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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators

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Outbound references

Observation c121f8cf-ee29-4682-ae06-cb0ef307d133 · outbound

This paper cites Quionero-Candela, M.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Quionero-Candela, M

Reference 1

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Observation 2bc97599-120a-4a00-af2b-90b8842e2d52 · outbound

This paper cites A survey on transfer learning,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators A survey on transfer learning,

Reference 2

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Observation 554ef6ef-d4f9-46f6-a307-46f4615eeba9 · outbound

This paper cites Improving predictive inference under covariate shift by weighting the log-likelihood function,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Improving predictive inference under covariate shift by weighting the log-likelihood function,

Reference 3

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Observation 9083d577-0530-4f10-a5a2-be021c61c699 · outbound

This paper cites Covariate shift adaptation by importance weighted cross valida- tion,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Covariate shift adaptation by importance weighted cross valida- tion,

Reference 4

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Observation b0e40973-c855-4050-9415-55cc65993f9c · outbound

This paper cites What is the effect of impor- tance weighting in deep learning?.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators What is the effect of impor- tance weighting in deep learning?

Reference 5

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Observation 2a115c9a-8150-4f42-9466-454bdca959b7 · outbound

This paper cites Rethinking importance weighting for deep learning under distribu- tion shift,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Rethinking importance weighting for deep learning under distribu- tion shift,

Reference 6

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Observation 65ff5f3e-31b7-4757-973e-2990d21ec005 · outbound

This paper cites Correcting sample selection bias by unla- beled data,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Correcting sample selection bias by unla- beled data,

Reference 7

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Observation 5b99452f-3f14-4568-bc2a-6d1260a45742 · outbound

This paper cites GPU acceler- ation of ADMM for large-scale quadratic programming,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators GPU acceler- ation of ADMM for large-scale quadratic programming,

Reference 8

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Observation 32ab55ce-bff4-4432-881c-e38b6febb756 · outbound

This paper cites Direct importance estimation with model selection and its application to covariate shift adaptation,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Direct importance estimation with model selection and its application to covariate shift adaptation,

Reference 9

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This paper cites A least-squares approach to direct importance estimation,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators A least-squares approach to direct importance estimation,

Reference 10

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This paper cites Density- ratio matching under the Bregman divergence: a unified framework of density-ratio estimation,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Density- ratio matching under the Bregman divergence: a unified framework of density-ratio estimation,

Reference 11

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This paper cites The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming,

Reference 12

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Observation 33f2a151-6f88-41bb-b75b-47934bd1a6e7 · outbound

This paper cites Im- portance weighting for aligning language models under deployment distribution shift,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Im- portance weighting for aligning language models under deployment distribution shift,

Reference 13

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Importance-weighted positive-unlabeled learning for distribution shift adaptation,

Reference 14

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Constrained minimiza- tion methods,

Reference 15

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This paper cites Integral probability metrics and their gener- ating classes of functions,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Integral probability metrics and their gener- ating classes of functions,

Reference 16

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators A general class of coefficients of divergence of one distribution from another,

Reference 17

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Markov processes over denumerable products of spaces describing large system of automata,

Reference 18

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Observation fc3d2cd2-a148-4f05-a019-2ac4c21f0a27 · outbound

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators On choosing and bound- ing probability metrics,

Reference 19

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This paper cites Integrating structured biological data by kernel maximum mean discrepancy,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Integrating structured biological data by kernel maximum mean discrepancy,

Reference 20

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators A kernel two-sample test,

Reference 21

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Hilbert space em- beddings and metrics on probability measures,

Reference 22

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Kernel measures of conditional dependence,

Reference 23

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators On information and suf- ficiency,

Reference 24

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Neue begr¨ undung der theorie quadratischer formen von unendlichvielen ver¨anderlichen

Reference 25

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Confliction of the convexity and metric properties in f-divergences,

Reference 26

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators The earth mover’s distance as a metric for image retrieval,

Reference 27

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Villani,Topics in optimal transportation, ser

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Wasserstein generative adversarial networks,

