ARTIFICIAL INTELLIGENCE

Bipropagation is a new Deep Learning algorithm. It is much faster and much more reliable than Backpropagation. Here is the demo from the  ResearchGate and GitHub. Inner layers of the Neural Network have not hidden anymore. Learning is done layer by layer with much fewer iterations. Please cite me in your work. Click the G+   button if you like this demo. Any comments are desirable.

Raziskovalci se občasno sestanemo, da drug drugemu predstavimo svoje delo, svoje dosežke. Dobra priložnost za to so znanstvene konference. Ena naj bolj uglednih tovrstnih konferenc na področju umetne inteligence v Sloveniji z naslovom Informacijska družba 2016 , se je odvila te dni na institutu Jožef Štefan v Ljubljani. Na njej smo obravnavali mnogo zanimivih tem, ki nam nakazujejo smer razvoja informacijske tehnologije v družbi v bližnji prihodnosti. Zadnja leta je vedno bolj v ospredju umetna inteligenca in strojno učenje, trenutno v svetu še posebej odmevajo dosežki globokega učenja. Nekatere druge teme so bile: evidentiranje genetsko modificiranih organizmov v živilih, zaznavanje stresa v službi, priporočanje čtiva, odkrivanje novih zlitin, sinteza slovenskega govora, razvoj avtonomnega vozila; seveda vse skupaj na osnovi umetne inteligence. Sam sem predstavil kolegom dva nova algoritma strojnega učenja, ki sem ju razvil v bližnji preteklosti. Več o vsebini ...

Gartner is predicting a very bright near future for the "Machine learning". 2015 was a peak year of inflated expectations, now, in 2016 is following period of disillusionment and in 2017 should be reached the plateau of productivity. Elsewhere this process usually last for 10 years. One kind of the most popular modern "machine learning" is named "Deep Learning" what is another name for neural networks with little bit more layers and perhaps even with a convolution and/or recursion. The learning of this kinds networks was until now usually based on gradient descent, on slow, iterative, non-reliable process named Backpropagation . That kind of learning is very demanding and extensive. On plain computer can last for hours or even many days and is often unsuccessful concluded. Recently are appeared two algorithms that significantly improve this kind of machine learning: " Bipropagation " and " Border pairs method ". Bipropagat...

Trenutno globoko učenje (Deep learning) in z njim celotna umetna inteligenca doživlja razcvet, saj je v preteklem letu bilo doseženih nekaj pomembnih in odmevnih rezultatov kot so prepoznavanje fotografij in govora, prevajanje govorjenega besedila, pisanje besedila na osnovi podanih ključnih besed,... Danes, 12. 3. 2016 pa je bil tej zbirki uspehov dodan še en. Googlova globoka nevronska mreža ( Deep neural Network ) poimenovana AlphaGo je premagala v igri Go najboljšega igralca na svetu, Leeja Sedola . Igralna plošča azijske miselne igre GO V tej azijski miselni igri nasprotnika izmenjaje polagata črne in bele kamne na mrežo velikosti 19 krat 19. Nasprotnikovi kamni, ki so obdani z vseh 4 strani se odstranijo iz igralnega polja, cilj igre pa je zavzeti čim večji del tega polja. Rezultat zgodovinskega dvoboja med človekom in strojem je bil 3 proti 0 v korist stroja. Poraženec Lee je po dvoboju izjavil, da je pozitivno presenečen nad zmogljivostjo umetne inteligence. Ta d...

Here is given an example of the "bipropagation" algorithm for learning of NN. It is written in MatLAB language (R2015a) and is as similar as possible  to  "Deep learning" example "AutoencoderDigitsExample.m" which is included in MatLAB's Neural Network Toolbox. So you can easily compare both algorithms. I believe that my algorithm have few advantages over autoencoder. Please tell me what do you think about it. Please cite me in your works. Thanks a lot. Download demo ====================================================== %% Training a Deep Neural Network for Digit Classification % This example shows how to use the Neural Network Toolbox(TM) to train a % deep neural network to classify images of digits and is very similar to % "AutoencoderDigitsExample.m" which is included in % Neuronal Network ToolBox from MatLAB. This example is made for comparison % of both algorithms. % % Neural networks with multiple hidden layers can be usefu...