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View Code? Open in Web Editor NEWA meta-study of research related to associative memories.
A meta-study of research related to associative memories.
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This paper introduces what paper #31 calls a "Boltzmann Machine" that can be used for autoassociative memory.
According to an article I read (#31) this paper proposes a model called "Brain-states-in-a-box" or "BSB" for short.
This paper introduces what paper #31 calls a "Hamming Network" that can be used for autoassociative memory.
Notes from the startup meeting (meeting 1). Things to do before next meeting.
Suggested paper which merges the fields of machine learning with psychology.
Write a project proposal.
Should roughly contain the following sections.
This issue tracks everything related to preparations for the presentation.
There are a number of topics we may wish to discuss.
How do we want to present the findings of our meta-study? In what format?
Any other ideas? There will be many presentations given during the day, lets spice it up a little!
Notes about the presentation:
@Chilinot and @chrisking2020, would you be alright with releasing our work into the public domain? Another alternative might be to use a Creative Commons license.
Personally, I'd be very happy to release the work into the public domain.
Cheers
Identify a rough starting point for the meta-study research.
Which papers are key within this field?
Have other meta-studies been done within this field? Which papers did they refer to?
Interesting papers from other disciplines. What does neuroscience have to say about associative memories?
What about psychology (cognitive psychology, biological psychology, ...)?
Other fields
Please add to this list as you find more resources that may be a good starting point for the meta-study research.
We should try to have a rough project plan figured out before the first meeting.
Which are the major tasks within the project?
If you've got any ideas on what to add to the project plan, or how to structure and track each task, feel free to discuss.
As this is a meta-study, the related work, or background research section will be the main content of the paper. Therefore, this section has been split into several sub-tasks, to be tracked by meeting deadlines.
For each of these sub-tasks a set of research papers (see #1) will have been read, reviewed, critically evaluated, and summarized in the report.
TODO: Add specific research papers to be read, critically evaluated and summarized by each project member for this sub-task.
As this is a meta-study, the related work, or background research section will be the main content of the paper. Therefore, this section has been split into several sub-tasks, to be tracked by meeting deadlines.
For each of these sub-tasks a set of research papers (see #1) will have been read, reviewed, critically evaluated, and summarized in the report.
TODO: Add specific research papers to be read, critically evaluated and summarized by each project member for this sub-task.
This is a meta-issue for the project report, tracking its progress. The specific sections have dedicated issues tracking their progress. Once all sections have been completed, and we have proof-read the report, this issue may be closed.
Now we conduct the full literature review, trying both to objectively outline what has been done within the field, compare the results of different approaches, and critically evaluating what has been written. Are the authors clearly stating the assumptions that their work build upon, if the work generalizes or if it is only capable of solving specialized problems. This is particularly important, as the term associative memory may be vague and many authors may try to solve different problems, thus making their results difficult to compare objectively.
This issue is meant to track discussions related to identifying the aim and objective of the project.
From ML course information 2016.pdf
:
Survey some sub-field of machine learning, i.e. search for scientific papers on a subject,
summarize them, identify open and closed problems and define the 'state of the art',
TODO: Olle pointed out that we should define what we mean by associative memories, to make the aim and objective clearer. This should be easier once we finish the preliminary literature review (tracked by issue #1).
The primary aim of the project is to identify open and closed problems related to machine learning approaches to achieve associative memories. A secondary aim of the project is to compare the 'state of the art' machine learning approaches to human capabilities for associative memories, as understood by neuroscience, psychology and other research disciplines.
To achieve the primary aim of the project, the following objectives have been identified.
To achieve the secondary aim of the project, the following objectives have been identified.
We still need to discuss and figure out the details regarding what we wish to achieve with this project. Once we know what we want to achieve, it is easy to break this down into a set of objectives which would help us reach this aim. This discussion will be fueled by whatever we may uncover from the preliminary literature review, the starting point of which is tracked in #1.
Skeleton of the report.
Short, catchy, true. 2 seconds to grab attention.
Prior work is a subset of related work. Prior work may be introduced in the introduction.
[1]
in [42], foo says bar
. References should be invisible. Foo Bar describes, blah blah [42].
As this is a meta-study, the related work, or background research section will be the main content of the paper. Therefore, this section has been split into several sub-tasks, to be tracked by meeting deadlines.
For each of these sub-tasks a set of research papers (see #1) will have been read, reviewed, critically evaluated, and summarized in the report.
TODO: Add specific research papers to be read, critically evaluated and summarized by each project member for this sub-task.
Identify key models of associative memory.
Other key models, not included in the report.
From other fields (such as psychology).
As this is a meta-study, the related work, or background research section will be the main content of the paper. Therefore, this section has been split into several sub-tasks, to be tracked by meeting deadlines.
For each of these sub-tasks a set of research papers (see #1) will have been read, reviewed, critically evaluated, and summarized in the report.
TODO: Add specific research papers to be read, critically evaluated and summarized by each project member for this sub-task.
A heavy and in-depth article. I have currently not read through it in its entirety, but I don't think we need a full review in the article as of now.
Short summary:
The article is a very in-depth analysis and discussion on how an interactive memory or what we would call a "Linear Associative Memory" today would be constructed using artificial neural networks. It even includes some sections where animal testing has been performed on monkeys in order to understand how neuron interact with each other.
Nugent, Michael Alexander, and Timothy Wesley Molter. "AHaH Computing–From Metastable Switches to Attractors to Machine Learning." PloS one 9.2 (2014): e85175.
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