2 papers
cs.LG2025
Tensor Network Based Feature Learning Model
Albert Saiapin, Kim Batselier
Many approximations were suggested to circumvent the cubic complexity of kernel-based algorithms, allowing their application to large-scale datasets. One strategy is to consider th…
stat.ML2025
Laplace Approximation For Tensor Train Kernel Machines In System Identification
Albert Saiapin, Kim Batselier
To address the scalability limitations of Gaussian process (GP) regression, several approximation techniques have been proposed. One such method is based on tensor networks, which…