Related papers: Simple implementation of deletion from open-addres…
In this article we discuss a data structure, which combines advantages of two different ways for representing graphs: adjacency matrix and collection of adjacency lists. This data structure can fast add and search edges (advantages of…
In this paper a novel approach for matrix manipulation and indexing is proposed .Here the elements in a row of matrix are designated by numeric value called permutation index followed by the elements of the row being randomised. This is…
A tabulation-based hash function maps a key into d derived characters indexing random values in tables that are then combined with bitwise xor operations to give the hash. Thorup and Zhang (2004) presented d-wise independent…
We firstly suggest new cache policy applying the duty to delete invalid cache data on Non-volatile Memory (NVM). This cache policy includes generating random data and overwriting the random data into invalid cache data. Proposed cache…
For nearly six decades, the central open question in the study of hash tables has been to determine the optimal achievable tradeoff curve between time and space. State-of-the-art hash tables offer the following guarantee: If keys/values are…
Garbage Collection in concurrent data structures, especially lock-free ones, pose multiple design and consistency challenges. In this instance, we consider the case of concurrent sets. A set is a collection of elements, where the elements…
This report describes an implementation of a non-blocking concurrent shared-memory hash trie based on single-word compare-and-swap instructions. Insert, lookup and remove operations modifying different parts of the hash trie can be run…
The analysis of several algorithms and data structures can be framed as a peeling process on a random hypergraph: vertices with degree less than k and their adjacent edges are removed until no vertices of degree less than k are left. Often…
Index structures often materialize one or multiple levels of explicit indirections (aka pointers) to allow for a quick traversal to the data of interest. Unfortunately, dereferencing a pointer to go from one level to the other is costly…
The open-domain text-to-SQL task aims to retrieve question-relevant tables from massive databases and generate SQL. However, the performance of current methods is constrained by single-hop retrieval, and existing multi-hop retrieval of…
A hidden database refers to a dataset that an organization makes accessible on the web by allowing users to issue queries through a search interface. In other words, data acquisition from such a source is not by following static…
We present {\bf Sli}ding Blo{\bf ck} Hashing (Slick), a simple hash table data structure that combines high performance with very good space efficiency. This preliminary report outlines avenues for analysis and implementation that we intend…
The retrieval of data from computer hard drives that have been seized from police busts against suspected criminals are sometimes not straight forward. Typically the incriminating data, which may be important evidence in subsequent trials,…
One of the most popular setups for a back-end of a high performance website consists of a relational database and a cache which stores results of performed queries. Several application frameworks support caching of queries made to the…
Recorded option pricing datasets are not always freely available. Additionally, these datasets often contain numerous prices which are either higher or lower than can reasonably be expected. Various reasons for these unexpected observations…
Sending money in cryptocurrencies is majorly based on public keys or their hashed forms -- "addresses." These long random-looking strings are user unfriendly for transferring by other means than via copy-and-paste or QR codes. Replacing…
A significant impediment to high performance in key-value stores is the high cost of thread switching or stalls. While there are many sources for this, a major one is the contention for resources. And this cost increases with load as…
We compare two deletion-based methods for dealing with the problem of missing observations in linear regression analysis. One is the complete-case analysis (CC, or listwise deletion) that discards all incomplete observations and only uses…
Deleting data from a trained machine learning (ML) model is a critical task in many applications. For example, we may want to remove the influence of training points that might be out of date or outliers. Regulations such as EU's General…
Hashing has emerged as a popular technique for large-scale similarity search. Most learning-based hashing methods generate compact yet correlated hash codes. However, this redundancy is storage-inefficient. Hence we propose a lossless…