Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization.
Tian YeSimon S. DuPublished in: NeurIPS (2021)
Keyphrases
- global convergence
- low rank matrix factorization
- matrix factorization
- global optimum
- convergence rate
- convergence speed
- optimization methods
- convergence analysis
- objective function
- missing data
- cost function
- convex minimization
- conjugate gradient
- recommender systems
- low rank
- loss function
- globally convergent
- gauss newton
- particle swarm
- stochastic gradient descent
- hybrid algorithm
- collaborative filtering
- high dimensional data
- particle swarm optimization
- simulated annealing
- step size
- data sets
- singular value decomposition
- optimization method
- differential evolution
- active learning
- genetic algorithm