Your English writing platform
Discover LudwigSuggestions(1)
Exact(1)
The well-known vector quantization (VQ) can represent any fixed-length lossy source coding, but requires too much computation resource.
Similar(59)
Compared with the latest work, we can get 1.48 times speedup and use 19% more memory with much less computation resources (34.5% less ALUTs and 46.1% less Regis-ters).
These analyses require considerably much computation time.
Moreover, it can save much computation for subsequent processing.
It can provide high performance but takes much computation time.
The technique thus reduces the computation resource at sensor nodes.
Therefore, mobile devices can select the most adaptable computation resource to execute their offloaded computations.
Then, a computation resource in the cloud system is dynamically assigned for the requested offloading computation.
Is there too much computation in the world of language translation?
The pathway model presented here is primarily designed to function as a computation resource.
However, for long sequences, these methods may require too much computation overhead and memory.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com