A Full Adagrad algorithm with O(Nd) operations

• URL: http://arxiv.org/abs/2405.01908v1
• Date: Fri, 3 May 2024 08:02:08 GMT
• Title: A Full Adagrad algorithm with O(Nd) operations
• Authors: Antoine Godichon-Baggioni, Wei Lu, Bruno Portier,
• Abstract summary: The study offers efficient and practical algorithms for large-scale applications. This innovative strategy significantly reduces the complexity and resource demands typically associated with full-matrix methods.
• Score: 4.389938747401259
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: A novel approach is given to overcome the computational challenges of the full-matrix Adaptive Gradient algorithm (Full AdaGrad) in stochastic optimization. By developing a recursive method that estimates the inverse of the square root of the covariance of the gradient, alongside a streaming variant for parameter updates, the study offers efficient and practical algorithms for large-scale applications. This innovative strategy significantly reduces the complexity and resource demands typically associated with full-matrix methods, enabling more effective optimization processes. Moreover, the convergence rates of the proposed estimators and their asymptotic efficiency are given. Their effectiveness is demonstrated through numerical studies.

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