Výsledky vyhledávání - "Yang, Xuelin"

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Dimension-free Private Mean Estimation for Anisotropic Distributions

Autor: Dagan, Yuval, Jordan, Michael I., Yang, Xuelin, Zakynthinou, Lydia, Zhivotovskiy, Nikita

We present differentially private algorithms for high-dimensional mean estimation. Previous private estimators on distributions over $\mathbb{R}^d$ suffer from a curse of dimensionality, as they require $\Omega(d^{1/2})$ samples to achieve non-trivia

Externí odkaz: http://arxiv.org/abs/2411.00775

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Fairness-Aware Meta-Learning via Nash Bargaining

Autor: Zeng, Yi, Yang, Xuelin, Chen, Li, Ferrer, Cristian Canton, Jin, Ming, Jordan, Michael I., Jia, Ruoxi

To address issues of group-level fairness in machine learning, it is natural to adjust model parameters based on specific fairness objectives over a sensitive-attributed validation set. Such an adjustment procedure can be cast within a meta-learning

Externí odkaz: http://arxiv.org/abs/2406.07029

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CLEVRER-Humans: Describing Physical and Causal Events the Human Way

Autor: Mao, Jiayuan, Yang, Xuelin, Zhang, Xikun, Goodman, Noah D., Wu, Jiajun

Building machines that can reason about physical events and their causal relationships is crucial for flexible interaction with the physical world. However, most existing physical and causal reasoning benchmarks are exclusively based on synthetically

Externí odkaz: http://arxiv.org/abs/2310.03635

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FastCPH: Efficient Survival Analysis for Neural Networks

Autor: Yang, Xuelin, Abraham, Louis, Kim, Sejin, Smirnov, Petr, Ruan, Feng, Haibe-Kains, Benjamin, Tibshirani, Robert

The Cox proportional hazards model is a canonical method in survival analysis for prediction of the life expectancy of a patient given clinical or genetic covariates -- it is a linear model in its original form. In recent years, several methods have

Externí odkaz: http://arxiv.org/abs/2208.09793

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ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time

Autor: Wu, Tailin, Tjandrasuwita, Megan, Wu, Zhengxuan, Yang, Xuelin, Liu, Kevin, Sosič, Rok, Leskovec, Jure

Humans have the remarkable ability to recognize and acquire novel visual concepts in a zero-shot manner. Given a high-level, symbolic description of a novel concept in terms of previously learned visual concepts and their relations, humans can recogn

Externí odkaz: http://arxiv.org/abs/2206.15049

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