conftrace_

Fanny Yang

29 papers · 2017–2025 · 8 conferences · across top CS/AI conferences

Achievements

Jump to papers ↓
+11 more ↓ 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) πŸ—ΊοΈ Taxonomy Completionist (11) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (8)
πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (11) πŸ‘‘ Triple Crown πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (29) ⚑ Prolific Year (8) ❓ The Questioner (3) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (114)

Conferences

NIPS (8) ICML (6) ICLR (5) AISTATS (4) UAI (3) ALT (1) CORL (1) JMLR (1)

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