Range-Net: A High Precision Streaming SVD for Big Data Applications

Understand

In a Big Data setting computing the dominant SVD factors is restrictive due to the main memory requirements.

• Recently introduced streaming Randomized SVD schemes work under the restrictive assumption that the singular value spectrum of the data has exponential decay.
• This is seldom true for any practical data.
• Although these methods are claimed to be applicable to scientific computations due to associated tail-energy error bounds, the approximation errors in the singular vectors and values are high when the aforementioned assumption does not hold.