382 citations · 978 across the 50 of their papers we have counts for
7 papers · 1 filter
Solving Games with Functional Regret Estimation
Kevin Waugh, Dustin Morrill, J. Andrew Bagnell +1
We propose a novel online learning method for minimizing regret in large extensive-form games. The approach learns a function approximator online to estimate the regret for choosin…
Vision and Learning for Deliberative Monocular Cluttered Flight
Debadeepta Dey, Kumar Shaurya Shankar, Sam Zeng +6
Cameras provide a rich source of information while being passive, cheap and lightweight for small and medium Unmanned Aerial Vehicles (UAVs). In this work we present the first impl…
A Unified View of Large-scale Zero-sum Equilibrium Computation
Kevin Waugh, J. Andrew Bagnell
The task of computing approximate Nash equilibria in large zero-sum extensive-form games has received a tremendous amount of attention due mainly to the Annual Computer Poker Compe…
Visual Chunking: A List Prediction Framework for Region-Based Object Detection
Nicholas Rhinehart, Jiaji Zhou, Martial Hebert +1
We consider detecting objects in an image by iteratively selecting from a set of arbitrarily shaped candidate regions. Our generic approach, which we term visual chunking, reasons…
Efficient Feature Group Sequencing for Anytime Linear Prediction
Hanzhang Hu, Alexander Grubb, J. Andrew Bagnell +1
We consider \textit{anytime} linear prediction in the common machine learning setting, where features are in groups that have costs. We achieve anytime (or interruptible) predictio…
Reinforcement and Imitation Learning via Interactive No-Regret Learning
Stephane Ross, J. Andrew Bagnell
Recent work has demonstrated that problems-- particularly imitation learning and structured prediction-- where a learner's predictions influence the input-distribution it is tested…
Near Optimal Bayesian Active Learning for Decision Making
Shervin Javdani, Yuxin Chen, Amin Karbasi +3
How should we gather information to make effective decisions? We address Bayesian active learning and experimental design problems, where we sequentially select tests to reduce unc…