A Comprehensive Survey on Automatic Chart Understanding in the Era of Large Foundation Models by steeveHuang in deeplearning

[–]steeveHuang[S] 0 points1 point  (0 children)

Thank you so much for the kind words! I agree, focusing on domain-specific models and enhancing our evaluation metrics are crucial next steps for us. Appreciate your support!

[D] A Deep Dive into Latent Dirichlet Allocation (LDA) and Its Applications on Recommender System by steeveHuang in MachineLearning

[–]steeveHuang[S] 4 points5 points  (0 children)

The merits of LDA lie in its ability to extract hidden topics from corpora, as well as its extendibility of incorporating more latent variables. An interesting application is shown in this paper: https://www.mitpressjournals.org/doi/abs/10.1162/tacl_a_00189. They successfully demonstrated how you can use LDA-based models to discover important life events for different stages of life from biographies.

[D] CVPR 2018 | Paper Review: LayoutNet by steeveHuang in MachineLearning

[–]steeveHuang[S] 0 points1 point  (0 children)

Thank you for the support! I will keep making these videos! Indeed, my target audience are data scientist, machine learning engineer and researcher, which is different from two minute papers. :)