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04/30/2023
Reliable Gradient-free and Likelihood-free Prompt Tuning
Due to privacy or commercial constraints, large pre-trained language mod...
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04/27/2023
On the Generalization Error of Meta Learning for the Gibbs Algorithm
We analyze the generalization ability of joint-training meta learning al...
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12/14/2022
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model
It is known that neural networks have the problem of being over-confiden...
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02/24/2022
Tighter Expected Generalization Error Bounds via Convexity of Information Measures
Generalization error bounds are essential to understanding machine learn...
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02/01/2022
On the Benefits of Selectivity in Pseudo-Labeling for Unsupervised Multi-Source-Free Domain Adaptation
Due to privacy, storage, and other constraints, there is a growing need ...
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11/02/2021
Characterizing and Understanding the Generalization Error of Transfer Learning with Gibbs Algorithm
We provide an information-theoretic analysis of the generalization abili...
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07/28/2021
Characterizing the Generalization Error of Gibbs Algorithm with Symmetrized KL information
Bounding the generalization error of a supervised learning algorithm is ...
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12/30/2020
A Maximal Correlation Approach to Imposing Fairness in Machine Learning
As machine learning algorithms grow in popularity and diversify to many ...
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11/13/2018
