7 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.IR2021★ 1 cited
Lessons Learned Addressing Dataset Bias in Model-Based Candidate Generation at Twitter
Alim Virani, Jay Baxter, Dan Shiebler +7
Traditionally, heuristic methods are used to generate candidates for large scale recommender systems. Model-based candidate generation promises multiple potential advantages, prima…
cs.LG2020★ 7 cited
Amazon SageMaker Autopilot: a white box AutoML solution at scale
Piali Das, Valerio Perrone, Nikita Ivkin +22
AutoML systems provide a black-box solution to machine learning problems by selecting the right way of processing features, choosing an algorithm and tuning the hyperparameters of…
cs.LG2020★ 7 cited
DropCluster: A structured dropout for convolutional networks
Liyan Chen, Philippos Mordohai, Sergul Aydore
Dropout as a common regularizer to prevent overfitting in deep neural networks has been less effective in convolutional layers than in fully connected layers. This is because Dropo…