Bridging Domain Expertise and Generalization for Performance Estimation | Paper Citation Record

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This paper cites Zico Kolter.

Bridging Domain Expertise and Generalization for Performance Estimation Zico Kolter

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This paper cites On the Opportunities and Risks of Foundation Models.

Bridging Domain Expertise and Generalization for Performance Estimation On the Opportunities and Risks of Foundation Models

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This paper cites Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, and Christopher R´e.

Bridging Domain Expertise and Generalization for Performance Estimation Chen, Karan Goel, Nimit Sharad Sohoni, Fait Poms, Kayvon Fatahalian, and Christopher R´e

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Bridging Domain Expertise and Generalization for Performance Estimation Unresolved cited work

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This paper cites Christie, Neil Fendley, James Wilson, and Ryan Mukherjee.

Bridging Domain Expertise and Generalization for Performance Estimation Christie, Neil Fendley, James Wilson, and Ryan Mukherjee

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This paper cites Confidence and dispersity speak: Characterising prediction matrix for unsupervised accuracy estimation.

Bridging Domain Expertise and Generalization for Performance Estimation Confidence and dispersity speak: Characterising prediction matrix for unsupervised accuracy estimation

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This paper cites Barrett, Yi Xiang, Miguel Romero Calvo, Anna Currey, and Xing Niu.

Bridging Domain Expertise and Generalization for Performance Estimation Barrett, Yi Xiang, Miguel Romero Calvo, Anna Currey, and Xing Niu

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This paper cites Data determines distributional robustness in contrastive language image pre-training (CLIP).

Bridging Domain Expertise and Generalization for Performance Estimation Data determines distributional robustness in contrastive language image pre-training (CLIP)

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Bridging Domain Expertise and Generalization for Performance Estimation Lempitsky

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This paper cites Leveraging unla- beled data to predict out-of-distribution performance.

Bridging Domain Expertise and Generalization for Performance Estimation Leveraging unla- beled data to predict out-of-distribution performance

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This paper cites Predicting with confidence on unseen distributions.

Bridging Domain Expertise and Generalization for Performance Estimation Predicting with confidence on unseen distributions

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Bridging Domain Expertise and Generalization for Performance Estimation Weinberger

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This paper cites Deep residual learning for image recognition.

Bridging Domain Expertise and Generalization for Performance Estimation Deep residual learning for image recognition

Reference 13

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This paper cites Sample selection bias as a specification error.Econometrica, 47(1):153–161, 1979.

Bridging Domain Expertise and Generalization for Performance Estimation Sample selection bias as a specification error.Econometrica, 47(1):153–161, 1979

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This paper cites A baseline for detect- ing misclassified and out-of-distribution examples in neural networks.

Bridging Domain Expertise and Generalization for Performance Estimation A baseline for detect- ing misclassified and out-of-distribution examples in neural networks

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This paper cites The many faces of robustness: A critical analysis of out-of-distribution generalization.

Bridging Domain Expertise and Generalization for Performance Estimation The many faces of robustness: A critical analysis of out-of-distribution generalization

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Bridging Domain Expertise and Generalization for Performance Estimation Weinberger

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Bridging Domain Expertise and Generalization for Performance Estimation Unresolved cited work

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Observation c0049616-16d6-4a6d-b226-edeca0411c25 · outbound

This paper cites Zico Kolter.

Bridging Domain Expertise and Generalization for Performance Estimation Zico Kolter

Reference 19

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This paper cites Domain adaptation without source data.IEEE Trans.

Bridging Domain Expertise and Generalization for Performance Estimation Domain adaptation without source data.IEEE Trans

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This paper cites Haque, Sara M.

Bridging Domain Expertise and Generalization for Performance Estimation Haque, Sara M

Reference 21

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This paper cites Learning multiple lay- ers of features from tiny images.

Bridging Domain Expertise and Generalization for Performance Estimation Learning multiple lay- ers of features from tiny images

Reference 22

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This paper cites V ., and R.

Bridging Domain Expertise and Generalization for Performance Estimation V ., and R

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This paper cites Gradient-based learning applied to document recog- nition.Proc.

Bridging Domain Expertise and Generalization for Performance Estimation Gradient-based learning applied to document recog- nition.Proc

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This paper cites Confidence score for source-free unsupervised domain adap- tation.

Bridging Domain Expertise and Generalization for Performance Estimation Confidence score for source-free unsupervised domain adap- tation

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This paper cites Model adaptation: Unsupervised domain adaptation without source data.

Bridging Domain Expertise and Generalization for Performance Estimation Model adaptation: Unsupervised domain adaptation without source data

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This paper cites Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation.

Bridging Domain Expertise and Generalization for Performance Estimation Do we really need to access the source data? source hypothesis transfer for unsupervised domain adaptation

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This paper cites Divergence measures based on the shannon entropy.IEEE Trans.

Bridging Domain Expertise and Generalization for Performance Estimation Divergence measures based on the shannon entropy.IEEE Trans

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Bridging Domain Expertise and Generalization for Performance Estimation Unresolved cited work

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This paper cites Harder or different? a closer look at distribution shift in dataset reproduction.

