale machine learning (ML) programs, such as big topic models or deep neural nets, one usually assumes such tasks can only be attempted with industrial-sized c…
cs.DC2014★ 6 cited
Model-Parallel Inference for Big Topic Models
Xun Zheng, Jin Kyu Kim, Qirong Ho +1
In real world industrial applications of topic modeling, the ability to capture gigantic conceptual space by learning an ultra-high dimensional topical representation, i.e., the so…
stat.ML2014★ 15 cited
Primitives for Dynamic Big Model Parallelism
Seunghak Lee, Jin Kyu Kim, Xun Zheng +3
When training large machine learning models with many variables or parameters, a single machine is often inadequate since the model may be too large to fit in memory, while trainin…