Approximately Correct Machine Intelligence (ACMI) Lab (acmi-lab)

Approximately Correct Machine Intelligence (ACMI) Lab

acmi-lab

Geek Repo

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

Home Page:http://acmilab.org/

Twitter:@acmi_lab

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Approximately Correct Machine Intelligence (ACMI) Lab's repositories

cmu-10717-the-art-of-the-paper

Official repository for CMU Machine Learning Department's 10717: "The Art of the Paper".

cmu-10721-philosophy-machine-intelligence

Official repository for CMU Machine Learning Department's 10721: "Philosophical Foundations of Machine Intelligence".

superheroes-deep-learning

Thrilling tales of heroic feats by ML's larger-than-life champions.

counterfactually-augmented-data

Learning the Difference that Makes a Difference with Counterfactually-Augmented Data

cmu-10732-robustness-adaptivity-shift

Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments

CHILS

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

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PU_learning

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

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RLSbench

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

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modular-summarization

code for modular summarization work published in ACL2021 by Krishna et al

Open-Set-Label-Shift

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

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papers-worth-reading

A Curated Set of Papers Actually Worth Reading

pretraining-with-nonsense

Pretraining summarization models using a corpus of nonsense

mvp

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

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local-causal-discovery

Code for the paper "Local Causal Discovery for Estimating Causal Effects".

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online-moment-selection

Code for the paper "Efficient Online Estimation of Causal Effects by Deciding What to Observe".

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RATT_generalization_bound

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

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EvaluationOverTime

Python package for Evaluating Medical Datasets Over Time (EMDOT).

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OnlineLabelShift

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

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imp-regularizers

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

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Latent-Label-Shift-DDFA

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

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Missingness-Shift

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

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