Huijun Yu

Mar 27, 2024 | amazon.science | Shuai Zhang |Huijun Yu |Xiangkun Hu |Dongyu Ru

We introduce a prompt pre-training method POMP, which fisrt enables prompt learning on large-scale datasets like ImageNet-21K with over twenty-thousand classes. POMP is memory and computation efficient. Compared with previous methods like CoOp, it achieves comparable accuracy on ImageNet-1K with only 19% GPU memory and 50% training time. POMP achieves new SOTAs on various open-vocabulary visual recognition datasets and tasks.

Mar 27, 2024 | amazon.science | Jacek R. Golebiowski |Philipp Schmidt |Artur Bekasov |Huijun Yu

This repository contains code for evaluating the methods proposed in Learning action embeddings for off-policy evaluation. To get started, we recommend checking the Example.ipynb notebook as it clearly demonstrates benefits of the proposed method from Section 3 and implements everything in a few lines of code. To run the notebook, you only need python 3 with standard machine learning libraries.

Jan 23, 2024 | amazon.science | Yu Liu |Huijun Yu |Xiangkun Hu |Dongyu Ru

This package contains the Hierarchical Bayesian model to predict sample size for online activity. The bang package (https://cran.rstudio.com/web/packages/bang/index.html) was used and accelerated by modifying it to use sufficient statistics, and to only simulate from the posterior over the hyper-parameters. "misc.R", "beta_prior.R", "binom_beta.R", "hef.R" and "set_and_check_prior.R" are source files from bang packages (https://cran.rstudio.com/web/packages/bang/index.html).

Oct 20, 2023 | amazon.science | Arpit Gupta |Huijun Yu |Xiangkun Hu |Dongyu Ru

Amazon Fulfillment Planning & Execution (FPX) Science team within Supply Chain Optimization Technologies (SCOT) Fulfilment Optimization group is seeking a Principal Research Scientist with expertise in Machine Learning and a proven record of solving business problems through scalable ML solutions. Network Planning and Fulfillment Execution tackles some of the most mathematically complex challenges in facility and transportation planning to improve Amazon's operational efficiency worldwide.