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Conference and Workshop Papers
- 2024
[c11]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:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. ACL (Findings) 2024: 6549-6560- 2023
- [c10]Mark Rucker, Yinglun Zhu, Paul Mineiro:
Infinite Action Contextual Bandits with Reusable Data Exhaust. ICML 2023: 29259-29274 - 2022
- [c9]Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak:
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. AISTATS 2022: 6735-6769 - [c8]Yinglun Zhu, Robert D. Nowak:
Pareto Optimal Model Selection in Linear Bandits. AISTATS 2022: 6793-6813 - [c7]Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro:
Contextual Bandits with Large Action Spaces: Made Practical. ICML 2022: 27428-27453 - [c6]Yinglun Zhu, Paul Mineiro:
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces. ICML 2022: 27574-27590 - [c5]Yinglun Zhu, Robert Nowak:
Active Learning with Neural Networks: Insights from Nonparametric Statistics. NeurIPS 2022 - [c4]Yinglun Zhu, Robert Nowak:
Efficient Active Learning with Abstention. NeurIPS 2022 - 2021
- [c3]Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert Nowak:
Pure Exploration in Kernel and Neural Bandits. NeurIPS 2021: 11618-11630 - 2020
- [c2]Yinglun Zhu, Sumeet Katariya, Robert D. Nowak:
Robust Outlier Arm Identification. ICML 2020: 11566-11575 - [c1]Yinglun Zhu, Robert Nowak:
On Regret with Multiple Best Arms. NeurIPS 2020
Informal and Other Publications
- 2024
- [i14]Gantavya Bhatt, Yifang Chen, Arnav Mohanty Das, Jifan Zhang, Sang T. Truong, Stephen Mussmann, Yinglun Zhu, Jeffrey A. Bilmes, Simon S. Du, Kevin G. Jamieson, Jordan T. Ash, Robert D. Nowak:
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models. CoRR abs/2401.06692 (2024) - [i13]Dingyang Chen, Qi Zhang, Yinglun Zhu:
Efficient Sequential Decision Making with Large Language Models. CoRR abs/2406.12125 (2024) - 2023
- [i12]Mark Rucker, Yinglun Zhu, Paul Mineiro:
Infinite Action Contextual Bandits with Reusable Data Exhaust. CoRR abs/2302.08551 (2023) - [i11]Jifan Zhang, Yifang Chen, Gregory Canal, Stephen Mussmann, Yinglun Zhu, Simon Shaolei Du, Kevin G. Jamieson, Robert D. Nowak:
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning. CoRR abs/2306.09910 (2023) - 2022
- [i10]Yinglun Zhu, Robert D. Nowak:
Efficient Active Learning with Abstention. CoRR abs/2204.00043 (2022) - [i9]Yinglun Zhu, Dylan J. Foster, John Langford, Paul Mineiro:
Contextual Bandits with Large Action Spaces: Made Practical. CoRR abs/2207.05836 (2022) - [i8]Yinglun Zhu, Paul Mineiro:
Contextual Bandits with Smooth Regret: Efficient Learning in Continuous Action Spaces. CoRR abs/2207.05849 (2022) - [i7]Yinglun Zhu, Robert D. Nowak:
Active Learning with Neural Networks: Insights from Nonparametric Statistics. CoRR abs/2210.08367 (2022) - 2021
- [i6]Yinglun Zhu, Robert D. Nowak:
Pareto Optimal Model Selection in Linear Bandits. CoRR abs/2102.06593 (2021) - [i5]Yinglun Zhu, Dongruo Zhou, Ruoxi Jiang, Quanquan Gu, Rebecca Willett, Robert D. Nowak:
Pure Exploration in Kernel and Neural Bandits. CoRR abs/2106.12034 (2021) - [i4]Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak:
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. CoRR abs/2109.05131 (2021) - 2020
- [i3]Yinglun Zhu, Robert D. Nowak:
On Regret with Multiple Best Arms. CoRR abs/2006.14785 (2020) - [i2]Yinglun Zhu, Sumeet Katariya, Robert Nowak:
Robust Outlier Arm Identification. CoRR abs/2009.09988 (2020) - 2017
- [i1]Jiefeng Chen, Zihang Meng, Changtian Sun, Wei Tang, Yinglun Zhu:
ReabsNet: Detecting and Revising Adversarial Examples. CoRR abs/1712.08250 (2017)
Coauthor Index
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