Annealed Langevin dynamics reach the tensor PCA algorithmic threshold
Part II says spherical Langevin dynamics with annealing and averaging strongly recover from a random start.
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Part II says spherical Langevin dynamics with annealing and averaging strongly recover from a random start.
Markov models of repair sequences reach 96.0% attribution accuracy and separate Llama-3 8B from 70B under spoofing.
Researchers give near-optimal private bounds for learning Markov chain transition matrices.
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