Andrew Wagenmaker

Andrew Wagenmaker 

Andrew Wagenmaker
Paul G. Allen School of Computer Science & Engineering
University of Washington

ajwagen@cs.washington.edu
Office: CSE2 231
Gates Center for Computer Science & Engineering
University of Washington
Seattle, WA 98195


I am a fourth-year Ph.D. student in Computer Science at the University of Washington working with Kevin Jamieson. My research interests are in active learning, reinforcement learning, and control theory. I am supported by an NSF Graduate Research Fellowship.

Previously, I completed a master's and bachelor's degree at the University of Michigan, both in Electrical Engineering. While at the University of Michigan, I worked with Raj Rao Nadakuditi and Necmiye Ozay.

Preprints

Beyond No Regret: Instance-Dependent PAC Reinforcement Learning
Andrew Wagenmaker, Max Simchowitz, and Kevin Jamieson
Preprint, 2021.

Publications

Task-Optimal Exploration in Linear Dynamical Systems
Andrew Wagenmaker, Max Simchowitz, and Kevin Jamieson
ICML, 2021 (Long Talk).

Experimental Design for Regret Minimization in Linear Bandits
Andrew Wagenmaker*, Julian Katz-Samuels*, and Kevin Jamieson
AISTATS, 2021.

Active Learning for Identification of Linear Dynamical Systems
Andrew Wagenmaker and Kevin Jamieson
COLT, 2020.

Robust Photometric Stereo via Dictionary Learning
Andrew Wagenmaker, Brian Moore, and Raj Rao Nadakuditi
IEEE Transactions on Computational Imaging, 2018.

Robust Photometric Stereo Using Learned Image and Gradient Dictionaries
Andrew Wagenmaker, Brian Moore, and Raj Rao Nadakuditi 
IEEE International Conference on Image Processing (ICIP), 2017.

Robust Surface Reconstruction from Gradients via Adaptive Dictionary Regularization
Andrew Wagenmaker, Brian Moore, and Raj Rao Nadakuditi
IEEE International Conference on Image Processing (ICIP), 2017.

A Bisimulation-Like Algorithm for Abstracting Control Systems
Andrew Wagenmaker and Necmiye Ozay
Allerton Conference on Communication, Control, and Computing, 2016.