Brendan O'Donoghue

According to our database1, Brendan O'Donoghue authored at least 39 papers between 2011 and 2023.

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Bibliography

2023
Optimistic Meta-Gradients.
CoRR, 2023

Probabilistic Inference in Reinforcement Learning Done Right.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Optimistic Meta-Gradients.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization.
Proceedings of the International Conference on Machine Learning, 2023

ReLOAD: Reinforcement Learning with Optimistic Ascent-Descent for Last-Iterate Convergence in Constrained MDPs.
Proceedings of the International Conference on Machine Learning, 2023

2022
POMRL: No-Regret Learning-to-Plan with Increasing Horizons.
CoRR, 2022

On the connection between Bregman divergence and value in regularized Markov decision processes.
CoRR, 2022

The Neural Testbed: Evaluating Joint Predictions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Operator Splitting for a Homogeneous Embedding of the Linear Complementarity Problem.
SIAM J. Optim., 2021

Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
CoRR, 2021

Discovering Diverse Nearly Optimal Policies withSuccessor Features.
CoRR, 2021

Matrix games with bandit feedback.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Reward is enough for convex MDPs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variational Bayesian Optimistic Sampling.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Variational Bayesian Reinforcement Learning with Regret Bounds.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Discovering a set of policies for the worst case reward.
Proceedings of the 9th International Conference on Learning Representations, 2021

Sample Efficient Reinforcement Learning with REINFORCE.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Globally Convergent Type-I Anderson Acceleration for Nonsmooth Fixed-Point Iterations.
SIAM J. Optim., 2020

Solving Mixed Integer Programs Using Neural Networks.
CoRR, 2020

Stochastic matrix games with bandit feedback.
CoRR, 2020

Making Sense of Reinforcement Learning and Probabilistic Inference.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Hamiltonian descent for composite objectives.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Verification of Non-Linear Specifications for Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles.
CoRR, 2018

Hamiltonian Descent Methods.
CoRR, 2018

Training verified learners with learned verifiers.
CoRR, 2018

Adversarial Risk and the Dangers of Evaluating Against Weak Attacks.
Proceedings of the 35th International Conference on Machine Learning, 2018

The Uncertainty Bellman Equation and Exploration.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Combining policy gradient and Q-learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding.
J. Optim. Theory Appl., 2016

PGQ: Combining policy gradient and Q-learning.
CoRR, 2016

2015
Large-Scale Convex Optimization for Dense Wireless Cooperative Networks.
IEEE Trans. Signal Process., 2015

Adaptive Restart for Accelerated Gradient Schemes.
Found. Comput. Math., 2015

2014
Fast Alternating Direction Optimization Methods.
SIAM J. Imaging Sci., 2014

Performance Bounds and Suboptimal Policies for Multi-Period Investment.
Found. Trends Optim., 2014

2013
A Splitting Method for Optimal Control.
IEEE Trans. Control. Syst. Technol., 2013

Iterated approximate value functions.
Proceedings of the 12th European Control Conference, 2013

2011
Min-max approximate dynamic programming.
Proceedings of the 2011 IEEE International Symposium on Computer-Aided Control System Design, 2011


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