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Found 9 papers, 6 papers with code
From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practice
We propose a novel paradigm that, complementing known specialized ones, can produce Learned versions of any Sorted Set Dictionary, for instance, Balanced Binary Search Trees or Binary Search on layouts other that sorted, i. e., Eytzinger.
A Critical Analysis of Classifier Selection in Learned Bloom Filters
Learned Bloom Filters, i. e., models induced from data via machine learning techniques and solving the approximate set membership problem, have recently been introduced with the aim of enhancing the performance of standard Bloom Filters, with special focus on space occupancy.
On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexes
In turn, that would favour the use of Neural Networks as building blocks of Classic Data Structures.
Standard Vs Uniform Binary Search and Their Variants in Learned Static Indexing: The Case of the Searching on Sorted Data Benchmarking Software Platform
With the use of the Searching on Sorted Sets SOSD Learned Indexing benchmarking software, we investigate how to choose a Search routine for the final stage of searching in a Learned Index.
On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters
Bloom Filters are a fundamental and pervasive data structure.
Learned Sorted Table Search and Static Indexes in Small Model Space
In modern applications, model space is a key factor and, in fact, a major open question concerning this area is to assess to what extent one can enjoy the speed-up of Binary Search achieved by Learned Indexes while using constant or nearly constant space models.
The Power of Word-Frequency Based Alignment-Free Functions: a Comprehensive Large-scale Experimental Analysis -- Version 3
Experimental studies on real datasets abound and, to some extent, there are also studies regarding their control of false positive rate (Type I error).
Learning from Data to Speed-up Sorted Table Search Procedures: Methodology and Practical Guidelines
Here we study to what extend Machine Learning Techniques can contribute to obtain such a speed-up via a systematic experimental comparison of known efficient implementations of Sorted Table Search procedures, with different Data Layouts, and their Learned counterparts developed here.
FASTdoop: a versatile and efficient library for the input of FASTA and FASTQ files for MapReduce Hadoop bioinformatics applications
We present FASTdoop, a generic Hadoop library for the management of FASTA and FASTQ files.
