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Found 4 papers, 2 papers with code
NG+ : A Multi-Step Matrix-Product Natural Gradient Method for Deep Learning
In this paper, a novel second-order method called NG+ is proposed.
DST: Data Selection and joint Training for Learning with Noisy Labels
In this paper, we propose a Data Selection and joint Training (DST) method to automatically select training samples with accurate annotations.
A variational quantum algorithm for Hamiltonian diagonalization
To obtain the full spectrum of the Hamiltonian, we use a quantum imaginary time evolution algorithm with high temperature, which prepares a thermal state with a small correlation length.
Quantum Physics
Sketchy Empirical Natural Gradient Methods for Deep Learning
Experiments on the distributed large-batch training show that the scaling efficiency is quite reasonable.
