Julian Katz-Samuels

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 28

Top Topics

Active Learning

Sample Complexity

Pac Learnability

Experimental Designs

Top Venues

Publications

Haoyue Bai, Yifei Ming, Julian Katz-Samuels, Yixuan Li
HYPO: Hyperspherical Out-of-Distribution Generalization. CoRR (2024)
Haoyue Bai, Yifei Ming, Julian Katz-Samuels, Yixuan Li
HYPO: Hyperspherical Out-Of-Distribution Generalization. ICLR (2024)
Jifan Zhang, Julian Katz-Samuels, Robert D. Nowak
GALAXY: Graph-based Active Learning at the Extreme. CoRR (2022)
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)
Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. AISTATS (2022)
Jifan Zhang, Julian Katz-Samuels, Robert D. Nowak
GALAXY: Graph-based Active Learning at the Extreme. ICML (2022)
Julian Katz-Samuels, Julia Nakhleh, Robert Nowak, Yixuan Li
Training OOD Detectors in their Natural Habitats. CoRR (2022)
Julian Katz-Samuels, Julia B. Nakhleh, Robert D. Nowak, Yixuan Li
Training OOD Detectors in their Natural Habitats. ICML (2022)
Romain Camilleri, Kevin Jamieson, Julian Katz-Samuels
High-dimensional Experimental Design and Kernel Bandits. ICML (2021)
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson
Improved Algorithms for Agnostic Pool-based Active Classification. ICML (2021)
Yinglun Zhu, Julian Katz-Samuels, Robert D. Nowak
Near Instance Optimal Model Selection for Pure Exploration Linear Bandits. CoRR (2021)
Andrew Wagenmaker, Julian Katz-Samuels, Kevin G. Jamieson
Experimental Design for Regret Minimization in Linear Bandits. AISTATS (2021)
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 (2021)
Romain Camilleri, Julian Katz-Samuels, Kevin G. Jamieson
High-Dimensional Experimental Design and Kernel Bandits. CoRR (2021)
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)
Julian Katz-Samuels, Jifan Zhang, Lalit Jain, Kevin Jamieson
Improved Algorithms for Agnostic Pool-based Active Classification. CoRR (2021)
Julian Katz-Samuels, Kevin G. Jamieson
The True Sample Complexity of Identifying Good Arms. AISTATS (2020)
Andrew Wagenmaker, Julian Katz-Samuels, Kevin G. Jamieson
Experimental Design for Regret Minimization in Linear Bandits. CoRR (2020)
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 (2020)
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)
Julian Katz-Samuels, Gilles Blanchard, Clayton Scott
Decontamination of Mutual Contamination Models. J. Mach. Learn. Res. 20 (2019)
Julian Katz-Samuels, Clayton Scott
Top Feasible Arm Identification. AISTATS (2019)
Julian Katz-Samuels, Kevin G. Jamieson
The True Sample Complexity of Identifying Good Arms. CoRR (2019)
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)
Julian Katz-Samuels, Clayton Scott
Feasible Arm Identification. ICML (2018)
Julian Katz-Samuels, Clayton Scott
Nonparametric Preference Completion. AISTATS (2018)
Julian Katz-Samuels, Clayton Scott
Nonparametric Preference Completion. CoRR (2017)
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)