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Found 7 papers, 4 papers with code
Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification
Land cover classification (LCC), and monitoring how land use changes over time, is an important process in climate change mitigation and adaptation.
Non-Markovian Reward Modelling from Trajectory Labels via Interpretable Multiple Instance Learning
We generalise the problem of reward modelling (RM) for reinforcement learning (RL) to handle non-Markovian rewards.
Resilient robot teams: a review integrating decentralised control, change-detection, and learning
Purpose of review: This paper reviews opportunities and challenges for decentralised control, change-detection, and learning in the context of resilient robot teams.
Learning from the Pros: Extracting Professional Goalkeeper Technique from Broadcast Footage
As an amateur goalkeeper playing grassroots soccer, who better to learn from than top professional goalkeepers?
Model Agnostic Interpretability for Multiple Instance Learning
In Multiple Instance Learning (MIL), models are trained using bags of instances, where only a single label is provided for each bag.
What Happened Next? Using Deep Learning to Value Defensive Actions in Football Event-Data
Objectively quantifying the value of player actions in football (soccer) is a challenging problem.
Mechanism Design for Efficient Online and Offline Allocation of Electric Vehicles to Charging Stations
We formulate the problem of the optimal EV to charging station allocation as a Mixed Integer Programming (MIP) one and we propose two pricing mechanisms: A fixed-price one, and another that is based on the well known Vickrey-Clark-Groves (VCG) mechanism.
Computer Science and Game Theory Systems and Control Systems and Control
