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09/07/2023
A State Representation for Diminishing Rewards
A common setting in multitask reinforcement learning (RL) demands that a...
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10/24/2022
Scalable Representation Learning in Linear Contextual Bandits with Constant Regret Guarantees
We study the problem of representation learning in stochastic contextual...
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09/29/2022
Does Zero-Shot Reinforcement Learning Exist?
A zero-shot RL agent is an agent that can solve any RL task in a given e...
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03/14/2021
Learning One Representation to Optimize All Rewards
We introduce the forward-backward (FB) representation of the dynamics of...
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10/24/2020
Efficient Learning in Non-Stationary Linear Markov Decision Processes
We study episodic reinforcement learning in non-stationary linear (a.k.a...
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10/08/2020
Maximum Reward Formulation In Reinforcement Learning
Reinforcement learning (RL) algorithms typically deal with maximizing th...
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07/07/2020
Sharp Analysis of Smoothed Bellman Error Embedding
The Smoothed Bellman Error Embedding algorithm <cit.>, known as SBEED, w...
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07/06/2020
TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?
We investigate whether Jacobi preconditioning, accounting for the bootst...
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03/09/2020
Stable Policy Optimization via Off-Policy Divergence Regularization
Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization...
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03/09/2020
Zooming for Efficient Model-Free Reinforcement Learning in Metric Spaces
Despite the wealth of research into provably efficient reinforcement lea...
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06/10/2019
Stochastic Neural Network with Kronecker Flow
Recent advances in variational inference enable the modelling of highly ...
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06/09/2019
SVRG for Policy Evaluation with Fewer Gradient Evaluations
Stochastic variance-reduced gradient (SVRG) is an optimization method or...
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03/05/2019
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
In model-based reinforcement learning, the agent interleaves between mod...
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02/05/2019
Separating value functions across time-scales
In many finite horizon episodic reinforcement learning (RL) settings, it...
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06/06/2018
Randomized Value Functions via Multiplicative Normalizing Flows
Randomized value functions offer a promising approach towards the challe...
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12/22/2017
Adaptive Stochastic Dual Coordinate Ascent for Conditional Random Fields
This work investigates training Conditional Random Fields (CRF) by Stoch...
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10/06/2017
Learnable Explicit Density for Continuous Latent Space and Variational Inference
In this paper, we study two aspects of the variational autoencoder (VAE)...
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08/08/2017
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling
Generative modeling of high dimensional data like images is a notoriousl...
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05/25/2017