Classification with Costly Features using Deep Reinforcement Learning

Reinforcement learning for robots using neural networks

L.-J. Lin · 1993

Earlier work this paper cites.

Cost-sensitive learning of classification knowledge and its applications in robotics

M. Tan · 1993

Earlier work this paper cites.

Learning multiple layers of features from tiny images

A. Krizhevsky and G. Hinton · 2009

Earlier work this paper cites.

Datum-wise classification: a sequential approach to sparsity

G. Dulac-Arnold, L. Denoyer, P. Preux, and P. Gallinari · 2011

Earlier work this paper cites.

The greedy miser: learning under test-time budgets

Z. Xu, K. Weinberger, and O. Chapelle · 2012

Earlier work this paper cites.

UCI machine learning repository, 2013

M. Lichman · 2013

Earlier work this paper cites.

Supervised sequential classification under budget constraints

K. Trapeznikov and V. Saligrama · 2013

Earlier work this paper cites.

Cost-sensitive tree of classifiers

Z. Xu, M. Kusner, K. Weinberger, and M. Chen · 2013

Earlier work this paper cites.

Feature-cost sensitive learning with submodular trees of classifiers

M. Kusner, W. Chen, Q. Zhou, Z. Xu, K. Weinberger, and Y. Chen · 2014

Cited alongside, same era.

Classifier cascades and trees for minimizing feature evaluation cost

Z. Xu, M. Kusner, K. Weinberger, M. Chen, and O. Chapelle · 2014

Cited alongside, same era.

Adam: A method for stochastic optimization

D. P. Kingma and J. Ba · 2015

Cited alongside, same era.

Human-level control through deep reinforcement learning

V. Mnih, K. Kavukcuoglu, D. Silver, A. A. Rusu, J. Veness, M. G. Bellemare, A. Graves, M. Riedmiller, A. K. Fidjeland, G. Ostrovski, et al · 2015

Cited alongside, same era.

Feature-budgeted random forest

F. Nan, J. Wang, and V. Saligrama · 2015

Cited alongside, same era.

Efficient learning by directed acyclic graph for resource constrained prediction

J. Wang, K. Trapeznikov, and V. Saligrama · 2015

Continuous control with deep reinforcement learning

T. P. Lillicrap, J. J. Hunt, A. Pritzel, N. Heess, T. Erez, Y. Tassa, D. Silver, and D. Wierstra · 2016

Later among the works it cites.

Safe and efficient off-policy reinforcement learning

R. Munos, T. Stepleton, A. Harutyunyan, and M. Bellemare · 2016

Later among the works it cites.

Pruning random forests for prediction on a budget

F. Nan, J. Wang, and V. Saligrama · 2016

Later among the works it cites.

Deep reinforcement learning with double q-learning

H. Van Hasselt, A. Guez, and D. Silver · 2016

Later among the works it cites.

Dueling network architectures for deep reinforcement learning

Z. Wang, T. Schaul, M. Hessel, H. Hasselt, M. Lanctot, and N. Freitas · 2016

Later among the works it cites.

Adaptive classification for prediction under a budget

F. Nan and V. Saligrama · 2017

Closest in time.