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stat.ME2026
Heteroskedastic Canonical Polyadic Tensor Decomposition
Kyle Ritscher, Carlos Llosa-Vite
When minimizing the squared-error loss, the popular CP decomposition can be interpreted as parameter inference in a Gaussian model with a low-rank mean tensor and constant variance…
cs.LG2026
FlexAct: Why Learn when you can Pick?
Ramnath Kumar, Kyle Ritscher, Junmin Judy +2
Learning activation functions has emerged as a promising direction in deep learning, allowing networks to adapt activation mechanisms to task-specific demands. In this work, we int…