Yinglun Zhu

According to our database, Yinglun Zhu authored at least 15 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Efficient Sparse PCA via Block-Diagonalization.

Alberto Del Pia, Dekun Zhou, Yinglun Zhu

CoRR, 2024

Efficient Sequential Decision Making with Large Language Models.

Dingyang Chen, Qi Zhang, Yinglun Zhu

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.

Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeff A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning.

Jifan Zhang, Yifang Chen, Gregory Canal, Stephen Mussmann, Yinglun Zhu, Simon Shaolei Du, Kevin G. Jamieson, Robert D. Nowak

CoRR, 2023

Infinite Action Contextual Bandits with Reusable Data Exhaust.

Mark Rucker, Yinglun Zhu, Paul Mineiro

Proceedings of the International Conference on Machine Learning, 2023

2022

Efficient Active Learning with Abstention.

Yinglun Zhu, Robert Nowak

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Active Learning with Neural Networks: Insights from Nonparametric Statistics.

Yinglun Zhu, Robert Nowak

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces.

Yinglun Zhu, Paul Mineiro

Proceedings of the International Conference on Machine Learning, 2022

Contextual Bandits with Large Action Spaces: Made Practical.

Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro

Proceedings of the International Conference on Machine Learning, 2022

Pareto Optimal Model Selection in Linear Bandits.

Yinglun Zhu, Robert D. Nowak

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Near Instance Optimal Model Selection for Pure Exploration Linear Bandits.

Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Pure Exploration in Kernel and Neural Bandits.

Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

On Regret with Multiple Best Arms.

Yinglun Zhu, Robert Nowak

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Robust Outlier Arm Identification.

Yinglun Zhu, Sumeet Katariya, Robert D. Nowak

Proceedings of the 37th International Conference on Machine Learning, 2020

2017

ReabsNet: Detecting and Revising Adversarial Examples.

Jiefeng Chen, Zihang Meng, Changtian Sun, Wei Tang, Yinglun Zhu

CoRR, 2017