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09/13/2022
Test-Time Adaptation with Principal Component Analysis
Machine Learning models are prone to fail when test data are different f...
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07/27/2022
Towards Clear Expectations for Uncertainty Estimation
If Uncertainty Quantification (UQ) is crucial to achieve trustworthy Mac...
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06/21/2022
Performance Prediction Under Dataset Shift
ML models deployed in production often have to face unknown domain chang...
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05/25/2021
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query Shift
Few-Shot Learning (FSL) algorithms have made substantial progress in lea...
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12/03/2020
Stochastic Adversarial Gradient Embedding for Active Domain Adaptation
Unsupervised Domain Adaptation (UDA) aims to bridge the gap between a so...
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06/25/2020
Target Consistency for Domain Adaptation: when Robustness meets Transferability
Learning Invariant Representations has been successfully applied for rec...
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06/24/2020
Robust Domain Adaptation: Representations, Weights and Inductive Bias
Unsupervised Domain Adaptation (UDA) has attracted a lot of attention in...
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07/29/2019
Learning Invariant Representations for Sentiment Analysis: The Missing Material is Datasets
Learning representations which remain invariant to a nuisance factor has...
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07/29/2019