Search Results for author: Devin Guillory

Found 10 papers, 5 papers with code

Hyperbolic Active Learning for Semantic Segmentation under Domain Shift

1 code implementation19 Jun 2023 Luca Franco, Paolo Mandica, Konstantinos Kallidromitis, Devin Guillory, Yu-Teng Li, Trevor Darrell, Fabio Galasso

In HALO (Hyperbolic Active Learning Optimization), for the first time, we propose the use of epistemic uncertainty as a data acquisition strategy, following the intuition of selecting data points that are the least known.

Semantic Segmentation Source-Free Domain Adaptation

Using Language to Extend to Unseen Domains

1 code implementation18 Oct 2022 Lisa Dunlap, Clara Mohri, Devin Guillory, Han Zhang, Trevor Darrell, Joseph E. Gonzalez, aditi raghunathan, Anja Rohrbach

It is expensive to collect training data for every possible domain that a vision model may encounter when deployed.

Domain Adaptation

Studying Bias in GANs through the Lens of Race

no code implementations6 Sep 2022 Vongani H. Maluleke, Neerja Thakkar, Tim Brooks, Ethan Weber, Trevor Darrell, Alexei A. Efros, Angjoo Kanazawa, Devin Guillory

In this work, we study how the performance and evaluation of generative image models are impacted by the racial composition of their training datasets.

Disentangled Action Recognition with Knowledge Bases

no code implementations NAACL 2022 Zhekun Luo, Shalini Ghosh, Devin Guillory, Keizo Kato, Trevor Darrell, Huijuan Xu

In this paper, we aim to improve the generalization ability of the compositional action recognition model to novel verbs or novel nouns that are unseen during training time, by leveraging the power of knowledge graphs.

Action Recognition Knowledge Graphs

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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