most citedWide & Deep Learning for Recommender Systems

263 citations · 395 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2019132 cited

TensorFlow.js: Machine Learning for the Web and Beyond

Daniel Smilkov, Nikhil Thorat, Yannick Assogba +17

TensorFlow.js is a library for building and executing machine learning algorithms in JavaScript. TensorFlow.js models run in a web browser and in the Node.js environment. The libra…

cs.HC2019

Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making

Carrie J. Cai, Emily Reif, Narayan Hegde +8

Machine learning (ML) is increasingly being used in image retrieval systems for medical decision making. One application of ML is to retrieve visually similar medical images from p…

cs.LG2016263 cited

Wide & Deep Learning for Recommender Systems

Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen +13

Generalized linear models with nonlinear feature transformations are widely used for large-scale regression and classification problems with sparse inputs. Memorization of feature…

cs.CL2016

Smart Reply: Automated Response Suggestion for Email

Anjuli Kannan, Karol Kurach, Sujith Ravi +8

In this paper we propose and investigate a novel end-to-end method for automatically generating short email responses, called Smart Reply. It generates semantically diverse suggest…

cs.DC2016

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham +37

TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed…