research
∙
08/27/2023
Distributional Off-Policy Evaluation for Slate Recommendations
Recommendation strategies are typically evaluated by using previously lo...
share
research
∙
05/16/2023
Coagent Networks: Generalized and Scaled
Coagent networks for reinforcement learning (RL) [Thomas and Barto, 2011...
research
∙
05/06/2023
Explaining RL Decisions with Trajectories
Explanation is a key component for the adoption of reinforcement learnin...
research
∙
06/30/2022
Personalized Detection of Cognitive Biases in Actions of Users from Their Logs: Anchoring and Recency Biases
Cognitive biases are mental shortcuts humans use in dealing with informa...
research
∙
04/23/2022
Smoothed Online Combinatorial Optimization Using Imperfect Predictions
Smoothed online combinatorial optimization considers a learner who repea...
research
∙
03/05/2022
Off-Policy Evaluation in Embedded Spaces
Off-policy evaluation methods are important in recommendation systems an...
research
∙
12/30/2021
Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning
Online reinforcement learning (RL) algorithms are often difficult to dep...
research
∙
12/10/2021
Edge-Compatible Reinforcement Learning for Recommendations
Most reinforcement learning (RL) recommendation systems designed for edg...
research
∙
09/19/2021
Multiscale Manifold Warping
Many real-world applications require aligning two temporal sequences, in...
research
∙
10/23/2020
Towards Safe Policy Improvement for Non-Stationary MDPs
Many real-world sequential decision-making problems involve critical sys...
research
∙
09/15/2020
Reinforcement Learning for Strategic Recommendations
Strategic recommendations (SR) refer to the problem where an intelligent...
research
∙
05/17/2020
Optimizing for the Future in Non-Stationary MDPs
Most reinforcement learning methods are based upon the key assumption th...
research
∙
06/05/2019
Reinforcement Learning When All Actions are Not Always Available
The Markov decision process (MDP) formulation used to model many real-wo...
research
∙
06/05/2019
Lifelong Learning with a Changing Action Set
In many real-world sequential decision making problems, the number of av...
research
∙
02/01/2019
Learning Action Representations for Reinforcement Learning
Most model-free reinforcement learning methods leverage state representa...
research
∙
11/21/2017
Posterior Sampling for Large Scale Reinforcement Learning
Posterior sampling for reinforcement learning (PSRL) is a popular algori...
research
∙
02/09/2016
