Next time could you please read “A Mathematical Theory of Communication” by Claude Shannon because it’s a seminal paper and information theory is highly relevant to machine learning?
6 years ago (edited) | 2
Next time could you please read “A Mathematical Theory of Communication” by Claude Shannon because it’s a seminal paper and information theory is highly relevant to machine learning?
6 years ago (edited) | 2
Kaggle
Time to pick the next paper for the Kaggle reading group! Here are your choices:
> "Learning from Dialogue after Deployment: Feed Yourself, Chatbot!" (Hancock et al, 2019) was published at
ACL in 2019 & proposes a method for a dialog agent to continue to learn and update with user feedback. aclweb.org/anthology/P19-1358.pdf> "AutoML using Metadata Language Embeddings" (Drori et al, unpublished) proposes a method to augment existing AutoML systems by incorporating information from the text description of the dataset & description of possible algorithms to use. arxiv.org/pdf/1910.03698.pdf> "Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules" (Sanchez-Lengeling et al, unpublished) outline an approach to predicting the scent of a molecule given it's structure using graph neural networks. arxiv.org/pdf/1910.10685.pdf
6 years ago | [YT] | 32