Reference 29

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Improved training of Wasserstein GANs,

Reference 30

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Learning multiple layers of features from tiny images,

Reference 32

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators ImageNet Large Scale Visual Recognition Challenge,

Reference 33

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Gradient-based learning applied to document recogni- tion,

Reference 34

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators A stochastic approximation method,

Reference 35

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Deep residual learning for image recognition,

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Observation c733fb40-d136-496e-93c8-de0b42b48ce1 · outbound

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Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Adam: A method for stochas- tic optimization,

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Observation 10e8d7e9-5cdf-4841-99da-9b218a452ae8 · outbound

This paper cites Learn- ing to reweight examples for robust deep learning,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Learn- ing to reweight examples for robust deep learning,

Reference 38

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Observation 6cce8ef8-1722-44fc-bece-c61cf0bddf0f · outbound

This paper cites Meta-weight-net: Learning an explicit mapping for sample weighting,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Meta-weight-net: Learning an explicit mapping for sample weighting,

Reference 39

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Observation 22658f4b-8d7c-4ece-8978-8250edc3754e · outbound

This paper cites A systematic study of the class imbalance problem in convolutional neural networks,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators A systematic study of the class imbalance problem in convolutional neural networks,

Reference 40

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Observation c642a414-87f4-445a-ae71-0daf01832332 · outbound

This paper cites Co-teaching: Robust training of deep neural networks with extremely noisy labels,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Co-teaching: Robust training of deep neural networks with extremely noisy labels,

Reference 41

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Observation 8d119926-eaf4-4f2f-acdc-648f227dbfe7 · outbound

This paper cites Learning with symmetric label noise: The importance of being unhinged,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Learning with symmetric label noise: The importance of being unhinged,

Reference 42

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Observation 34ce986f-ead1-4b05-9861-5ca61210812b · outbound

This paper cites Learning under concept drift: A review,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Learning under concept drift: A review,

Reference 43

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Observation 9b8747e6-9bf9-47d1-9bea-2bedc774adfb · outbound

This paper cites an unresolved cited work.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Unresolved cited work

Reference 44

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Observation 0e1eeb4f-1cdd-4066-91d0-1713de31d356 · outbound

This paper cites Deep visual domain adaptation: A survey,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Deep visual domain adaptation: A survey,

Reference 45

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Observation 2cbc1c02-f770-4e8a-b157-a206499951b7 · outbound

This paper cites Learning transferable features with deep adaptation networks,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Learning transferable features with deep adaptation networks,

Reference 46

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Observation 362683b3-ccd0-4d0c-9caf-ca5090367e81 · outbound

This paper cites Domain-adversarial training of neural networks,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Domain-adversarial training of neural networks,

Reference 47

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Observation ac2af9ae-e356-4c73-8404-8267fc4222f9 · outbound

This paper cites Adver- sarial discriminative domain adaptation,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Adver- sarial discriminative domain adaptation,

Reference 48

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Observation 9f9304c0-dbc7-4e84-8f44-8f00bcab1ea9 · outbound

This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural net- works,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Pseudo-label: The simple and efficient semi-supervised learning method for deep neural net- works,

Reference 49

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Observation f33af81c-03d1-4cc3-8d3b-6b2e93798ed0 · outbound

This paper cites Asymmetric tri- training for unsupervised domain adaptation,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Asymmetric tri- training for unsupervised domain adaptation,

Reference 50

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Observation 5ebbc3da-f848-4fbc-82e7-bd02640d30d3 · outbound

This paper cites Stochastic first-and zeroth-order methods for nonconvex stochastic programming,.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Stochastic first-and zeroth-order methods for nonconvex stochastic programming,

Reference 51

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Observation 1b0e3681-920a-4b03-9701-11d6239cee02 · outbound

This paper cites Handbook of Convergence Theorems for (Stochastic) Gradient Methods.

Accelerated Dynamic Importance Weighting with Versatile Divergence-Minimizing Estimators Handbook of Convergence Theorems for (Stochastic) Gradient Methods

Reference 52

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