'
MLC@Home: Machine Learning Comprehension @ Home

MLC@Home is a distributed computing project dedicated to understanding and interpreting complex machine learning models, with an emphasis on neural networks. It uses the BOINC distributed computing platform.

Opening the Black Box
https://xkcd.com/1838/
XKCD #1838

Neural Networks have fuelled a machine learning revolution over the past decade that has led to machines accomplishing amazingly complex tasks. However, these models are largly black boxes: we know they work, but they are so complex (up to hundreds of millions of parameters!) that we struggle to understand the limits of such systems. Yet understanding networks becomes extremely important as networks are deployed in safety critical fields, like medicine and autonomous vehicles. Models must be vetted for robustness against adversarial examples, biases need to be identified and compensated for, and boundaries for what the network will produce need to be identified.

What MLC@Home Does

MLC@Home provides an open, collaborative platform for researchers studying machine learning comprehension. It allows us to train thousands of networks in parallel, with tightly controlled inputs, hyperparameters, and network structures. We use this to gain insights into these complex models.

MLC@Home's initial project, the Machine Learning Dataset Generator (MLDS), will generate a large dataset of simple networks trained with both clean and adversarial data. To our knowledge, this is the first dataset of its kind. MLC@Home also welcomes project proposals from other researchers aligned with this research area. MLC@Home requests that all data generated by our supported projects be made available to the public, and that, where possible, any papers and analysis be made public as well.

MLDS Live Status
Dataset 1
NameCompleteIn ProgressTotal
SingleDirectMachine 10002 0 10004
EightBitMachine 10001 4 10007
SingleInvertMachine 10001 0 10003
SimpleXORMachine 10000 0 10002
ParityMachine 869 9135 10012
Dataset 2
NameCompleteIn ProgressTotal
ParityModified 260 9745 10005
EightBitModified 6442 3564 10006
SimpleXORModified 10005 0 10005
SingleDirectModified 10004 0 10004
SingleInvertModified 10002 0 10002
Dataset 3
Overall Completed: : 34737/40125
Milestone 1 (100x100) : COMPLETE (10000/10000)
Milestone 2 (1000x100) :
371374373319354334317266368292
263324354372257315358369346369
367374373376356236378341368378
376353347368367299365325376363
364372347348371366341353306262
361359319340369361367330375372
366377290297370368367355368369
355376359368280374370372367364
369371226372325351380289375259
369373359345367336367368349311
0% < 25% 25% - 75% >75% 100%
Last update: 2020-10-25 03:45:10.277202