research
∙
08/13/2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods
Stochastic gradient descent (SGD) and adaptive gradient methods, such as...
share
research
∙
07/17/2023
Efficient and Accurate Optimal Transport with Mirror Descent and Conjugate Gradients
We design a novel algorithm for optimal transport by drawing from the en...
research
∙
07/04/2023
Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
We consider the problem of learning models for risk-sensitive reinforcem...
research
∙
06/30/2023
λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces
The idea of decision-aware model learning, that models should be accurat...
research
∙
11/25/2022
Operator Splitting Value Iteration
We introduce new planning and reinforcement learning algorithms for disc...
research
∙
04/04/2022
Value Gradient weighted Model-Based Reinforcement Learning
Model-based reinforcement learning (MBRL) is a sample efficient techniqu...
research
∙
10/21/2021
Deep Reinforcement Learning for Online Control of Stochastic Partial Differential Equations
In many areas, such as the physical sciences, life sciences, and finance...
research
∙
10/05/2020
The act of remembering: a study in partially observable reinforcement learning
Reinforcement Learning (RL) agents typically learn memoryless policies—p...
research
∙
07/19/2020
Beyond Prioritized Replay: Sampling States in Model-Based RL via Simulated Priorities
Model-based reinforcement learning (MBRL) can significantly improve samp...
research
∙
04/04/2020
Adversarial Robustness through Regularization: A Second-Order Approach
Adversarial training is a common approach to improving the robustness of...
research
∙
02/28/2020
Policy-Aware Model Learning for Policy Gradient Methods
This paper considers the problem of learning a model in model-based rein...
research
∙
02/14/2020
An implicit function learning approach for parametric modal regression
For multi-valued functions—such as when the conditional distribution on ...
research
∙
02/14/2020
Frequency-based Search-control in Dyna
Model-based reinforcement learning has been empirically demonstrated as ...
research
∙
06/18/2019
Hill Climbing on Value Estimates for Search-control in Dyna
Dyna is an architecture for model-based reinforcement learning (RL), whe...
research
∙
03/08/2019
Improving Skin Condition Classification with a Visual Symptom Checker trained using Reinforcement Learning
We present a visual symptom checker that combines a pre-trained Convolut...
research
∙
11/15/2018
Improving Skin Condition Classification with a Question Answering Model
We present a skin condition classification methodology based on a sequen...
research
∙
06/13/2018
Reinforcement Learning with Function-Valued Action Spaces for Partial Differential Equation Control
Recent work has shown that reinforcement learning (RL) is a promising ap...
research
∙
02/06/2017
Attentional Network for Visual Object Detection
We propose augmenting deep neural networks with an attention mechanism f...
research
∙
07/02/2014
Classification-based Approximate Policy Iteration: Experiments and Extended Discussions
Tackling large approximate dynamic programming or reinforcement learning...
research
∙
07/23/2012