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41 papers · 1 filter
Fairness in Machine Learning
Luca Oneto, Silvia Chiappa
Machine learning based systems are reaching society at large and in many aspects of everyday life. This phenomenon has been accompanied by concerns about the ethical issues that ma…
Improved Sample Complexity for Incremental Autonomous Exploration in MDPs
Jean Tarbouriech, Matteo Pirotta, Michal Valko +1
We investigate the exploration of an unknown environment when no reward function is provided. Building on the incremental exploration setting introduced by Lim and Auer [1], we def…
Exact Reduction of Huge Action Spaces in General Reinforcement Learning
Sultan Javed Majeed, Marcus Hutter
The reinforcement learning (RL) framework formalizes the notion of learning with interactions. Many real-world problems have large state-spaces and/or action-spaces such as in Go,…
Relative Variational Intrinsic Control
Kate Baumli, David Warde-Farley, Steven Hansen +1
In the absence of external rewards, agents can still learn useful behaviors by identifying and mastering a set of diverse skills within their environment. Existing skill learning m…
Concept-based model explanations for Electronic Health Records
Diana Mincu, Eric Loreaux, Shaobo Hou +7
Recurrent Neural Networks (RNNs) are often used for sequential modeling of adverse outcomes in electronic health records (EHRs) due to their ability to encode past clinical states.…
Balancing Constraints and Rewards with Meta-Gradient D4PG
Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy +4
Deploying Reinforcement Learning (RL) agents to solve real-world applications often requires satisfying complex system constraints. Often the constraint thresholds are incorrectly…