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08/15/2023
Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic Segmentation
Medical image segmentation modeling is a high-stakes task where understa...
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06/28/2023
Structure in Reinforcement Learning: A Survey and Open Problems
Reinforcement Learning (RL), bolstered by the expressive capabilities of...
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06/07/2023
Generalization Across Observation Shifts in Reinforcement Learning
Learning policies which are robust to changes in the environment are cri...
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05/26/2023
A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem
Training multiple agents to coordinate is an important problem with appl...
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05/23/2023
Sequence Modeling is a Robust Contender for Offline Reinforcement Learning
Offline reinforcement learning (RL) allows agents to learn effective, re...
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05/17/2023
Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor
Social media platforms moderate content for each user by incorporating t...
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04/03/2023
Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning
In goal-reaching reinforcement learning (RL), the optimal value function...
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04/02/2023
GitHub OSS Governance File Dataset
Open-source Software (OSS) has become a valuable resource in both indust...
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03/28/2023
BC-IRL: Learning Generalizable Reward Functions from Demonstrations
How well do reward functions learned with inverse reinforcement learning...
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03/20/2023
Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement
Object rearrangement is a challenge for embodied agents because solving ...
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03/17/2023
Confidence-aware 3D Gaze Estimation and Evaluation Metric
Deep learning appearance-based 3D gaze estimation is gaining popularity ...
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02/16/2023
Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods
It is well known that Reinforcement Learning (RL) can be formulated as a...
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02/07/2023
Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability
Goal-conditioned reinforcement learning (GCRL) refers to learning genera...
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01/05/2023
Do Users Want Platform Moderation or Individual Control? Examining the Role of Third-Person Effects and Free Speech Support in Shaping Moderation Preferences
This study examines social media users' preferences for the use of platf...
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12/21/2022
Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning
Traditional approaches to RL have focused on learning decision policies ...
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10/27/2022
LAD: Language Augmented Diffusion for Reinforcement Learning
Learning skills from language provides a powerful avenue for generalizat...
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10/03/2022
Latent State Marginalization as a Low-cost Approach for Improving Exploration
While the maximum entropy (MaxEnt) reinforcement learning (RL) framework...
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07/20/2022
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis
Recommender systems are the algorithms which select, filter, and persona...
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06/30/2022
Denoised MDPs: Learning World Models Better Than the World Itself
The ability to separate signal from noise, and reason with clean abstrac...
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04/27/2022
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning
Building generalizable goal-conditioned agents from rich observations is...
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02/17/2022
Designing Word Filter Tools for Creator-led Comment Moderation
Online social platforms centered around content creators often allow com...
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02/14/2022
Robust Policy Learning over Multiple Uncertainty Sets
Reinforcement learning (RL) agents need to be robust to variations in sa...
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02/11/2022
Online Decision Transformer
Recent work has shown that offline reinforcement learning (RL) can be fo...
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01/09/2022
Information Borrowing in Regression Models
Model development often takes data structure, subject matter considerati...
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11/18/2021
A Survey of Generalisation in Deep Reinforcement Learning
The study of generalisation in deep Reinforcement Learning (RL) aims to ...
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11/15/2021
Learning Representations for Pixel-based Control: What Matters and Why?
Learning representations for pixel-based control has garnered significan...
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10/13/2021
Block Contextual MDPs for Continual Learning
In reinforcement learning (RL), when defining a Markov Decision Process ...
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08/27/2021
Designing for Multiple Centers of Power: A Taxonomy of Multi-level Governance in Online Social Platforms
Many have criticized the centralized and unaccountable governance of pro...
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07/13/2021
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
Generalization is a central challenge for the deployment of reinforcemen...
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06/22/2021
Provably Efficient Representation Learning in Low-rank Markov Decision Processes
The success of deep reinforcement learning (DRL) is due to the power of ...
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04/20/2021
MBRL-Lib: A Modular Library for Model-based Reinforcement Learning
Model-based reinforcement learning is a compelling framework for data-ef...
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02/19/2021
Model-Invariant State Abstractions for Model-Based Reinforcement Learning
Accuracy and generalization of dynamics models is key to the success of ...
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02/11/2021
Multi-Task Reinforcement Learning with Context-based Representations
The benefit of multi-task learning over single-task learning relies on t...
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01/27/2021
Pano: Engaging with News using Moral Framing towards Bridging Ideological Divides
Society is showing signs of strong ideological polarization. When pushed...
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12/09/2020
Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews
Objective: Systematic reviews of scholarly documents often provide compl...
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12/03/2020
Intervention Design for Effective Sim2Real Transfer
The goal of this work is to address the recent success of domain randomi...
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07/14/2020
Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP
Multi-task reinforcement learning is a rich paradigm where information f...
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06/18/2020
Learning Invariant Representations for Reinforcement Learning without Reconstruction
We study how representation learning can accelerate reinforcement learni...
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05/07/2020
Plan2Vec: Unsupervised Representation Learning by Latent Plans
In this paper we introduce plan2vec, an unsupervised representation lear...
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03/12/2020
Invariant Causal Prediction for Block MDPs
Generalization across environments is critical to the successful applica...
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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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03/02/2020
Out-of-Distribution Generalization via Risk Extrapolation (REx)
Generalizing outside of the training distribution is an open challenge f...
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10/02/2019
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
Training an agent to solve control tasks directly from high-dimensional ...
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06/25/2019
Learning Causal State Representations of Partially Observable Environments
Intelligent agents can cope with sensory-rich environments by learning t...
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11/14/2018
Natural Environment Benchmarks for Reinforcement Learning
While current benchmark reinforcement learning (RL) tasks have been usef...
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06/20/2018
A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning
The risks and perils of overfitting in machine learning are well known. ...
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04/27/2018
Decoupling Dynamics and Reward for Transfer Learning
Current reinforcement learning (RL) methods can successfully learn singl...
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03/01/2018
Composable Planning with Attributes
The tasks that an agent will need to solve often are not known during tr...
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12/15/2017
Mapping the world population one building at a time
High resolution datasets of population density which accurately map spar...
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07/27/2017
