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Claudia Doppioslash
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Claudia Doppioslash

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Why did Alonzo Church use lambda for function abstraction?
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hi friend 
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"Monads cannot be taught. They must be discovered."
so some helpful people made the Monad Challenges ;)
http://mightybyte.github.io/monad-challenges/ #haskell
The Monad Challenges. A set of challenges for jump starting your understanding of monads. Outline. Set 1: Random Numbers · Set 2: Failing Computations · Set 3: Permutations · Set 4: Common Abstraction · Set 5: Do Notation · Download ZIP · Download TAR · View On GitHub ...
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Vector field rendering experiment #2. Getting really great depth and structure out of this.

http://acko.net/files/dump/tiles/fieldlines2.html
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"Seen through the lens of side-effects, mocks are a flag that your code is impure, and in the functional programmer's eye, proof that something is wrong. " 
In part one of this post, I defined functional programming not from an academic perspective, or a marketing one, but in a way that will make sense to a jobbing programmer. More importantly, I hope, I defined what side-effects are in a way that makes it easy for a jobbing programmer to spot them ...
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A cool ARM emulator, with a lot of visualisation aids :D
Home · User Guide · Downloads · About. full screenshot VisUAL has been developed as a cross-platform tool to make learning ARM Assembly language easier. In addition to emulating a subset of the ARM UAL instruction set, it provides visualisations of key concepts unique to assembly language ...
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Unrelated to VisualARM!
visual6502.org/sim/varm/armgl.html
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How to Learn an Algorithm (video). I review 3 decades of our research on both gradient-based and more general problem solvers that search the space of algorithms running on general purpose computers with internal memory. Architectures include traditional computers, Turing machines, recurrent neural networks, fast weight networks, stack machines, and others. Some of our algorithm searchers are based on algorithmic information theory and are optimal in asymptotic or other senses. Most can learn to direct internal and external spotlights of attention. Some of them are self-referential and can even learn the learning algorithm itself (recursive self-improvement). Without a teacher, some of them can reinforcement-learn to solve very deep algorithmic problems (involving billions of steps) infeasible for more recent memory-based deep learners. And algorithms learned by our Long Short-Term Memory recurrent networks defined the state-of-the-art in handwriting recognition, speech recognition, natural language processing, machine translation, image caption generation, etc. Google and other companies made them available to over a billion users.

The video was taped on Oct 7 2015 during MICCAI 2015 at the Deep Learning Meetup Munich:  http://www.meetup.com/en/deeplearning/events/225423302/  Link to video: https://www.youtube.com/watch?v=mF5-tr7qAF4

Similar talk at the Deep Learning London Meetup of Nov 4 2015: http://www.meetup.com/Deep-Learning-London/events/225841989/ (video not quite ready yet)

Most of the slides for these talks are here: http://people.idsia.ch/~juergen/deep2015white.pdf

These also includes slides for the AGI keynote in Berlin http://agi-conf.org/2015/keynotes/, the IEEE distinguished lecture in Seattle (Microsoft Research, Amazon), the INNS BigData plenary talk in San Francisco, the keynote for the Swiss eHealth summit, two MICCAI 2015 workshops, and a recent talk for CERN (some of the above were videotaped as well).

Parts of these talks (and some of the slides) are also relevant for upcoming talks in the NYC area (Dec 4-6 and 13-16) and at NIPS workshops in Montreal:

1. Reasoning, Attention, Memory (RAM) Workshop, NIPS 2015 https://research.facebook.com/pages/764602597000662/reasoning-attention-memory-ram-nips-workshop-2015/

2. Deep Reinforcement Learning Workshop, NIPS 2015 http://rll.berkeley.edu/deeprlworkshop/

3. Applying (machine) Learning to Experimental Physics (ALEPH) Workshop, NIPS 2015 http://yandexdataschool.github.io/aleph2015/pages/keynote-speakers.html

More videos: http://people.idsia.ch/~juergen/videos.html

Also available now: Scholarpedia article on Deep Learning: http://www.scholarpedia.org/article/Deep_Learning

Finally, a recent arXiv preprint: On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models. http://arxiv.org/abs/1511.09249

#machinelearning
#artificialintelligence
#computervision
#deeplearning

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The first meeting of the Type Theory Study Group will happen in a few hours.
 
