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The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-540-87479-9_61openalex-snapshot
Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs
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Quad trees a data structure for retrieval on composite keys
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Human-level control through deep reinforcement learning
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Markov Decision Processes: Discrete Stochastic Dynamic Programming
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An implementation and performance analysis of spatial data access methods
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STR: a simple and efficient algorithm for R-tree packing
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Reinforcement Learning with Tree-LSTM for Join Order Selection
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Online Index Selection Using Deep Reinforcement Learning for a Cluster Database
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Indexing non-uniform spatial data
inferredcites →https://doi.org/10.1109/ssdm.2001.938552openalex-snapshot
Cost-based unbalanced R-trees
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A revised r*-tree in comparison with related index structures
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Multiattribute hashing using Gray codes
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Spatial query processing in an object-oriented database system
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Multiattribute hashing using Gray codes
inferredcites →https://doi.org/10.1145/16894.16886openalex-snapshot
Spatial query processing in an object-oriented database system
inferredcites →https://doi.org/10.1145/288692openalex-snapshot
Proceedings of the 6th ACM international symposium on Advances in geographic information systems
inferredcites →https://doi.org/10.1145/288692.288723openalex-snapshot
A greedy algorithm for bulk loading R-trees
inferredcites →https://doi.org/10.1145/3183713.3196909openalex-snapshot
The Case for Learned Index Structures
inferredcites →https://doi.org/10.1145/3187009.3177738openalex-snapshot
Theoretically optimal and empirically efficient r-trees with strong parallelizability
inferredcites →https://doi.org/10.1145/318898.318900openalex-snapshot
Direct spatial search on pictorial databases using packed R-trees
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Distance browsing in spatial databases
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An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning
inferredcites →https://doi.org/10.1145/3318464.3380579openalex-snapshot
Learning Multi-Dimensional Indexes
inferredcites →https://doi.org/10.1145/3318464.3389703openalex-snapshot
LISA: A Learned Index Structure for Spatial Data
inferredcites →https://doi.org/10.1145/3318464.3389711openalex-snapshot
ALEX: An Updatable Adaptive Learned Index
inferredcites →https://doi.org/10.1145/3318464.3389770openalex-snapshot
Qd-tree: Learning Data Layouts for Big Data Analytics
inferredcites →https://doi.org/10.1145/361002.361007openalex-snapshot
Multidimensional binary search trees used for associative searching
inferredcites →https://doi.org/10.1145/73721.73746openalex-snapshot
Fractals for secondary key retrieval
inferredcites →https://doi.org/10.1145/93597.98741openalex-snapshot
The R*-tree: an efficient and robust access method for points and rectangles
inferredcites →https://doi.org/10.1184/r1/6610748openalex-snapshot
The R+-Tree: A Dynamic Index for Multi-Dimensional Objects
inferredcites →https://doi.org/10.14778/3407790.3407827openalex-snapshot
Efficient and effective similar subtrajectory search with deep reinforcement learning
inferredcites →https://doi.org/10.14778/3407790.3407829openalex-snapshot
Effectively learning spatial indices
inferredcites →https://doi.org/10.1609/aaai.v34i05.6190openalex-snapshot
Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning
inferredcites →https://doi.org/10.2307/2291177openalex-snapshot
Markov Decision Processes: Discrete Stochastic Dynamic Programming.
inferredcites →https://doi.org/10.48550/arxiv.2004.14541openalex-snapshot
RadixSpline: A Single-Pass Learned Index
inferredcites →https://doi.org/10.5441/002/edbt.2018.29openalex-snapshot
QUASII: QUery-Aware Spatial Incremental Index
inferredcites →https://doi.org/10.5441/002/edbt.2020.44openalex-snapshot
The ML-Index: A Multidimensional, Learned Index for Point, Range, and Nearest-Neighbor Queries
inferredcites →https://doi.org/10.65109/jsrc7365openalex-snapshot
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Random Sampling Over Spatial Range Joins
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A Survey on Deep Reinforcement Learning for Data Processing and Analytics
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Machine Learning for Databases: Foundations, Paradigms, and Open problems
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