PUBLIC MARKS from ogrisel with tag modeling

CVXMOD is a Python-based tool for expressing and solving convex optimization problems. It uses CVXOPT as its solver. It is developed by Jacob Mattingley, as PhD work under Stephen Boyd at Stanford University. CVXMOD is primarily a modeling layer for CVXOPT. While it is possible to use CVXOPT directly, CVXMOD makes it faster and easier to build and solve problems. Advanced users who want to see or manipulate how their problems are being solved should consider using CVXOPT directly. Additional features are being added to CVXMOD beyond just modeling. These are currently experimental. CVXMOD has a similar design philosophy to CVX, a convex optimization modeling language for Matlab®, and uses the principles of disciplined convex programming, as developed by Michael Grant, Stephen Boyd and Yinyu Ye.

Relational databases are universally conceived of as an advance over their predecessors network and hierarchical models. Superior in every querying respect, they turned out to be surprisingly incomplete when modeling transitive dependencies. Almost every couple of months a question about how to model a tree in the database pops up at the comp.database.theory newsgroup. In this article I'll investigate two out of four well known approaches to accomplishing this and show a connection between them. We'll discover a new method that could be considered as a "mix-in" between materialized path and nested sets.

First mail of a thread on the postgresql mailing list dealing of various ways to implement a tree structure with PostgreSQL.

This document describes an approach for handling hierarchical data in a relational database.

Denormalization is the process of attempting to optimize the performance of a database by adding redundant data. It is sometimes necessary because current DBMSs implement the relational model poorly. A true relational DBMS would allow for a fully normalized database at the logical level, while providing physical storage of data that is tuned for high performance.

Heuristics for denormalizing relational database tables are examined with an objective of improving processing performance for data insertions, deletions and selection. Client-server applications necessitate consideration of denormalized database schemas as a means of achieving good system performance where the client-server interface is graphical (GUI) and the network capacity is limited by the network channel.