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Occupancy Detection Based on Electricity Consumption
This article presents a new methodology for extracting intervals when a home is vacant from low-frequency electricity consumption data.
Domain Knowledge Aids in Signal Disaggregation; the Example of the Cumulative Water Heater
In this article we present an unsupervised low-frequency method aimed at detecting and disaggregating the power used by Cumulative Water Heaters (CWH) in residential homes.
PBCS : Efficient Exploration and Exploitation Using a Synergy between Reinforcement Learning and Motion Planning
In this paper, we propose a new algorithm called "Plan, Backplay, Chain Skills" (PBCS) that combines motion planning and reinforcement learning to solve hard exploration environments.
The problem with DDPG: understanding failures in deterministic environments with sparse rewards
In environments with continuous state and action spaces, state-of-the-art actor-critic reinforcement learning algorithms can solve very complex problems, yet can also fail in environments that seem trivial, but the reason for such failures is still poorly understood.