We'll be covering the suggestion is Chapters 1 and 2 of Practical Foundations of Programming Languages by Bob Harper.

We'll be using the second edition, currently this may be found online at http://www.cs.cmu.edu/~rwh/plbook/2nded.pdf (warning, large pdf).

As a rough content summary, these chapters lay the groundwork for the rest of the book by establishing all the math we'll be using. Because these chapters are somewhat dry, it may be interesting for us to discuss actually implementing some of the things discussed in $(your favorite PL).

Joseph Abrahamson, Craig Stuntz, and Danny Gratzer will handle leading that discussion.
This Hangout On Air is hosted by Joseph Abrahamson. The live video broadcast will begin soon.
Q&A
Preview
Live
Type Theory Study Group Meeting #1 (2015 Nov 13)
Fri, November 13, 2015, 6:00 PM
Hangouts On Air - Broadcast for free

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A writeup of my OBT 2016 keynote on the confluence of computational logic and game design.
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Mathematics with conventional linear algebra and introduction to Grassmann / geometric algebra | Crowdfunding is a democratic way to support the fundraising needs of your community. Make a contribution today!
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"According to the syntax, this function takes no inputs and returns no output, and yet it's obviously depending on something, and it's obviously doing something. The fact is, it has a hidden set of inputs and outputs."
This is my take on what functional programming really is, in a way that will make sense to a jobbing programmer just trying to Get Stuff Done. I put it to you that every function you write has two sets of inputs and two sets of outputs. Two? Only one, surely? No, two. Definitely two.
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Spiking Neural Network is a type of biologically inspired neural networks that perform information processing based on discrete-time spikes. Recently, researchers from Zhejiang University and Hangzhou Dianzi University in Hangzhou, China developed the Darwin Neural Processing Unit, a neuromorphic hardware co-processor based on Spiking Neural Networks, fabricated by standard CMOS technology. This research is reported in a paper to be published in ...
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Analysis of crickets' jumps could lead to new, tiny robots
Researchers at Johns Hopkins University are studying spider crickets' jumps, hoping to one day use their design principles to create small robots to maneuver across rough terrain like earthquake rubble.

Spider crickets — members of the Orthoptera order that originated in Asia — are good models in that they jump between earthbound and airborne states.

"Let's say you're trying to search for people after a natural disaster, and that terrain is very complex, full of nooks, holes and crannies,".
"A crawling robot could only do so much. If you had a flying robot, it would also have limitations. But if a microrobot could fly, land on any surface, and take off again, as these crickets do, it would be extremely helpful."

Watch:
https://www.youtube.com/watch?v=Ua6wauucdOo

PR:
http://hub.jhu.edu/2015/10/20/spider-crickets-jumping-robotics

#robotics   #research   #science  
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Work
Occupation
Polyglot developer (Unity3D/iOS/Android/Marmalade/Web/Whatever)
Skills
Elm, C#, Cg shader language, Unity3d, iOS, Android, Objective-C, Javascript, Clojure, Clojurescript, Boo, Lua, F#, Racket, Java, Python
Employment
  • Starship
    Game Developer, 2013 - present
    Unity3D game development, shader programming
  • Setgo Ltd
    Software Developer, 2012 - 2012
    Client SDKs on various platforms for the company's Game Analytics service
  • Racelogic
    Junior iOS Developer, 2011 - 2012
    iOS apps with MFi interfacing
  • Me
    Freelance iOS Developer, 2010 - 2011
  • Milkytea Ltd
    Mobile Game Developer, 2013 - 2013
    Unity3D mobile game development
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Tagline
Mind Contortionist and Bit Enchantress.
Introduction
Mobile game developer. 
Interested in Game AI, Shaders, Elm, Clojure, WebGL, Erlang, ObjC, Cognitive Science
Bragging rights
Meddling with the workings of the universe since 1984 - One of MCV's 100 Top women in games 2015
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Claudia Doppioslash's +1's are the things they like, agree with, or want to recommend.
NHK Easy Japanese News – Android Apps on Google Play
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Sequel. Shaw, Bernard. 1916. Pygmalion
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Developing a source code formatter for F#
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The iOS Design Cheat Sheet is a great resource for iOS designers and developers. Quickly find all important data about Apple devices when it

George Lakoff to green marketers: use the F-word
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RoboVM - Develop iPhone and iPad Apps in Java with RoboVM
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