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Advancing Forest Fire Prevention: Deep Reinforcement Learning for Effective Firebreak Placement
To the best of our knowledge, this study represents a pioneering effort in using Reinforcement Learning to address the aforementioned problem, offering promising perspectives in fire prevention and landscape management
Unconventional application of k-means for distributed approximate similarity search
In this paper, we introduce MASK (Multilevel Approximate Similarity search with $k$-means), an unconventional application of the $k$-means algorithm as the foundation of a multilevel index structure for approximate similarity search, suitable for metric spaces.
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