about
Quantum Deep Learning (arxiv.org)
44 points by jonbaer on Dec 15, 2014 | hide | past | pdf | 14 comments on HN

In plain words: A quantum computer trains a learning network that normally needs slow, approximate steps, letting its units settle into good settings faster. It cut training time and found better settings, and could train fuller, fully connected versions that classical training struggles with.

Abstract

In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on conventional, classical computers. We show that quantum computing not only reduces the time required to train a deep restricted Boltzmann machine, but also provides a richer and more comprehensive framework for deep learning than classical computing and leads to significant improvements in the optimization of the underlying objective function. Our quantum methods also permit efficient training of full Boltzmann machines and multi-layer, fully connected models and do not have well known classical counterparts.

Nathan Wiebe, Ashish Kapoor, Krysta M. Svore
arXiv:1412.3489 · quant-ph, cs.LG, cs.NE · submitted Dec 10, 2014 · updated May 22, 2015
abstract · pdf · html · 34 pages, many figures

add comment on HN
Also discussed: Dec 2014 (7 points, 0 comments)

The paper mentions a quantum oracle for training the quantum memory I guess used to store the system. So would a quantum computer even be able to utilize quantum deep learning without such access to storage?
Great question, the answer is that quantum oracles aren't needed for the idea to work but in some cases it might be a really useful thing to have. First off, just to be clear the idea of the algorithm is basically to use a quantum computer to directly sample from probability distributions that ordinary computers are stuck approximating. However in order to do so, the algorithm has to interact with the data in some manner. The quantum oracle really just serves as an abstraction for whatever method is used to input the data.

The first approach considered in the algorithm really doesn't need a quantum oracle. Since that algorithm only requires that you sequentially feed the input data you want to train the system with, you don't need any sophisticated quantum algorithm to provide an entangled mixture of the data used to train the system.

The second algorithm we consider does use a quantum oracle (meaning a quantum device that allows the quantum computer to prepare an entangled mixture of input training examples). In practice, if you have a database of training vectors (like MNIST handwriting images that you want to recognize) then you'd need to make a giant quantum computer that stores all of this and allows quantum access to this. This could be done using a QRAM (although not all quantum computer designs have efficient QRAM).

Alternatively, the quantum oracle could be any other quantum algorithm that you want to learn about. One idea that I'm a little obsessed with is the idea of using a quantum simulation subroutine as the quantum oracle. Then this approach allows you to train a deep Boltzmann machine to learn features of the system that the subroutine is simulating. Ideas like this could really accelerate drug testing and development by using AI and quantum simulation simultaneously to focus in on promising candidate drugs without requiring as much trial and error as current methods.

At work we've spent some time talking about the idea of using a quantum computer to do inference over a probabilistic knowledge graph. It seems like a natural match.

I actually did some preliminary investigations, but unfortunately using factor graphs as a way of quantum state is apparently an area of active research. That makes searching for using quantum computers to calculate factor graph traversal pretty hard!

This paper looks pretty interesting though.

Quantum computing enabling DNA computing to solve for non-linear matricies might work.
Sounds like something a quantum Markov chain would say.
I'm simply saying that todays platforms are not cut out to support DNA computing or the simulation of it. Sorry I sound like a robot, I'm not very social.
lol, some of his comments certainly look like generated :D
thanks, made me lol.
Do you have a log of your research into this?
No, sorry.

"Research" is probably an exaggeration, it was mostly some Googling on a Friday afternoon, and some whiteboard scribbles and reading the D-Wave docs.

Some of my colleagues have talked to D-Wave previously, so we are only mostly ignorant.

Quantum = metric or measure, after reading the abstract, I think it's cool, but I'm more info Fuzzy State Machine influenced designs, like a hybrid neural fuzzy system.

The extra, "Fuzzy," makes it better. With two data points, you get sets of attributes, ad infinitum. Rather than trying to simply point out what ones are common, or good, or match any given specific outcome, etc. I like infinitely awesome attributes.

Tastes like bacon.

Have you ever tasted the difference between fuzzy logic influenced design and the probabilistic stuff? Infinitely more delicious.

Case in point: sometimes, you simply want to know an expectation was met - or not; and that there was the initial "expectation." Once this becomes clear, the chain of trust is easily, "fuzzed," to get some interesting outcomes.

Sigh; whoever nuked my karma, a short story to help you understand. Though I'm after good teachers, perhaps you can follow up?

Research a "three dimensional model of taste," which doesn't exist (yet). Why? Think of a six sided dice, every facet, which combined with it's twin, adds up to seven, a prime.

Now, extrapolate from the flavors you've enjoyed the following: 1. Sweetness - strawberry perhaps? 2. Sourness - a lemon? 3. Saltiness - a saltine cracker maybe? Thirsty? 4. Bitterness - funny how the lips pucker from Grapefruit. 5. Umami / savory - we might not officially recognize this in some places, but we all know "savory," - potatoe soup's a favorite of mine. 6. Spicy - are you feeling the heat, yet?

Now, compare that to any given model of flavor...I'm waiting. Thanks :)

It doesn't match, does it? With taste & smell, alone, a human being can sense four dimensions...all three axes, X, Y and Z on the Cartesian plan. Oddly enough, most flavor models left out, "Spicy," and after I saw a German guy's head nearly explode from a Thai Chili Pepper, I knew, *spicy exists

What's the fourth, for the person who can't see, who can't hear, who can't talk?

Time. If you can taste, taste changes over time. If you can feel, you're Hellen Keller and can understand Braille.

Now, Helen Keller - please next time, throw me some of your clearly larger, more infinite, more awesomely epic knowledge, because I'm confused.

I'm also blind, can't hear, and can't see. When you sh!t on my, "Karma," and refuse to share your overwhelmingly superior knowledge...

...well, we all know :)

Quantum computers are impractical devices and will never be built.
Never is an awfully long time.