Search Results for author: Devin Guillory

Found 6 papers, 3 papers with code

Pyramid Mini-Batching for Optimal Transport

no code implementations29 Sep 2021 Devin Guillory, Kuniaki Saito, Eric Tzeng, Yannik Pitcan, Kate Saenko, Trevor Darrell

Optimal transport theory provides a useful tool to measure the differences between two distributions.

Domain Adaptation

Predicting with Confidence on Unseen Distributions

no code implementations ICCV 2021 Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt

Our work connects techniques from domain adaptation and predictive uncertainty literature, and allows us to predict model accuracy on challenging unseen distributions without access to labeled data.

Domain Adaptation

Self-Supervised Pretraining Improves Self-Supervised Pretraining

1 code implementation23 Mar 2021 Colorado J. Reed, Xiangyu Yue, Ani Nrusimha, Sayna Ebrahimi, Vivek Vijaykumar, Richard Mao, Bo Li, Shanghang Zhang, Devin Guillory, Sean Metzger, Kurt Keutzer, Trevor Darrell

Through experimentation on 16 diverse vision datasets, we show HPT converges up to 80x faster, improves accuracy across tasks, and improves the robustness of the self-supervised pretraining process to changes in the image augmentation policy or amount of pretraining data.

Image Augmentation

Combating Anti-Blackness in the AI Community

no code implementations18 Jun 2020 Devin Guillory

In response to a national and international awakening on the issues of anti-Blackness and systemic discrimination, we have penned this piece to serve as a resource for allies in the AI community who are wondering how they can more effectively engage with dismantling racist systems.

Computers and Society I.2.0

An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy

2 code implementations4 Nov 2017 Kamelia Aryafar, Devin Guillory, Liangjie Hong

In this paper, we provide a holistic view of Etsy's promoted listings' CTR prediction system and propose an ensemble learning approach which is based on historical or behavioral signals for older listings as well as content-based features for new listings.

Click-Through Rate Prediction Ensemble Learning

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