cf

20 ms·

151.
by cf 10y ago
My presumption is that we will interact with most computers through wireless devices. For example, the chromecast has no buttons on it, and I haven't felt limited by that.
152.
by cf 10y ago
Sure. I tend to keep my postprocessing of a model under version control. In particular, what features were most helpful for predictions.
153.
by cf 10y ago
PMML is fairly verbose and limited to a particular set of models. It's often easier to pickle the models and then keep tagged versions. I think a human readable format could be created, but since most models are just a pile of numbers
154.
by cf 10y ago
Yes but in this particular instance Uber recruits heavily in the Bay Area. If all workers in the Silicon Valley office refused to work and discouraged others to work for Uber it could be quite effective.
155.
by cf 10y ago
Can you share your PCPartPicker list? I'm curious how the costs breakdown.
156.
by cf 10y ago
A lot of people from Iran and other countries were also trying to get home that day. They couldn't call an Uber.
157.
by cf 10y ago
Although to do serious production level ML, I agree that you need to understand the math. But as a starting point, the machine learning for hackers is a great place to start. I think writing some algorithms and using them to solve problems
158.
by cf 10y ago
Since the comments section of a news website is a major source of engagement, why not charge to make comments? Wouldn't this discourage the worst of the them?
159.
by cf 10y ago
If the problem is painful enough, it doesn't matter if the function is trivial.
160.
by cf 10y ago
I expect no significant challenges in porting to more recent version of GHC. Some version bounds will need to be loosened and an Applicative instance added for the Measure monads. Also if you have any feature requests for that version I&#x2
161.
by cf 10y ago
That's the concrete syntax for the language. It was chosen to be make the language more familiar to people who do machine learning in Python. The embedded design we had made it very challenging to develop new inference algorithms and t
162.
by cf 10y ago
I think PyMC is a much more mature solution. Also while PyMC is much more focused on sampling, Hakaru is more focused on Bayesian inference and trying to represent stochastic models in a way such that any inference algorithm could be applie
163.
by cf 10y ago
It doesn't require a Maple license exactly. Maple is just needed to use the simplifier. It is perfectly possible to write and run Hakaru programs without having Maple installed.
164.
by cf 10y ago
There are two lines of research in this direction. So there is work from my lab [1] and some folks at ETH-Zurich [2] is automatically finding closed form solutions. These when used do give performance equivalent to handwritten methods. Beyo
165.
by cf 10y ago
So there has been work done in compiling probabilistic programs directly into C or C++ [1]. Your intuition is correct that in many of these languages if you wrote an HMM and did MAP inference over it you wouldn't recover the Viterbi al
166.
by cf 10y ago
Sure. I will also continue to answer any questions others have about these systems on this thread.
167.
by cf 10y ago
It depends on what you are looking for in a probabilistic programming system. If you want something that is more of a library than a language you gain the advantages of being integrated into a mainstream language. This would point to system
168.
by cf 10y ago
I ask since I work on probabilistic programming in Haskell and am always looking for more use cases. Good luck and I hope the work is published.
169.
by cf 10y ago
Oh really. Is this Haskell program anywhere online?
170.
by cf 10y ago
That's why you need to bring some of those thin Japanese whiteboard markers. http://www.jetpens.com/Zebra-Mackee-Wet-Erase-Double-Sided-M...
171.
by cf 11y ago
This is a fantastic point. Sometimes when someone hands me a study I will ask what is the effect size. In some studies, even if there was a discernible effect, there is no hope for it to be anything but a small effect.
172.
by cf 11y ago
It's really odd for him to keep harping on Mathematica when the LIGO computations were clearly done in a Python ecosystem as shown in: http://journals.aps.org/prl/pdf/10.1103/PhysRevLett.116.0611... htt
173.
by cf 11y ago
It's worth mentioning that Terra ( http://terralang.org/ ) is pretty cool on its own terms.
174.
Terra: A Multi-Stage Language for High-Performance Computing(terralang.org)
2 points by cf 11y ago|0 comments
175.
by cf 11y ago
I'm always fascinated by these simulated sounds. Is there any resource for simulating other instruments like trumpets and drums?
176.
by cf 11y ago
I think the landmarks are just less well-known. Things like the Getty and Griffith Observatory. Others are generic, but instantly recognizable, like Venice boardwalk and the LA river.
177.
by cf 11y ago
I think its helpful to define concepts like interpretation and compilation. Interpreters take a program and produce a value. Compilation takes a program and returns another program that hopefully when interpreted gives the same value. In so
178.
by cf 11y ago
I think we are broadly in agreement. When I say coding up inference for a particular model, that includes deriving the equations and updates needed. This effort is nonzero for all inference methods, but is much lower for MCMC.
179.
by cf 11y ago
I know STAN and Figaro are going to push out inference methods like I mention, but my hope is eventually all of the ones mentioned in the article do this. I like thinking of this in terms of the standard library that needs to be built out.
180.
by cf 11y ago
What's interesting about most complaints of these systems is people talk about their poor performance or scalability? That is usually more a consequence of using MCMC or other inference algorithm than the language itself. MCMC is a ver

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