Bridging Domain Expertise and Generalization for Performance Estimation Harder or different? a closer look at distribution shift in dataset reproduction

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Bridging Domain Expertise and Generalization for Performance Estimation Unresolved cited work

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This paper cites Revisiting the calibration of modern neural net- works.

Bridging Domain Expertise and Generalization for Performance Estimation Revisiting the calibration of modern neural net- works

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This paper cites Reading digits in natural images with unsupervised feature learning.

Bridging Domain Expertise and Generalization for Performance Estimation Reading digits in natural images with unsupervised feature learning

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This paper cites A survey on transfer learn- ing.IEEE Trans.

Bridging Domain Expertise and Generalization for Performance Estimation A survey on transfer learn- ing.IEEE Trans

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Bridging Domain Expertise and Generalization for Performance Estimation The entropy enigma: Success and failure of en- tropy minimization

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This paper cites Development and application of a metric on semantic nets.

Bridging Domain Expertise and Generalization for Performance Estimation Development and application of a metric on semantic nets

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This paper cites Learning transferable visual models from natural language supervision.

Bridging Domain Expertise and Generalization for Performance Estimation Learning transferable visual models from natural language supervision

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This paper cites Do CIFAR-10 Classifiers Generalize to CIFAR-10?.

Bridging Domain Expertise and Generalization for Performance Estimation Do CIFAR-10 Classifiers Generalize to CIFAR-10?

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This paper cites Do imagenet classifiers generalize to im- agenet? InInternational Conference on Machine Learning (ICML), pages 5389–5400, 2019.

Bridging Domain Expertise and Generalization for Performance Estimation Do imagenet classifiers generalize to im- agenet? InInternational Conference on Machine Learning (ICML), pages 5389–5400, 2019

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This paper cites Can contrastive learning avoid shortcut solutions? InAdvances in Neural Information Processing Systems (NeurIPS), pages 4974–4986, 2021.

Bridging Domain Expertise and Generalization for Performance Estimation Can contrastive learning avoid shortcut solutions? InAdvances in Neural Information Processing Systems (NeurIPS), pages 4974–4986, 2021

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Bridging Domain Expertise and Generalization for Performance Estimation Distance matters for improving performance estimation under covariate shift

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Bridging Domain Expertise and Generalization for Performance Estimation (almost) provable er- ror bounds under distribution shift via disagreement discrep- ancy

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Bridging Domain Expertise and Generalization for Performance Estimation Bernstein, Alexander C

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Bridging Domain Expertise and Generalization for Performance Estimation BREEDS: benchmarks for subpopulation shift

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Bridging Domain Expertise and Generalization for Performance Estimation Hoffmann, Max Argus, V olker Fis- cher, and Thomas Brox

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Bridging Domain Expertise and Generalization for Performance Estimation Improving predictive inference under covariate shift by weighting the log-likelihood function.J

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Bridging Domain Expertise and Generalization for Performance Estimation Sculley, Joshua V

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Bridging Domain Expertise and Generalization for Performance Estimation Proxy denoising for source-free domain adaptation

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Bridging Domain Expertise and Generalization for Performance Estimation A closer look at the robustness of contrastive language-image pre-training (CLIP)

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Bridging Domain Expertise and Generalization for Performance Estimation Deep Domain Confusion: Maximizing for Domain Invariance

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Bridging Domain Expertise and Generalization for Performance Estimation Adversarial discriminative domain adaptation

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Bridging Domain Expertise and Generalization for Performance Estimation Representation Learning with Contrastive Predictive Coding

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Bridging Domain Expertise and Generalization for Performance Estimation Lipton, and Eric P

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Bridging Domain Expertise and Generalization for Performance Estimation Understanding contrastive representation learning through alignment and uniformity on the hypersphere

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Bridging Domain Expertise and Generalization for Performance Estimation Verb semantics and lexical selection

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Bridging Domain Expertise and Generalization for Performance Estimation Hovy, and Quoc V

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This paper cites On the importance of feature separability in predicting out-of-distribution error.

Bridging Domain Expertise and Generalization for Performance Estimation On the importance of feature separability in predicting out-of-distribution error

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This paper cites Cold case: The lost MNIST digits.

Bridging Domain Expertise and Generalization for Performance Estimation Cold case: The lost MNIST digits

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This paper cites How transferable are features in deep neural networks? InAd- vances in Neural Information Processing Systems (NeurIPS), pages 3320–3328, 2014.

Bridging Domain Expertise and Generalization for Performance Estimation How transferable are features in deep neural networks? InAd- vances in Neural Information Processing Systems (NeurIPS), pages 3320–3328, 2014

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Bridging Domain Expertise and Generalization for Performance Estimation Predicting out-of-distribution error with the projection norm

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Bridging Domain Expertise and Generalization for Performance Estimation Sigmoid loss for language image pre-training

Reference 62

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Bridging Domain Expertise and Generalization for Performance Estimation Unresolved cited work

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This paper cites Average Confidence (AC).THe AC baseline directly esti- mates the target error by computing the average of one minus the maximum softmax confidence over the unlabeled target samples.

Bridging Domain Expertise and Generalization for Performance Estimation Average Confidence (AC).THe AC baseline directly esti- mates the target error by computing the average of one minus the maximum softmax confidence over the unlabeled target samples

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