Approximate query processing: What is new and where to go? a survey on approximate query processing
Online analytical processing (OLAP) is a core functionality in database systems. The
performance of OLAP is crucial to make online decisions in many applications. However, it is …
performance of OLAP is crucial to make online decisions in many applications. However, it is …
Conformal frequency estimation using discrete sketched data with coverage for distinct queries
This paper develops conformal inference methods to construct a confidence interval for the
frequency of a queried object in a very large discrete data set, based on a sketch with a …
frequency of a queried object in a very large discrete data set, based on a sketch with a …
Count-min: Optimal estimation and tight error bounds using empirical error distributions
D Ting - Proceedings of the 24th ACM SIGKDD International …, 2018 - dl.acm.org
The Count-Min sketch is an important and well-studied data summarization method. It can
estimate the count of any item in a stream using a small, fixed size data sketch. However, the …
estimate the count of any item in a stream using a small, fixed size data sketch. However, the …
Approximate Computing: Concepts, Architectures, Challenges, Applications, and Future Directions
AM Dalloo, AJ Humaidi, AK Al Mhdawi… - IEEE …, 2024 - ieeexplore.ieee.org
The unprecedented progress in computational technologies led to a substantial proliferation
of artificial intelligence applications, notably in the era of big data and IoT devices. In the …
of artificial intelligence applications, notably in the era of big data and IoT devices. In the …
A survey of sketches in traffic measurement: Design, optimization, application and implementation
S Li, L Luo, D Guo, Q Zhang, P Fu - arXiv preprint arXiv:2012.07214, 2020 - arxiv.org
Network measurement probes the underlying network to support upper-level decisions such
as network management, network update, network maintenance, network defense and …
as network management, network update, network maintenance, network defense and …
CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models
Recently, the growing memory demands of embedding tables in Deep Learning
Recommendation Models (DLRMs) pose great challenges for model training and …
Recommendation Models (DLRMs) pose great challenges for model training and …
Sf-sketch: A fast, accurate, and memory efficient data structure to store frequencies of data items
A sketch is a probabilistic data structure that is used to record frequencies of items in a multi-
set. Sketches have been applied in a variety of fields, such as data stream processing …
set. Sketches have been applied in a variety of fields, such as data stream processing …
Smash++: an alignment-free and memory-efficient tool to find genomic rearrangements
Background The development of high-throughput sequencing technologies and, as its
result, the production of huge volumes of genomic data, has accelerated biological and …
result, the production of huge volumes of genomic data, has accelerated biological and …
Learning-augmented count-min sketches via Bayesian nonparametrics
The count-min sketch (CMS) is a time and memory efficient randomized data structure that
provides estimates of tokens' frequencies in a data stream of tokens, ie point queries, based …
provides estimates of tokens' frequencies in a data stream of tokens, ie point queries, based …
TreeSensing: Linearly Compressing Sketches with Flexibility
A Sketch is an excellent probabilistic data structure, which records the approximate statistics
of data streams. Linear additivity is an important property of sketches. This paper studies …
of data streams. Linear additivity is an important property of sketches. This paper studies …