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How to reformulate a classical discrete unconstrained optimization model into a quantum mechanical system.
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How to install Void Linux with LVM over LUKS for full-disk encryption, boot directly from kernel EFI Stub, hibernation, and per-user encryption.
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A tutorial on how to wipe, encrypt, auto mount, and decrypt an external usd drive on linux.
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Quantum Computers are advancing and one should know how to fit classical problems into them.
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Finite automata are awesome but inherently sequential.
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Did you know that Finite Automata can recognize divisibility?
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Finite automata accept a description using linear algebra that we can translate into a system of tensors or quantum circuits.
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A simple ssh workflow for interacting with Jupyter notebooks from your browser while using an HPC supercomputer’s resources.
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You may be used to sampling from probabilities, but what about sampling a random finite probability?
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Cutting planes are a powerful tool for solving stochastic programs.
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From monads to stochastic control and from fixed points to value iteration.
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Approximations by cuts are common in convex optimization.
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There are many kinds of finite automata.
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An exploration of cutting-plane approximations, a technique for representing functions via polyhedra that nicely fits into optimization problems.
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A mostly visual post illustrating the graphs for many common kinds of relations.
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By doing dynamic programming in an abstract Semiring, we discover that many classical algorithms are, in fact, calculating shortest paths.
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By delving into the realm of abstraction, we can uncover practical applications.
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Looking at Taylor series as streams of real numbers, solving differential equations becomes as easy as writing them.
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From parsing text to controling robots, dynamic programming is everywhere.
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What is the difference between automatic and symbolic differentiation?
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Writing a symbolic calculator for derivatives may sound like a hard task.
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The standard definition of average can be rather opaque.
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Ever had to program together with someone via ssh?
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All divide-and-conquer algorithms can be separated into a construction part and a merge part.
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Most introductions to recursion schemes are aimed at functional programmers.