HET: scaling out huge embedding model training via cache-enabled distributed framework
Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …
However, one open issue of embedding models is that their representations (latent factors) …
[PDF][PDF] HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework
X Miao, H Zhang, Y Shi, X Nie, Z Yang, Y Tao, B Cui - vldb.org
Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …
However, one open issue of embedding models is that their representations (latent factors) …
HET: scaling out huge embedding model training via cache-enabled distributed framework
X Miao, H Zhang, Y Shi, X Nie, Z Yang, Y Tao… - Proceedings of the …, 2021 - dl.acm.org
Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …
However, one open issue of embedding models is that their representations (latent factors) …
HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework
X Miao, H Zhang, Y Shi, X Nie, Z Yang, Y Tao… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …
However, one open issue of embedding models is that their representations (latent factors) …
[PDF][PDF] HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework
X Miao, H Zhang, Y Shi, X Nie, Z Yang, Y Tao, B Cui - hsword.github.io
Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …
However, one open issue of embedding models is that their representations (latent factors) …
[PDF][PDF] HET: Scaling out Huge Embedding Model Training via Cache-enabled Distributed Framework
X Miao, H Zhang, Y Shi, X Nie, Z Yang, Y Tao, B Cui - vldb.org
Embedding models have been an effective learning paradigm for high-dimensional data.
However, one open issue of embedding models is that their representations (latent factors) …
However, one open issue of embedding models is that their representations (latent factors) …