George Tucker

According to our database1, George Tucker authored at least 24 papers between 2013 and 2018.

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Bibliography

2018
The Laplacian in RL: Learning Representations with Efficient Approximations.
CoRR, 2018

Doubly Reparameterized Gradient Estimators for Monte Carlo Objectives.
CoRR, 2018

Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion.
CoRR, 2018

Guided evolutionary strategies: escaping the curse of dimensionality in random search.
CoRR, 2018

Smoothed Action Value Functions for Learning Gaussian Policies.
CoRR, 2018

The Mirage of Action-Dependent Baselines in Reinforcement Learning.
CoRR, 2018

Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling.
CoRR, 2018

The Mirage of Action-Dependent Baselines in Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Smoothed Action Value Functions for Learning Gaussian Policies.
Proceedings of the 35th International Conference on Machine Learning, 2018

Learning Hard Alignments with Variational Inference.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models.
CoRR, 2017

Max-Pooling Loss Training of Long Short-Term Memory Networks for Small-Footprint Keyword Spotting.
CoRR, 2017

Regularizing Neural Networks by Penalizing Confident Output Distributions.
CoRR, 2017

Filtering Variational Objectives.
CoRR, 2017

Particle Value Functions.
CoRR, 2017

Learning Hard Alignments with Variational Inference.
CoRR, 2017

An online sequence-to-sequence model for noisy speech recognition.
CoRR, 2017

REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Filtering Variational Objectives.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Compacting Neural Network Classifiers via Dropout Training.
CoRR, 2016

Max-pooling loss training of long short-term memory networks for small-footprint keyword spotting.
Proceedings of the 2016 IEEE Spoken Language Technology Workshop, 2016

Model Compression Applied to Small-Footprint Keyword Spotting.
Proceedings of the Interspeech 2016, 2016

2014
Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach.
BMC Systems Biology, 2014

2013
A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.
BMC Bioinformatics, 2013


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