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Preference-based ReinforcementLearning withFinite-TimeGuarantees
Neural Information Processing Systems
Wefirstshowthataunique optimal policymaynot exist if preferences over trajectories are deterministic for PbRL.
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- North America > United States > Pennsylvania > Allegheny County > Pittsburgh (0.04)
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- Asia > Middle East > Jordan (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.84)
Preference-based Reinforcement Learning with Finite-Time Guarantees
Neural Information Processing Systems
We first show that a unique optimal policy may not exist if preferences over trajectories are deterministic for PbRL.
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- North America > United States > Pennsylvania > Allegheny County > Pittsburgh (0.04)
- North America > United States > California (0.04)
- North America > Canada (0.04)
- Asia > Middle East > Jordan (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (1.00)
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- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- Asia > China > Hong Kong (0.04)
- Oceania > Australia > Victoria > Melbourne (0.04)
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- Europe > Russia (0.04)
- Asia > Russia (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
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- North America > United States > New York > Broome County > Binghamton (0.04)
- North America > Canada (0.04)
- Asia > China (0.04)
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- Asia > China (0.04)
- North America > United States > New York > Broome County > Binghamton (0.04)
- North America > United States > Massachusetts > Hampshire County > Amherst (0.04)
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.48)
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- Europe > United Kingdom > England > Nottinghamshire > Nottingham (0.14)
- Asia > China > Guangdong Province > Shenzhen (0.04)
- Europe > Italy > Trentino-Alto Adige/Sรผdtirol > Trentino Province > Trento (0.04)
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- Information Technology > Artificial Intelligence > Machine Learning > Unsupervised or Indirectly Supervised Learning (0.54)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.46)
- Information Technology > Artificial Intelligence > Machine Learning > Inductive Learning (0.43)
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- Asia > Middle East > Jordan (0.04)
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- Information Technology > Artificial Intelligence > Representation & Reasoning > Uncertainty > Bayesian Inference (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models > Directed Networks > Bayesian Learning (0.93)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.69)
Precisecharacterizationofthepriorpredictive distributionofdeepReLUnetworks
Neural Information Processing Systems
Whiletheoretical results havebeen obtained for their heavy-tailedness, the full characterization of the prior predictive distribution (i.e. its density, CDF andmoments), remained unknownpriortothiswork.
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- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
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Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.71)