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A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Information fusion, 2021-12, Vol.76, p.243-297

2021

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Approximate modified policy iteration and its application to the game of Tetris

Journal of machine learning research, 2015-08, Vol.16

2015

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Sequential Decision Making With Coherent Risk

IEEE transactions on automatic control, 2017-07, Vol.62 (7), p.3323-3338

2017

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Bayesian Policy Gradient and Actor-Critic Algorithms

Journal of machine learning research, 2016-08, Vol.17 (66), p.1-53

2016

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Natural actor–critic algorithms

Automatica (Oxford), 2009-11, Vol.45 (11), p.2471-2482

2009

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Finite-Sample Analysis of Least-Squares Policy Iteration

Journal of machine learning research, 2012-10, Vol.13, p.3041-3074

2012

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Analysis of Classification-based Policy Iteration Algorithms

Journal of machine learning research, 2016-01, Vol.17, p.1-30

2016

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Variance-constrained actor-critic algorithms for discounted and average reward MDPs

Machine learning, 2016-12, Vol.105 (3), p.367-417

2016

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Active Learning for Classification With Abstention

IEEE journal on selected areas in information theory, 2021-06, Vol.2 (2), p.705-719

2021

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Collaborative Multi-agent Stochastic Linear Bandits

2022 American Control Conference (ACC), 2022, p.2761-2766

2022

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Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity

The Journal of artificial intelligence research, 2018-01, Vol.63, p.461-494

2018

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Hierarchical multi-agent reinforcement learning

Autonomous agents and multi-agent systems, 2006-09, Vol.13 (2), p.197-229

2006

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Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors

ACM transactions on recommender systems, 2024-12, Vol.2 (4), p.1-37, Article 30

2024

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Classification-Based Approximate Policy Iteration

IEEE transactions on automatic control, 2015-11, Vol.60 (11), p.2989-2993

2015

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Conservative and Greedy Approaches to Classification-Based Policy Iteration

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2021-09, Vol.26 (1), p.914-920

2021

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Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display

Machine Learning and Data Mining in Pattern Recognition, 2017, Vol.10358, p.32-46

2017

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High-Confidence Off-Policy Evaluation

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2015, Vol.29 (1)

2015

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Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits

Algorithmic Learning Theory, 2011, p.189-203

2011

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Meta-Learning for Simple Regret Minimization

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2023, Vol.37 (6), p.6709-6717

2023

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Active Learning for Classification with Abstention

2020 IEEE International Symposium on Information Theory (ISIT), 2020, p.2801-2806

2020

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Multi-Environment Meta-Learning in Stochastic Linear Bandits

2022 IEEE International Symposium on Information Theory (ISIT), 2022, p.1659-1664

2022

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Improved Algorithms for Conservative Exploration in Bandits

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2020, Vol.34 (4), p.3962-3969

2020

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Graphical Model Sketch

Machine Learning and Knowledge Discovery in Databases, 2016, Vol.9851, p.81-97

2016

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Deep Bayesian Quadrature Policy Optimization

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2021, Vol.35 (8), p.6600-6608

2021

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Automated Data Cleansing through Meta-Learning

Proceedings of the ... AAAI Conference on Artificial Intelligence, 2017, Vol.31 (2), p.4760-4761

2017

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A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Approximate modified policy iteration and its application to the game of Tetris

Sequential Decision Making With Coherent Risk

Bayesian Policy Gradient and Actor-Critic Algorithms

Natural actor–critic algorithms

Finite-Sample Analysis of Least-Squares Policy Iteration

Analysis of Classification-based Policy Iteration Algorithms

Variance-constrained actor-critic algorithms for discounted and average reward MDPs

Active Learning for Classification With Abstention

Collaborative Multi-agent Stochastic Linear Bandits

Proximal Gradient Temporal Difference Learning: Stable Reinforcement Learning with Polynomial Sample Complexity

Hierarchical multi-agent reinforcement learning

Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors

Classification-Based Approximate Policy Iteration

Conservative and Greedy Approaches to Classification-Based Policy Iteration

Importance of Recommendation Policy Space in Addressing Click Sparsity in Personalized Advertisement Display

High-Confidence Off-Policy Evaluation

Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits

Meta-Learning for Simple Regret Minimization

Active Learning for Classification with Abstention

Multi-Environment Meta-Learning in Stochastic Linear Bandits

Improved Algorithms for Conservative Exploration in Bandits

Graphical Model Sketch

Deep Bayesian Quadrature Policy Optimization

Automated Data Cleansing through Meta-Learning

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