Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier
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Abstract (arXiv)
Recent work suggests improving the performance of Bloom filter by incorporating a machine learning model as a binary classifier. However, such learned Bloom filter does not take full advantage of the predicted probability scores. We proposed new algorithms that generalize the learned Bloom filter by using the complete spectrum of the scores regions. We proved our algorithms have lower False Positive Rate (FPR) and memory usage compared with the existing approaches to learned Bloom filter. We also demonstrated the improved performance of our algorithms on real-world datasets.
Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Oct 2019.
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Citing papers per year: 2021: 3; 2022: 4; 2023: 1; 2024: 1; 2025: 3; 2026: 3.
15 papers.
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- 2021DeepBF: Malicious URL detection using Learned Bloom Filter and Evolutionary Deep Learningcited by 4
- 2021Learned Sorted Table Search and Static Indexes in Small Model Spacecited by 4
- 2021On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filterscited by 4
- 2024A Survey of Learned Indexes for the Multi-dimensional Spacecited by 4
- 2022On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexescited by 3
- 2022Daisy Bloom Filterscited by 3
- 2022Proteus: A Self-Designing Range Filtercited by 2
- 2026Context Compaction Theorycited by 2
- 2026Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functionscited by 1
- 2022A Critical Analysis of Classifier Selection in Learned Bloom Filterscited by 0
- 2023From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practicecited by 0
- 2025Cascaded Learned Bloom Filter for Optimizing Model-Filter Size Balance and Fast Rejectioncited by 0
3 more
- 2025Learned Static Function Data Structurescited by 0
- 2025Optimized Learned Count-Min Sketchcited by 0
- 2026Learning Filters with Certaintycited by 0
- 2026Context Compaction Theory2 Aug 2026
- 2026Learning Filters with Certainty22 Jun 2026
- 2026Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functions28 Feb 2026
- 2025Optimized Learned Count-Min Sketch13 Dec 2025
- 2025Learned Static Function Data Structures31 Oct 2025
- 2025Cascaded Learned Bloom Filter for Optimizing Model-Filter Size Balance and Fast Rejection6 Feb 2025
- 2024A Survey of Learned Indexes for the Multi-dimensional Space11 Mar 2024
- 2023From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practice2 Sep 2023
- 2022A Critical Analysis of Classifier Selection in Learned Bloom Filters28 Nov 2022
- 2022Proteus: A Self-Designing Range Filter30 Jun 2022
- 2022Daisy Bloom Filters30 May 2022
- 2022On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexes21 Feb 2022
3 more
- 2021On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters13 Dec 2021
- 2021Learned Sorted Table Search and Static Indexes in Small Model Space19 Jul 2021
- 2021DeepBF: Malicious URL detection using Learned Bloom Filter and Evolutionary Deep Learning18 Mar 2021
- 2021DeepBF: Malicious URL detection using Learned Bloom Filter and Evolutionary Deep Learningcited by 4
- 2021Learned Sorted Table Search and Static Indexes in Small Model Spacecited by 4
- 2021On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filterscited by 4
- 2024A Survey of Learned Indexes for the Multi-dimensional Spacecited by 4
- 2022On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexescited by 3
- 2022Daisy Bloom Filterscited by 3
- 2022Proteus: A Self-Designing Range Filtercited by 2
- 2026Context Compaction Theorycited by 2
- 2026Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functionscited by 1
- 2022A Critical Analysis of Classifier Selection in Learned Bloom Filterscited by 0
- 2023From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practicecited by 0
- 2025Cascaded Learned Bloom Filter for Optimizing Model-Filter Size Balance and Fast Rejectioncited by 0
12 most cited of 15 All 15 (JSON)
- 2026Context Compaction Theory2 Aug 2026
- 2026Learning Filters with Certainty22 Jun 2026
- 2026Mathematical Foundations of Poisoning Attacks on Linear Regression over Cumulative Distribution Functions28 Feb 2026
- 2025Optimized Learned Count-Min Sketch13 Dec 2025
- 2025Learned Static Function Data Structures31 Oct 2025
- 2025Cascaded Learned Bloom Filter for Optimizing Model-Filter Size Balance and Fast Rejection6 Feb 2025
- 2024A Survey of Learned Indexes for the Multi-dimensional Space11 Mar 2024
- 2023From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practice2 Sep 2023
- 2022A Critical Analysis of Classifier Selection in Learned Bloom Filters28 Nov 2022
- 2022Proteus: A Self-Designing Range Filter30 Jun 2022
- 2022Daisy Bloom Filters30 May 2022
- 2022On the Suitability of Neural Networks as Building Blocks for The Design of Efficient Learned Indexes21 Feb 2022
12 newest of 15 All 15 (JSON)