chombier

14 ms·

151.
by chombier 8y ago
Projected Gauss-Seidel for solving (mixed) LCPs.
152.
by chombier 8y ago
The current generics proposal includes some form of ad-hoc polymorphism (overloading) on top of standard parametric polymorphism, which complicates things quite a lot. Also, choosing which compilation strategy to use has a big impact on the
153.
by chombier 8y ago
I'm also surprised, manual dictionary passing ("scrap your typeclasses"-style) seems way simpler.
154.
by chombier 8y ago
A more direct derivation: if you normalize the quaternion product y * x, you get twice the rotation taking x to y. So you need the square root of that, which you can obtain by adding 1 to the real part, then normalize again. This directly
155.
by chombier 8y ago
Thank you so much for this nice summary.
156.
by chombier 8y ago
one of the most intriguing/funny things about dual numbers (and dual quaternions in particular) is how they encode the derivative of the real part into the dual part, and how everything plays out nicely algebraically. this could be a n
157.
by chombier 8y ago
I am surprised nobody mentioned python's weird scoping rules for local variables. It bit me countless times.
158.
by chombier 8y ago
Can somebody comment on why is this PEP controversial?
159.
by chombier 8y ago
I most definitely agree with you, however this brings us even further away from the author's setting.
160.
by chombier 8y ago
The sum operator is linear, so its derivative is itself: the derivative of the sum is the sum of derivatives. Same goes for multiplication by a scalar. From this you obtain that the derivative of any linear combination is the linear combina
161.
by chombier 8y ago
Of course you are correct, even though one could argue the linearity of differentiation is a property you can obtain by differentiating in coordinate charts , where the reasoning is still valid. In any case, it is probably a good thing to
162.
by chombier 8y ago
Well this is the whole point of derivatives (i.e. tangent maps): to be linear approximations of functions. So yes, a linear approximation of a linear function is the function itself.
163.
by chombier 9y ago
Erik Meijer gave a talk about this at KotlinConf last year https://www.youtube.com/watch?v=NKeHrApPWlo
164.
by chombier 9y ago
It made me wonder whether OP's goal was no in fact to drive people away from Perl by posting this.
165.
by chombier 9y ago
Is there a documentation about the type system somewhere?
166.
by chombier 9y ago
I see, thanks for the precision!
167.
by chombier 9y ago
I thought Fω was an extension of System F with type operators, so I figured if System F can check self-application, System Fω can too. Am I missing something else?
168.
by chombier 9y ago
Besides, actually making a struct everytime is not that bad in practice. I also understand (and strongly support) the committee's desire not to introduce yet another language construct when a library solution can be worked out, given t
169.
by chombier 9y ago
Can somebody comment on what is missing for System F(ω) to be Turing complete? I recall that it can typecheck self-application, so is it not possible to define and use the fixed-point combinator?
170.
by chombier 9y ago
The easiest would be to first give cython a try, as it can provide a nice performance boost at a minimum effort in some cases. If you just need to bind simple number crunching functions, you may also write a small library exposing them with
171.
by chombier 9y ago
How is Jacobian transpose control an ahead-of-time IK? And how would you do IK without at least approximating the Jacobian?
172.
by chombier 9y ago
A little old, but still one of the best resources for humanoid control: http://www.cds.caltech.edu/~murray/mlswiki/index.php/Main_Pa... It has a chapter on closed-form IK for simple structures, and one on Jac
173.
by chombier 9y ago
To me, the issue is not the type system being TC, which may or may not be desirable depending on applications. What is a bit unsettling is that somebody noticed that it was in fact TC: this property should be clear from the type system de
174.
by chombier 9y ago
I realize I misread parent comment functions: always<A>(x: A): Parser<A> thenDependent<A, B>(a: Parser<A>, b: A -> Parser<B>): Parser<(A, B)> as: always<A>(x: A): Parser<A> t
175.
by chombier 9y ago
Monadic parser combinators! There is a nice paper on the subject by Graham Hutton and Erik Meijer. It's a very good introduction to both parser combinators and monads, and it's very readable even for beginners.
176.
by chombier 9y ago
I think his point is about reinventing the wheel due to insufficient theoretical background.
177.
by chombier 9y ago
Can somebody explain why this is interesting computationally-wise? It looks like standard derivation to me.
178.
by chombier 9y ago
This is beautiful. I especially like how the type environments naturally arise from lexical scope during macro expansion. The fact that this composes all the way up from simply typed lambda-calculus to F-omega is pretty impressive.
179.
by chombier 10y ago
If I am not mistaken you will always need a GC for cyclic data structures, which you can't type linearly.
180.
by chombier 10y ago
From the Kotlin spec: http://jetbrains.github.io/kotlin-spec/#_type_inference "Type inference is conservative — it may fail to find suitable assignment of type-arguments to the type-parameters despite that one exi

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