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Title: Integer programming for phylogenetic computations Speaker: Professor Dan Gusfield (University of California, Davis) Date: ...

A talk by Karol Węgrzycki, Max Planck Institute for Informatics, given on December 17, 2025. Integer linear programs min {cTx: Ax ...

Ganpat and Manju Engineering Center for International Collaboration and Innovation College of Engineering, Cal Poly Pomona ...

MIT 18.200 Principles of Discrete Applied Mathematics, Spring 2024 Instructor: Peter Shor View the complete course: ...

This video shows how to solve a binary problem using fathom method. The algorithm is described and the implementation is ...

Learn how to solve Linear Programming problems in Excel using the Solver add-in. This video walks through setting up decision ...

Quick explanation of mutually exclusive constraints in Integer Programming using course selection as an example!

This is an example on how to solve knapsack problem using dynamic programming based on a backward solution.

This is a simple mixed integer programming which is useful for students who want to learn on how to write a mathematical model ...

Linear Programming (LP) is a cornerstone of mathematical optimization, but real-world problems often require more advanced ...

Dan Roth, University of Illinois at Urbana-Champaign September 28, 2012 The Center for Language and Speech Processing ...

Pawel Kapuscinski - Optimizing fantasy basketball decisions with Python: linear & integer programming for roster management ...

Ever wondered about the foundational steps to tackling complex challenges? This video dives into how to systematically break ...

Title: Integer quadratic minimization over polyhedra in dimension two Speaker: Professor Robert Weismantel (ETH Zürich) Date: ...

Ever wondered how to make sense of the vast world of optimization problems? This video breaks down the fundamental ways we ...

Question: https://adventofcode.com/2025/day/10 Solution: https://github.com/woojiahao/aoc.py/blob/main/src/aoc/y2025/day10.py ...

Are the classical optimization algorithms we've relied on for decades still efficient enough for today's complex computational ...