Rohan Anil

TF-Ranking

2019

Learning-to-Rank deals with maximizing the utility of a list of examples presented to the user, with items of higher relevance being prioritized. It has several practical applications such as large-scale search, recommender systems, document summarization …

Large scale distributed neural network training through online\n distillation

2018 · arXiv (Cornell University)

Techniques such as ensembling and distillation promise model quality\nimprovements when paired with almost any base model. However, due to increased\ntest-time cost (for ensembles) and increased complexity of the training\npipeline (for distillation), these techniques are challenging …

Wide & Deep Learning for Recommender Systems

2016 · arXiv (Cornell University)

Generalized linear models with nonlinear feature transformations are widely used for large-scale regression and classification problems with sparse inputs. Memorization of feature interactions through a wide set of cross-product feature transformations are effective and interpretable, …

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

2019 · arXiv (Cornell University)

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models are composed of modular building blocks that are flexible and easily extensible, …

Gemini: A Family of Highly Capable Multimodal Models

2023 · arXiv (Cornell University)

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging …