Results 221 to 230 of about 128,390 (257)

G-Learned Index: Enabling Efficient Learned Index on GPU

IEEE Transactions on Parallel and Distributed Systems
Guoliang Li, Dong Deng, Yuxing Chen
exaly   +2 more sources

Learned Index for Spatial Queries

2019 20th IEEE International Conference on Mobile Data Management (MDM), 2019
With the pervasiveness of location-based services (LBS), spatial data processing has received considerable attention in the research of database system management. Among various spatial query techniques, index structures play a key role in data access and query processing.
Haixin Wang 0001, Xiaoyi Fu, Jianliang Xu, Hua Lu 0001   +3 more
openaire   +2 more sources

Micro-architectural analysis of a learned index

Proceedings of the Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2022
Since the publication of The Case for Learned Index Structures in 2018 [26], there has been a rise in research that focuses on learned indexes for different domains and with different functionalities. While the effectiveness of learned indexes as an alternative to traditional index structures such as B+Trees have already been demonstrated by several ...
Mikkel Møller Andersen, Pinar Tözün
openaire   +4 more sources

Learning an Index Advisor with Deep Reinforcement Learning

2021
Indexes are crucial for the efficient processing of database workloads and an appropriately selected set of indexes can drastically improve query processing performance. However, the selection of beneficial indexes is a non-trivial problem and still challenging.
Sichao Lai, Xiaoying Wu, Senyang Wang, Yuwei Peng, Zhiyong Peng 0001   +4 more
openaire   +1 more source

Learning Neighbourhoods for Fingerprint Indexing

2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2018
Fingerprint Indexing allows filtering databases for samples most similar to a query fingerprint. Fixed-length feature vectors invariant to the count of minutiae allow fast comparison. This is the first approach, which uses Deep Convolutional Neural Networks to generate fixed-length index vectors from minutia neighbourhoods.
Patrick Schuch, Jan Marek May, Christoph Busch 0001   +2 more
openaire   +1 more source

Preferred Learning Style Index

Medical Teacher, 1979
In this occasional series, we will be printing evaluation instruments, questionnaires, rating scales and similar resource materials useful to teachers, evaluators and planners.
openaire   +2 more sources

PROBABILISTIC AUTOMATIC INDEXING BY LEARNING FROM HUMAN INDEXERS

Journal of Documentation, 1984
A probabilistic model previously used in relevance feedback is adapted for use in automatic indexing of documents (in the sense of imitating human indexers). The model fits with previous work in this area (the ‘adhesion coefficient’ method), in effect merely suggesting a different way of arriving at the adhesion coefficients.
Stephen E. Robertson, P. Harding
openaire   +1 more source

A Study of Learned KD Tree Based on Learned Index

2020 International Conference on Networking and Network Applications (NaNA), 2020
The dimensions of data in the real world are often relatively high. Traditional indexing methods are difficult to deal with complex situations. How to efficiently and effectively retrieve data has become a hot topic. In recent years, with the development of artificial intelligence, machine learning has played a huge role in many fields.
Yongxin Peng, Wei Zhou 0011, Lin Zhang 0038, Hongle Du   +3 more
openaire   +1 more source

Learned Index on GPU

2022 IEEE 38th International Conference on Data Engineering Workshops (ICDEW), 2022
Xun Zhong, Yong Zhang 0002, Yu Chen 0052, Chao Li 0012, Chunxiao Xing   +4 more
openaire   +1 more source

Research on a learning rate with energy index in deep learning

Neural Networks, 2019
The stochastic gradient descent algorithm (SGD) is the main optimization solution in deep learning. The performance of SGD depends critically on how learning rates are tuned over time. In this paper, we propose a novel energy index based optimization method (EIOM) to automatically adjust the learning rate in the backpropagation.
Huizhen Zhao, Fuxian Liu, Han Zhang, Zhibing Liang   +3 more
openaire   +2 more sources