CORDIS Project
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The project focuses on redefining how data is utilized in learning algorithms by exploring trade-offs between data size, running time, and other resources. It aims to develop a mathematical framework and prototype hardware to optimize these trade-offs across various domains, including scientific imaging and materials s…
Massive data poses a fundamental challenge to learning algorithms, which is captured by the following computational dogma:
The running time of an algorithm increases with the size of its input data.
The available computational power, however, is growing slowly relative to data sizes.
Hence, large-scale problems of interest require increasingly more time to solve.
Our recent research demonstrates that this dogma is false in general, and supports an emerging perspective:
Data should be treated as…
ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
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