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02/18/2023
Efficient exploration via epistemic-risk-seeking policy optimization
Exploration remains a key challenge in deep reinforcement learning (RL)....
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12/30/2022
POMRL: No-Regret Learning-to-Plan with Increasing Horizons
We study the problem of planning under model uncertainty in an online me...
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10/21/2022
On the connection between Bregman divergence and value in regularized Markov decision processes
In this short note we derive a relationship between the Bregman divergen...
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10/29/2021
Variational Bayesian Optimistic Sampling
We consider online sequential decision problems where an agent must bala...
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10/09/2021
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
Posterior predictive distributions quantify uncertainties ignored by poi...
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06/01/2021
Reward is enough for convex MDPs
Maximising a cumulative reward function that is Markov and stationary, i...
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12/23/2020
Solving Mixed Integer Programs Using Neural Networks
Mixed Integer Programming (MIP) solvers rely on an array of sophisticate...
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10/22/2020
Sample Efficient Reinforcement Learning with REINFORCE
Policy gradient methods are among the most effective methods for large-s...
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06/09/2020
Stochastic matrix games with bandit feedback
We study a version of the classical zero-sum matrix game with unknown pa...
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01/03/2020
Making Sense of Reinforcement Learning and Probabilistic Inference
Reinforcement learning (RL) combines a control problem with statistical ...
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02/25/2019
Verification of Non-Linear Specifications for Neural Networks
Prior work on neural network verification has focused on specifications ...
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11/22/2018
Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles
While deep learning has led to remarkable results on a number of challen...
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09/13/2018
Hamiltonian Descent Methods
We propose a family of optimization methods that achieve linear converge...
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07/25/2018
Variational Bayesian Reinforcement Learning with Regret Bounds
We consider the exploration-exploitation trade-off in reinforcement lear...
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05/25/2018
Training verified learners with learned verifiers
This paper proposes a new algorithmic framework,predictor-verifier train...
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02/15/2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
This paper investigates recently proposed approaches for defending again...
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09/15/2017
The Uncertainty Bellman Equation and Exploration
We consider the exploration/exploitation problem in reinforcement learni...
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11/05/2016