Haiyang Huang

11 papers A* 3Journal 8
YearRankTypeTitle / Venue / Authors
2025 A* conf
Dimension Reduction with Locally Adjusted Graphs.
AAAI
Yingfan Wang, Yiyang Sun, Haiyang Huang, Cynthia Rudin
2025 J jnl
It's LIT! Reliability-Optimized LLMs with Inspectable Tools.
CoRR
Ruixin Zhang, Jon Donnelly, Zhicheng Guo, Ghazal Khalighinejad, Haiyang Huang, Alina Jade Barnett, Cynthia Rudin
2024 J jnl
Dimension Reduction with Locally Adjusted Graphs.
CoRR
Yingfan Wang, Yiyang Sun, Haiyang Huang, Cynthia Rudin
2024 A* conf
Navigating the Effect of Parametrization for Dimensionality Reduction.
NeurIPS
Haiyang Huang, Yingfan Wang, Cynthia Rudin
2024 J jnl
Navigating the Effect of Parametrization for Dimensionality Reduction.
CoRR
Haiyang Huang, Yingfan Wang, Cynthia Rudin
2024 A* conf
Toward Efficient Inference for Mixture of Experts.
NeurIPS
Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Shruti Bhosale, Hsien-Hsin S. Lee, Carole-Jean Wu, Benjamin Lee
2023 J jnl
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference.
CoRR
Haiyang Huang, Newsha Ardalani, Anna Y. Sun, Liu Ke, Hsien-Hsin S. Lee, Anjali Sridhar, Shruti Bhosale, Carole-Jean Wu, Benjamin Lee
2022 J jnl
SegDiscover: Visual Concept Discovery via Unsupervised Semantic Segmentation.
CoRR
Haiyang Huang, Zhi Chen, Cynthia Rudin
2021 J jnl
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges.
CoRR
Cynthia Rudin, Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong
2021 J jnl
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMap, and PaCMAP for Data Visualization.
J. Mach. Learn. Res.
Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik
2020 J jnl
Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization.
CoRR
Yingfan Wang, Haiyang Huang, Cynthia Rudin, Yaron Shaposhnik