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Normal-order syntax-rules and proving the fix-point of call/cc

Normal-order direct-style beta-evaluator with syntax-rules, and the repeated applications of call/cc The presentation at the Workshop ``Daniel P. Friedman: A Celebration.'' December 4, 2004. Bloomington, IN Normal-order direct-style beta-evaluator with syntax-rules, and the repeated applications of call/cc Repeated applications of call/cc , formally , formally Normal-order direct-style beta-normalizer as syntax-rules Use (2) to prove (1) A few less common examples The title of the talk, i

Topics: cc cps lambda norm stack

Implicit ODE solvers are not universally more robust than explicit ODE solvers

A very common adage in ODE solvers is that if you run into trouble with an explicit method, usually some explicit Runge-Kutta method like RK4, then you should try an implicit method. Implicit methods, because they are doing more work, solving an implicit system via a Newton method having “better” stability, should be the thing you go to on the “hard” problems. This is at least what I heard at first, and then I learned about edge cases. Specifically, you hear people say “but for hyperbolic PDEs

Implicit ODE Solvers Are Not Universally More Robust Than Explicit ODE Solvers

A very common adage in ODE solvers is that if you run into trouble with an explicit method, usually some explicit Runge-Kutta method like RK4, then you should try an implicit method. Implicit methods, because they are doing more work, solving an implicit system via a Newton method having “better” stability, should be the thing you go to on the “hard” problems. This is at least what I heard at first, and then I learned about edge cases. Specifically, you hear people say “but for hyperbolic PDEs

Implicit Ode Solvers Are Not Universally More Robust Than Explicit Ode Solvers

A very common adage in ODE solvers is that if you run into trouble with an explicit method, usually some explicit Runge-Kutta method like RK4, then you should try an implicit method. Implicit methods, because they are doing more work, solving an implicit system via a Newton method having “better” stability, should be the thing you go to on the “hard” problems. This is at least what I heard at first, and then I learned about edge cases. Specifically, you hear people say “but for hyperbolic PDEs

Anonymous recursive functions in Racket

Anonymous recursive functions in Racket Context Some languages, like PowerShell, have “anonymous recursive functions”. That is, normally, a function needs to use a name to refer to itself to recur. But “anonymous recursion” means the language has some special mechanism by which the function can refer to itself without having to explicitly introduce a name. In some contexts, this is called an anaphoric reference. Code Here we show how we can easily implement this feature in Racket. The file a

Cloud provider Lambda may be gearing up for an IPO

In Brief Cloud provider Lambda might be following rival CoreWeave to the public markets. Lambda, an AI infrastructure company offering on-demand GPUs, has hired bankers for an upcoming IPO, according to reporting from The Information. Lambda has reportedly hired Morgan Stanley, J.P. Morgan, and Citi for a public listing that could happen as early as the first half of 2026. Lambda did not respond to a request for comment. The company has raised more than $1.7 billion in funding, according to

Lisp interpreter with GC in <750 lines of Odin (and <500 lines of C)

komplott / komplodin A tribute to: Recursive Functions of Symbolic Expressions and Their Computation by Machine, Part I (as found in paper/recursive.pdf ) A micro-subset of scheme / the original LISP in a single C file: komplott.c ! New in 2025! The LISP interpreter translated to Odin in komplodin.odin . More lines of code, but I am less familiar with the language and am translating directly from C, so there are probably ways to make it a cleaner solution. When I posted this to lobste.rs,

Topics: car cdr equal fun lambda

How to draw lambda diagrams (2020)

If you don’t want spoilers for my puzzle a few days ago, don’t read ahead! I think lambda diagrams are extremely cool, and haven’t seen any detailed description on how they work online. I’ll start by showing some very simple examples of lambda diagrams, and then build up to more complicated ones. First of all, what are lambda diagrams? They are pictorial representations of lambda expressions, and hence count as a pictorial system for a large portion of mathematics. I will assume that you under

A circle and a hyperbola living in one plot

We will see that the 3D plot of \(x^2 + (y + zi)^2 = 1\), where \(x\), \(y\), \(z\) are real and \(i\) is the imaginary unit, contains both a circle and a hyperbola. This visualization sheds light on the complex eigenvalues of real matrices. Let’s start by expanding the equation \(x^2+(y+zi)^2 = 1\) and separating it into real and imaginary parts. We get: \[\begin{align*} &\text{Real Part:} &x^2 + y^2 - z^2 &= 1, \\ &\text{Imaginary Part:} &yz &= 0. \end{align*}\] The condition \(yz=0\) split

Topics: align lambda mu real text

Entropy of a Mixture

Entropy of a Mixture Given a pair ( p 0 , p 1 ) (p_0, p_1) (p0​,p1​) of probability density functions and an interpolation factor λ ∈ [ 0 , 1 ] , \lambda \in [0, 1], λ∈[0,1], consider the mixture p λ = ( 1 − λ ) p 0 + λ p 1 . p_\lambda = (1 - \lambda) p_0 + \lambda p_1. pλ​=(1−λ)p0​+λp1​. How does the entropy H ( p λ ) = − E ⁡ X ∼ p λ ln ⁡ p λ ( X ) H(p_\lambda) = -\E_{X \sim p_\lambda} \ln p_\lambda(X) H(pλ​)=−EX∼pλ​​lnpλ​(X) of this mixture vary as a function of λ \lambda λ? The widget below

Topics: kl lambda p0 p_0 p_1

Apple @ Work: LambdaTest puts Apple Silicon to work for GenAI testing with MacStadium

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