Data Structures - Wikibooks, open books for an open world
Dec 29, 2022 · This book is part one of a series of three computer science textbooks on algorithms, continuing on to the techniques of algorithms in Algorithms and ending with Advanced Data …
Heap (data structure) - Wikipedia
stored, with their structure being implicit in the access pattern of the operations. Heaps differ in this way from other data structures with similar or
DSA Introduction - W3Schools
Data structures are essential ingredients in creating fast and powerful algorithms. They help in managing and organizing data, reduce complexity, and increase efficiency.
ISO/IEC 20248 - Wikipedia
Automatic Identification and Data Capture Techniques – Data Structures – Digital Signature Meta Structure is an international standard specification under development
vjcitn/curatedMSIData
Data structures managing published data on microsatellite instability in cancer (⭐ 1)
Inference of joint conformational distributions from separately-acquired experimental meas…
Many biomolecules have flexible structures, requiring distributional estimates of their conformations. Experiments to acquire distributional data typically measure pairs of labels separately, losing information on the joint distribution. These data a...
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic…
The transition from sequential to parallel computing is essential for modern high-performance applications but is hindered by the steep learning curve of concurrent programming. This challenge is magnified for irregular data structures (such as spars...
A Hybrid Adjacency and Time-Based Data Structure for Analysis of Temporal Networks
Dynamic or temporal networks enable representation of time-varying edges between nodes. Conventional adjacency-based data structures used for storing networks such as adjacency lists were designed without incorporating time and can thus quickly retri...
Intersection Searching amid Tetrahedra in Four Dimensions
We develop data structures for intersection queries in four dimensions that involve segments, triangles and tetrahedra. Specifically, we study three main problems: (i) Preprocess a set of $n$ tetrahedra in $\reals^4$ into a data structure for answeri...
Using Skip Graphs for Increased NUMA Locality
We present a data partitioning technique performed over skip graphs that promotes significant quantitative and qualitative improvements on NUMA locality in concurrent data structures, as well as reduced contention. We build on previous techniques of...
$(2+ε)$-ANN for time series under the Fréchet distance
We study approximate-near-neighbor data structures for time series under the continuous Fréchet distance. For an attainable approximation factor $c>1$ and a query radius $r$, an approximate-near-neighbor data structure can be used to preprocess $n$...
Inference in topic models: sparsity and trade-off
Topic models are popular for modeling discrete data (e.g., texts, images, videos, links), and provide an efficient way to discover hidden structures/semantics in massive data. One of the core problems in this field is the posterior inference for indi...
LEARN R [Introduction, Data Structures, Data ... - R CODER
This course is a set of tutorials sorted by category in which you will learn all the basics (and some more advanced content) to handle the R programming language.
Applications of Knot Theory for the Improvement of the AlphaFold Protein Database
AlphaFold, a groundbreaking protein prediction model, has revolutionized protein structure prediction, populating the AlphaFold Protein Database (AFDB) with millions of predicted structures. However, AlphaFold's accuracy in predicting proteins with i...
Perturbation and scaled Cook's distance
Cook's distance [Technometrics 19 (1977) 15-18] is one of the most important diagnostic tools for detecting influential individual or subsets of observations in linear regression for cross-sectional data. However, for many complex data structures (e....
Persistent data structure - Wikipedia
when it is modified. Such data structures are effectively immutable, as their operations do not (visibly) update the structure in-place, but instead always
Sparse One-Time Grab Sampling of Inliers
Estimating structures in "big data" and clustering them are among the most fundamental problems in computer vision, pattern recognition, data mining, and many other other research fields. Over the past few decades, many studies have been conducted fo...
Awkward Just-In-Time (JIT) Compilation: A Developer's Experience
Awkward Array is a library for performing NumPy-like computations on nested, variable-sized data, enabling array-oriented programming on arbitrary data structures in Python. However, imperative (procedural) solutions can sometimes be easier to write...
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evrencoskun/TableView
TableView is a powerful Android library for displaying complex data structures and rendering tabular data composed of rows, columns and cells. (⭐ 3186)