Anoop Korattikara | DeepAI

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∙ 12/10/2019

Measuring the Reliability of Reinforcement Learning Algorithms

Lack of reliability is a well-known issue for reinforcement learning (RL...

34 Stephanie C. Y. Chan, et al. ∙

∙ 02/20/2019

From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following

Reinforcement learning is a promising framework for solving control prob...

6 Justin Fu, et al. ∙

∙ 11/30/2016

Speed/accuracy trade-offs for modern convolutional object detectors

The goal of this paper is to serve as a guide for selecting a detection ...

0 Jonathan Huang, et al. ∙

∙ 06/14/2015

Bayesian Dark Knowledge

We consider the problem of Bayesian parameter estimation for deep neural...

0 Anoop Korattikara, et al. ∙

∙ 03/05/2015

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

Despite having various attractive qualities such as high prediction accu...

0 Sungjin Ahn, et al. ∙

∙ 04/19/2013

Austerity in MCMC Land: Cutting the Metropolis-Hastings Budget

Can we make Bayesian posterior MCMC sampling more efficient when faced w...

0 Anoop Korattikara, et al. ∙

∙ 06/27/2012

Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring

In this paper we address the following question: Can we approximately sa...

0 Sungjin Ahn, et al. ∙

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