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Name: Approximately Correct Machine Intelligence (ACMI) Lab

Type: Organization

Bio: Research on machine learning, its social impacts, and applications to healthcare. PI—@zackchase

Twitter: acmi_lab

Blog: http://acmilab.org/

Approximately Correct Machine Intelligence (ACMI) Lab's Projects

chils icon chils

Code and results accompanying our paper titled CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets

imp-regularizers icon imp-regularizers

Official implementation for the ICLR 2023 paper: Disentangling the Mechanisms Behind Implicit Regularization in SGD.

latent-label-shift-ddfa icon latent-label-shift-ddfa

Code and results accompanying our paper titled Unsupervised Learning under Latent Label Shift at NeurIPS 2022

missingness-shift icon missingness-shift

Code accompanying our paper "Domain Adaptation under Missingness Shift" at AISTATS 2023.

mvp icon mvp

Official Repository for the paper "Model-tuning Via Prompts Makes NLP Models More Robust"

onlinelabelshift icon onlinelabelshift

Code accompanying our paper titled Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms

open-set-label-shift icon open-set-label-shift

Code and results accompanying our paper titled Domain Adaptation under Open Set Label Shift

pu_learning icon pu_learning

Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotlight)

ratt_generalization_bound icon ratt_generalization_bound

Code and results accompanying our paper titled RATT: Leveraging Unlabeled Data to guarantee generalization at ICML 2021 (Long Talk)

rlsbench icon rlsbench

Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift

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