idunning

34 ms·

121.
by idunning 13y ago
It is open-source software, not a walled garden - there are going to be multiple options, and they are not going to all be named ["PLOTTINGISHERE$i" for i in 1:4]. If you like MATLAB/pyplot/matplotlib style, PyPlot.jl is
122.
by idunning 13y ago
A lot of mathematics (and real life, but lets not go there) is written 1-based, which makes it quite a pleasure to translate algorithms into Julia. But I don't think its a big criticism OR selling point really - sometimes its good, som
123.
by idunning 13y ago
Startup times are not fantastic with packages. This hasn't been a big area of focus yet, but there is a roadmap for getting this down. Its definitely a typo. Stable release is currently 0.2 (released near end of 2013) and upcoming vers
124.
by idunning 13y ago
I'd agree about it being a fluff piece, although I think the binary options you present aren't fair. I'm not a core developer on Julia, just a user and package creator. It is geared towards technical/scientific computin
125.
by idunning 13y ago
Just a little hacked together holiday project, interested to hear how you find it useful/useless!
126.
Optimally plan your Christmas meals with PingPots(pingpots.com)
2 points by idunning 13y ago|2 comments
127.
by idunning 13y ago
They can be OK if being optimal isn't a concern, or the problem isn't too hard.
128.
by idunning 13y ago
Not sure exactly, but I guess the dirty tricks are what really makes the difference. If you want to optimally solve a TSP, and know you are optimal when you stop, this is the approach you would use in practice - as far as I know it is the o
129.
Using Julia+JuMP to Solve a TSP with Lazy Constraints(iaindunning.com)
52 points by idunning 13y ago|6 comments
130.
by idunning 13y ago
We implemented a "serious" version of simplex algorithm for linear programming (sparse-matrix / sparse-vector operations that can't be handled by standard libs), and we got performance no worse than half of the equivalen
131.
by idunning 13y ago
Must be frustrating! Octave provides a valuable service to the community.
132.
by idunning 13y ago
Julia does support vectorization just like MATLAB, but I think what you may be referring to are some of the speed traps that currently exists where undesireable/unnecessary copies occur. This is often in practice the reason that writin
133.
by idunning 13y ago
Agreed - its always a sinking feeling to see code attached to a paper and see that its MATLAB or, even worse, MATLAB+some toolkit/addon. Of course, still better than seeing a paper without ANY code...
134.
by idunning 13y ago
I think its fair to say that it shines for numerical computation, but you can perform other tasks with Julia with ease. For example, the idea of writing some number-crunching as a webservice with MATLAB or Octave is not an option, but with
135.
by idunning 13y ago
I don't think speed is the only reason for using it - from my perspective in this context its more like free (in both senses) drop-in replacement for MATLAB, but with less "weirdness" than MATLAB (and Octave) that is also fas
136.
Representation, Filibusters and the US Senate(iaindunning.com)
1 points by idunning 13y ago|0 comments
137.
by idunning 13y ago
Here are the slides for a recent talk we gave about JuliaOpt: https://docs.google.com/presentation/d/1FlHt245YxPXFwOHmxLYW...
138.
by idunning 13y ago
That line of development hasn't been pushed very hard yet, but the fundamentals are good. For a example, check out http://iaindunning.com/2013/sudoku-as-a-service.html where I make a nice little webservice.
139.
by idunning 13y ago
I'm taking this class right now and it is certainly an interesting twist on the topic - its fun to see how many different ML techniques solve variants of a single base problem that you can analyze with statistical learning theory. Also
140.
by idunning 13y ago
It is primarily to showcase JuMP, yes. I also hoped it'd introduce more people to MIP, something not often covered in CS education. As for using other techniques, I don't think it necessarily makes more sense to use them. The natu
141.
Solving an Urban Planning Puzzle with JuMP + Julia(iaindunning.com)
17 points by idunning 13y ago|3 comments
142.
Solving a Combination Lock Puzzle with JuMP and Julia(iaindunning.com)
28 points by idunning 13y ago|10 comments
143.
by idunning 13y ago
Theres been some work towards that: https://github.com/hackerschool/Meddle.jl is "middleware", and https://github.com/hackerschool/Morsel.jl is a framework. The main issue right now is t
144.
by idunning 13y ago
It is a lot of fun, quite addictive! Let us know what you cook up at the julia-users google group. Re: optimization, that is indeed usually true, although I imagine the actual sudoku solve time dominates the request time. From a code design
145.
Sudoku as a Service with Julia(iaindunning.com)
62 points by idunning 13y ago|12 comments
146.
by idunning 13y ago
Definitely seeing activity in the machine learning community, and a colleague and I are introducing it to the optimization/operations research community: http://www.optimization-online.org/DB_HTML/2013/05&#x2F