Fanny Yang
29 papers · 2017–2025 · 8 conferences · across top CS/AI conferences
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ICML (6)
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Keywords
hypothesis testing
(2)
false discovery rate
(2)
lower bound
(2)
adversarial training
(2)
sample complexity
(2)
causal inference
(2)
high-dimensional analysis
(2)
early stopping
(2)
kernel methods
(2)
differential privacy
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semi-supervised learning
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self-supervised learning
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logistic regression
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ensemble learning
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algorithmic fairness
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domain generalization
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relational reasoning
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online learning
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robust optimization
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minimax optimization
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Papers
Learning Pareto manifolds in high dimensions: How can regularization help?
AISTATS 2025
Copyright-Protected Language Generation via Adaptive Model Fusion
ICLR 2025
Doubly robust identification of treatment effects from multiple environments
ICLR 2025
Achievable distributional robustness when the robust risk is only partially identified
NIPS 2024
Robust Mixture Learning when Outliers Overwhelm Small Groups
NIPS 2024
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent
ICML 2024
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces
ICML 2024
Detecting critical treatment effect bias in small subgroups
UAI 2024
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials
AISTATS 2024
Certified private data release for sparse Lipschitz functions
AISTATS 2024
Tight bounds for maximum $\ell_1$-margin classifiers
ALT 2024
Strong inductive biases provably prevent harmless interpolation
ICLR 2023
Why adversarial training can hurt robust accuracy
ICLR 2023
Can semi-supervised learning use all the data effectively? A lower bound perspective
NIPS 2023
Margin-based sampling in high dimensions: When being active is less efficient than staying passive
ICML 2023
Semi-supervised novelty detection using ensembles with regularized disagreement
UAI 2022
Tight bounds for minimum $\ell_1$-norm interpolation of noisy data
AISTATS 2022
How unfair is private learning?
UAI 2022
Fast rates for noisy interpolation require rethinking the effect of inductive bias
ICML 2022
How rotational invariance of common kernels prevents generalization in high dimensions
ICML 2021
Interpolation can hurt robust generalization even when there is no noise
NIPS 2021
Self-supervised Reinforcement Learning with Independently Controllable Subgoals
CORL 2021
Understanding and Mitigating the Tradeoff between Robustness and Accuracy
ICML 2020
Regularized Learning for Domain Adaptation under Label Shifts
ICLR 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness
NIPS 2019
Statistical and Computational Guarantees for the Baum-Welch Algorithm
JMLR 2017
Online control of the false discovery rate with decaying memory
NIPS 2017
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control
NIPS 2017
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
NIPS 2017