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11/18/2022
Building a Subspace of Policies for Scalable Continual Learning
The ability to continuously acquire new knowledge and skills is crucial ...
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02/20/2022
Efficient Continual Learning Ensembles in Neural Network Subspaces
A growing body of research in continual learning focuses on the catastro...
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02/14/2021
Domain Adversarial Reinforcement Learning
We consider the problem of generalization in reinforcement learning wher...
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10/07/2020
Regularized Inverse Reinforcement Learning
Inverse Reinforcement Learning (IRL) aims to facilitate a learner's abil...
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10/07/2020
A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix
Continual learning (CL) is a setting in which an agent has to learn from...
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06/12/2020
Deep Reinforcement and InfoMax Learning
Our work is based on the hypothesis that a model-free agent whose repres...
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02/07/2020
Provably efficient reconstruction of policy networks
Recent research has shown that learning poli-cies parametrized by large ...
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09/17/2019
Attraction-Repulsion Actor-Critic for Continuous Control Reinforcement Learning
Continuous control tasks in reinforcement learning are important because...
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07/05/2019
Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning
Goal-conditioned policies are used in order to break down complex reinfo...
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05/16/2019
Leveraging exploration in off-policy algorithms via normalizing flows
Exploration is a crucial component for discovering approximately optimal...
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01/24/2019
Multi-objective training of Generative Adversarial Networks with multiple discriminators
Recent literature has demonstrated promising results for training Genera...
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01/17/2019
Generating Realistic Sequences of Customer-level Transactions for Retail Datasets
In order to better engage with customers, retailers rely on extensive cu...
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07/31/2018
Online Adaptative Curriculum Learning for GANs
Generative Adversarial Networks (GANs) can successfully learn a probabil...
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05/13/2018