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Julian Katz-Samuels
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2020 – today
- 2024
- [c17]Julian Katz-Samuels, Zheng Li, Hyokun Yun, Priyanka Nigam, Yi Xu, Vaclav Petricek, Bing Yin, Trishul Chilimbi:
Evolutionary Contrastive Distillation for Language Model Alignment. EMNLP (Findings) 2024: 5328-5345 - [c16]Haoyue Bai, Yifei Ming, Julian Katz-Samuels, Yixuan Li:
HYPO: Hyperspherical Out-Of-Distribution Generalization. ICLR 2024 - [i12]Yifei Ming, Haoyue Bai, Julian Katz-Samuels, Yixuan Li:
HYPO: Hyperspherical Out-of-Distribution Generalization. CoRR abs/2402.07785 (2024) - [i11]Julian Katz-Samuels, Zheng Li, Hyokun Yun, Priyanka Nigam, Yi Xu, Vaclav Petricek, Bing Yin, Trishul Chilimbi:
Evolutionary Contrastive Distillation for Language Model Alignment. CoRR abs/2410.07513 (2024) - 2022
- [c15]Cody Coleman, Edward Chou, Julian Katz-Samuels, Sean Culatana, Peter Bailis, Alexander C. Berg, Robert D. Nowak, Roshan Sumbaly, Matei Zaharia, I. Zeki Yalniz:
Similarity Search for Efficient Active Learning and Search of Rare Concepts. AAAI 2022: 6402-6410 - [c14]Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak:
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. AISTATS 2022: 6735-6769 - [c13]Julian Katz-Samuels, Julia B. Nakhleh, Robert D. Nowak, Yixuan Li:
Training OOD Detectors in their Natural Habitats. ICML 2022: 10848-10865 - [c12]Jifan Zhang, Julian Katz-Samuels, Robert D. Nowak:
GALAXY: Graph-based Active Learning at the Extreme. ICML 2022: 26223-26238 - [i10]Jifan Zhang, Julian Katz-Samuels, Robert D. Nowak:
GALAXY: Graph-based Active Learning at the Extreme. CoRR abs/2202.01402 (2022) - [i9]Julian Katz-Samuels, Julia B. Nakhleh, Robert Nowak, Yixuan Li:
Training OOD Detectors in their Natural Habitats. CoRR abs/2202.03299 (2022) - 2021
- [c11]Andrew Wagenmaker, Julian Katz-Samuels, Kevin G. Jamieson:
Experimental Design for Regret Minimization in Linear Bandits. AISTATS 2021: 3088-3096 - [c10]Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels:
High-dimensional Experimental Design and Kernel Bandits. ICML 2021: 1227-1237 - [c9]Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson:
Improved Algorithms for Agnostic Pool-based Active Classification. ICML 2021: 5334-5344 - [c8]Julian Katz-Samuels, Blake Mason, Kevin G. Jamieson, Robert Nowak:
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers. NeurIPS 2021: 17801-17812 - [i8]Romain Camilleri, Julian Katz-Samuels, Kevin G. Jamieson:
High-Dimensional Experimental Design and Kernel Bandits. CoRR abs/2105.05806 (2021) - [i7]Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson:
Improved Algorithms for Agnostic Pool-based Active Classification. CoRR abs/2105.06499 (2021) - [i6]Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak:
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. CoRR abs/2109.05131 (2021) - [i5]Julian Katz-Samuels, Blake Mason, Kevin Jamieson, Robert D. Nowak:
Practical, Provably-Correct Interactive Learning in the Realizable Setting: The Power of True Believers. CoRR abs/2111.04915 (2021) - 2020
- [c7]Julian Katz-Samuels, Kevin G. Jamieson:
The True Sample Complexity of Identifying Good Arms. AISTATS 2020: 1781-1791 - [c6]Julian Katz-Samuels, Lalit Jain, Zohar Karnin, Kevin G. Jamieson:
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits. NeurIPS 2020 - [i4]Julian Katz-Samuels, Lalit Jain, Zohar Karnin, Kevin G. Jamieson:
An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits. CoRR abs/2006.11685 (2020) - [i3]Andrew Wagenmaker, Julian Katz-Samuels, Kevin G. Jamieson:
Experimental Design for Regret Minimization in Linear Bandits. CoRR abs/2011.00576 (2020)
2010 – 2019
- 2019
- [j1]Julian Katz-Samuels, Gilles Blanchard, Clayton Scott:
Decontamination of Mutual Contamination Models. J. Mach. Learn. Res. 20: 41:1-41:57 (2019) - [c5]Julian Katz-Samuels, Clayton Scott:
Top Feasible Arm Identification. AISTATS 2019: 1593-1601 - [i2]Julian Katz-Samuels, Kevin G. Jamieson:
The True Sample Complexity of Identifying Good Arms. CoRR abs/1906.06594 (2019) - 2018
- [c4]Julian Katz-Samuels, Clayton Scott:
Nonparametric Preference Completion. AISTATS 2018: 632-641 - [c3]Julian Katz-Samuels, Clayton Scott:
Feasible Arm Identification. ICML 2018: 2540-2548 - [c2]Dejiao Zhang, Julian Katz-Samuels, Mário A. T. Figueiredo, Laura Balzano
:
Simultaneous Sparsity and Parameter Tying for Deep Learning Using Ordered Weighted ℓ1 Regularization. SSP 2018: 65-69 - 2017
- [i1]Julian Katz-Samuels, Clayton Scott:
Nonparametric Preference Completion. CoRR abs/1705.08621 (2017) - 2016
- [c1]Matthew Burgess, Eugenia Giraudy, Julian Katz-Samuels, Joe Walsh, Derek Willis, Lauren Haynes, Rayid Ghani:
The Legislative Influence Detector: Finding Text Reuse in State Legislation. KDD 2016: 57-66
Coauthor Index
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