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math.NA2026
Stochastic Gradient Descent for Incomplete Tensor Linear Systems
Anna Ma, Deanna Needell, Alexander Xue
Solving large tensor linear systems poses significant challenges due to the high volume of data stored, and it only becomes more challenging when some of the data is missing. Recen…
math.NA2026
Attention Mechanisms Through the Lens of Numerical Methods: Approximation Methods and Alternative Formulations
Michel Fabrice Serret, Alice Cortinovis, Yijun Dong +10
The attention mechanism is the computational core of modern Transformer architectures, but its quadratic complexity in the input sequence length is the bottleneck for large-scale i…
math.NA2024
A Note on Randomized Kaczmarz Algorithm for Solving Doubly-Noisy Linear Systems
El Houcine Bergou, Soumia Boucherouite, Aritra Dutta +2
Large-scale linear systems, , frequently arise in practice and demand effective iterative solvers. Often, these systems are noisy due to operational errors or faulty data-col…