Max-Margin Markov Networks
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
- Stanford University
- Organisation type
- Academia
- Country
- United States of America
- Published
- 1 March 2004
- Authors
- B. Taskar, C. Guestrin, and D. Koller
What it does
The problem areas the model was built for. A model can carry several of each.
- Domain
- Vision, Language
- Task
- Image classification, Text 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
- 4,800 tokens
The data set is divided into 10 folds of ∼ 600 training and ∼ 5500 testing examples. The accuracy results, ... are averages over the 10 folds
How it is classified
Labels the source dataset applies when tracking notable models, and how confident it is in the entry.
- Citations
- 1,764
Sources
Where this record came from and when it was last checked.
- Reference
- Max-margin markov networks
- Last updated
- 28 November 2025
What the numbers mean
About this model
Max-Margin Markov Networks was published by Stanford University, in the country recorded as United States of America, during March 2004. The publishing organisation is categorised as academia.
It works in the domain of Vision, Language, and is recorded as performing the task of image classification, Text classification.
Its weights were never published, so it can only be reached through its provider. No graphics card changes that.
Training and provenance
Training consumed a corpus of around 4,800 tokens of text.
Answers
Max-Margin Markov Networks — common questions
Max-Margin Markov Networks— what is it used for?
It works in the domain of Vision, Language, and is recorded as handling the task of image classification, Text classification. Models frequently carry more than one of each, and the tags describe purpose rather than capability limits.
Max-Margin Markov Networks— what GPU do I need to run it?
None. This 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.
Max-Margin Markov Networks— is it open source?
The licensing was never recorded in our source data. We treat unstated licensing as closed, because an unrecorded licence is not one to rely on.
Max-Margin Markov Networks— how many parameters does it have?
No parameter count has been published for it, which is why no memory or speed figure appears on this page.
Max-Margin Markov Networks— who created it?
It was published by Stanford University, based in United States of America, an organisation categorised as academia.
Max-Margin Markov Networks— when was it released?
It was published in March 2004. Capability per parameter has improved considerably since, so a newer model of the same size is often the better use of the same hardware.
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.