ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization.
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Fast In-Memory Data Compression Algorithm (header-only C/C++) 540+MB/s compress, 3000+MB/s decompress, ratio% better than LZ4, Snappy, and Zstd@--1
- data-compression
- lz77
- compression
- compression-algorithm
A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
- optimization
- optimization-algorithms
- optimization-methods
- optimization-problem
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
- data-analytics
- data-cleaning
- data-cleansing
- data-engineering
A general-purpose lightweight C++ graph library
- graph
- bfs
- dfs
- graph-algorigthms
Bolt is a C++ template library optimized for GPUs. Bolt provides high-performance library implementations for common algorithms such as scan, reduce, transform, and sort.
Unicode Algorithms Implementation for C/C++
- unicode
- utf-16
- utf-8
- utf16
A c++ toolbox of locality-sensitive hashing (LSH), provides several popular LSH algorithms, also support python and matlab.
Very fast, high-quality hash function, discrete-incremental and streamed hashing-capable (non-cryptographic, header-only C/C++) 27GB/s + PRNG
Various open addressing hashmap algorithms in C++
Multi primitive-to-primitive (MP2P) ICP algorithms in C++
- slam
- icp
- point-clouds
- registration
Cheat sheet for ACM-ICPC. In memory of those good old days.
- acm-icpc-handbook
- algorithms
- acm-icpc
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
- svm
- regression
- classification
- machine-learning