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07/12/2023
Budgeting Counterfactual for Offline RL
The main challenge of offline reinforcement learning, where data is limi...
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06/30/2023
Resetting the Optimizer in Deep RL: An Empirical Study
We focus on the task of approximating the optimal value function in deep...
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06/30/2023
TD Convergence: An Optimization Perspective
We study the convergence behavior of the celebrated temporal-difference ...
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10/04/2022
Data drift correction via time-varying importance weight estimator
Real-world deployment of machine learning models is challenging when dat...
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05/28/2022
Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline
We study task-agnostic continual reinforcement learning (TACRL) in which...
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12/10/2021
Deep Q-Network with Proximal Iteration
We employ Proximal Iteration for value-function optimization in reinforc...
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02/26/2021
Deep Quantile Aggregation
Conditional quantile estimation is a key statistical learning challenge ...
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02/18/2021
Continuous Doubly Constrained Batch Reinforcement Learning
Reliant on too many experiments to learn good actions, current Reinforce...
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06/26/2020
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning
This paper prescribes a suite of techniques for off-policy Reinforcement...
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06/25/2020
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
Automated machine learning (AutoML) can produce complex model ensembles ...
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04/06/2020
TraDE: Transformers for Density Estimation
We present TraDE, an attention-based architecture for auto-regressive de...
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09/30/2019
Meta-Q-Learning
This paper introduces Meta-Q-Learning (MQL), a new off-policy algorithm ...
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05/05/2019
P3O: Policy-on Policy-off Policy Optimization
On-policy reinforcement learning (RL) algorithms have high sample comple...
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10/30/2018
Differentiable Greedy Networks
Optimal selection of a subset of items from a given set is a hard proble...
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09/28/2018
Direct optimization of F-measure for retrieval-based personal question answering
Recent advances in spoken language technologies and the introduction of ...
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02/16/2018
Constrained Convolutional-Recurrent Networks to Improve Speech Quality with Low Impact on Recognition Accuracy
For a speech-enhancement algorithm, it is highly desirable to simultaneo...
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11/07/2016
