conftrace_

importance weighting

59 papers

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Also known as

IW

Co-occurring keywords

domain adaptation (4595) distribution shift (722) covariate shift (157) variational inference (2069) contextual bandit (381) importance sampling (318) active learning (1301) off-policy evaluation (144) causal inference (1630) regret bound (1926)

Papers

An Importance Weighted Feature Selection Stability Measure JMLR 2021
Designing Transportable Experiments Under S-admissability AISTATS 2021
Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting AISTATS 2021
Mandoline: Model Evaluation under Distribution Shift ICML 2021
Active Learning under Label Shift AISTATS 2021
f-Divergence Variational Inference NIPS 2020
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization NIPS 2020
Misspelling Detection from Noisy Product Images COLING 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift NIPS 2020
Simulator Calibration under Covariate Shift with Kernels AISTATS 2020
A One-step Approach to Covariate Shift Adaptation ACML 2020
Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation AISTATS 2020
Q* Approximation Schemes for Batch Reinforcement Learning: A Theoretical Comparison UAI 2020
Policy Evaluation with Latent Confounders via Optimal Balance NIPS 2019
What is the Effect of Importance Weighting in Deep Learning? ICML 2019
Imitation Learning from Imperfect Demonstration ICML 2019
Deep Gaussian Processes with Importance-Weighted Variational Inference ICML 2019
The Label Complexity of Active Learning from Observational Data NIPS 2019
Detecting Overfitting via Adversarial Examples NIPS 2019
Covariate Shift Adaptation on Learning from Positive and Unlabeled Data AAAI 2019
Importance Weighted Adversarial Nets for Partial Domain Adaptation CVPR 2018
Robust Active Label Correction AISTATS 2018
Importance Weighting and Variational Inference NIPS 2018
Chi-square Generative Adversarial Network ICML 2018
Importance Weighted Transfer of Samples in Reinforcement Learning ICML 2018