Optimized Single-layer Net
No estimate
No hardware requirements for this model
The weights for this model have not been published, so it cannot be downloaded or run on your own hardware at any size. It is reachable only through its provider, and no graphics card changes that.
On record
Full specification
Everything on record for this model. Most of it describes how it was trained rather than how it runs — useful context for judging how much work went into it, and how it compares with models built at a different scale.
Origin
Who built this model, where, and when it was published.
- Organisation
- University of Michigan,Stanford University
- Organisation type
- Academia,Academia
- Country
- United States of America
- Published
- 11 April 2011
- Authors
- A Coates, A Ng, H Lee
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision
- Task
- Image classification
Size
How large the model is and how much data it was trained on. Parameters are the figure that decides whether it fits on a given graphics card.
- Training data
- 50,000 tokens
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Record confidence
- Unknown
- Citations
- 4,240
Sources
Where this record came from and when it was last checked.
- Reference
- An analysis of single-layer networks in unsupervised feature learning
- Last updated
- 1 January 2026
What the numbers mean
What this model is
Optimized Single-layer Net was published by University of Michigan,Stanford University, in United States of America, in April 2011. academia,Academia is the category the publisher falls under.
It works in Vision, and is recorded as doing image classification.
Because the weights are not available, none of the hardware figures elsewhere on this site apply to it.
What went into building it
The training set ran to roughly 50,000 tokens.
Answers
Optimized Single-layer Net — common questions
What GPU do I need to run Optimized Single-layer Net?
None. Optimized Single-layer Net is a closed model — its weights were never published, so it cannot be downloaded or run on your own hardware at any price. It is reachable only through its provider.
Is Optimized Single-layer Net open source?
The licensing for Optimized Single-layer Net was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
How many parameters does Optimized Single-layer Net have?
No parameter count has been published for Optimized Single-layer Net, which is why no memory or speed figure appears on this page.
Who created Optimized Single-layer Net?
Optimized Single-layer Net was published by University of Michigan,Stanford University, based in United States of America, categorised as academia,Academia.
When was Optimized Single-layer Net released?
Optimized Single-layer Net was published in April 2011. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
What is Optimized Single-layer Net used for?
Optimized Single-layer Net works in Vision, and is recorded as handling image classification. A model can carry several of each, so these are the areas it was built for rather than a limit on what it will attempt.
The other direction
Looking at it from the other side?
This page starts from the model. If you already own a card and want to know everything it will run, start from the hardware instead.