
Variable Skipping for Autoregressive Range Density Estimation
Deep autoregressive models compute point likelihood estimates of individ...
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NeuroCard: One Cardinality Estimator for All Tables
Query optimizers rely on accurate cardinality estimates to produce good ...
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Evaluating Protein Transfer Learning with TAPE
Protein modeling is an increasingly popular area of machine learning res...
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Selectivity Estimation with Deep Likelihood Models
Selectivity estimation has long been grounded in statistical tools for d...
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Flow++: Improving FlowBased Generative Models with Variational Dequantization and Architecture Design
Flowbased generative models are powerful exact likelihood models with e...
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Variance Reduction for Policy Gradient with ActionDependent Factorized Baselines
Policy gradient methods have enjoyed great success in deep reinforcement...
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Some Considerations on Learning to Explore via MetaReinforcement Learning
We consider the problem of exploration in meta reinforcement learning. T...
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ModelEnsemble TrustRegion Policy Optimization
Modelfree reinforcement learning (RL) methods are succeeding in a growi...
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Stochastic Neural Networks for Hierarchical Reinforcement Learning
Deep reinforcement learning has achieved many impressive results in rece...
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OneShot Imitation Learning
Imitation learning has been commonly applied to solve different tasks in...
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Adversarial Attacks on Neural Network Policies
Machine learning classifiers are known to be vulnerable to inputs malici...
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#Exploration: A Study of CountBased Exploration for Deep Reinforcement Learning
Countbased exploration algorithms are known to perform nearoptimally w...
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RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning
Deep reinforcement learning (deep RL) has been successful in learning so...
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Variational Lossy Autoencoder
Representation learning seeks to expose certain aspects of observed data...
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InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
This paper describes InfoGAN, an informationtheoretic extension to the ...
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VIME: Variational Information Maximizing Exploration
Scalable and effective exploration remains a key challenge in reinforcem...
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