Search Results for author:
Found 6 papers, 3 papers with code
Pyramid Mini-Batching for Optimal Transport
Optimal transport theory provides a useful tool to measure the differences between two distributions.
Predicting with Confidence on Unseen Distributions
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.
Self-Supervised Pretraining Improves Self-Supervised Pretraining
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.
Combating Anti-Blackness in the AI Community
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
Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning
Weakly-supervised action localization requires training a model to localize the action segments in the video given only video level action label.
Ranked #8 on
Weakly Supervised Action Localization
on THUMOS’14
An Ensemble-based Approach to Click-Through Rate Prediction for Promoted Listings at Etsy
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.
