Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Restricted Boltzmann Machines (RBMs) are widely used as building blocks for deep learning models. Learning typically proceeds by using stochastic gradient descent, and the gradients are estimated with sampling methods. Hover, the gradient estimation is a computational bottleneck, so better use of the gradients will speed up the descent algorithm. To this end,  rst derive upper bounds on the RBM cost function, then show that descent methods can have natural advantages by operating in the‘1 and Shatten1 norm.  introduce a new method called \Stochastic Spectral Descent" that updates parameters in the normed space. Empirical results show dramatic improvements over stochastic gradient descent, and have only have a fractional increase on the per-iteration cost.
['David E. Carlson', 'Volkan Cevher', 'Lawrence Carin']
I am writing a research paper on a idea Stochastic Spectral Descent for Restricted Boltzmann Machines
[{"from": "human", "value": "I am writing a research paper on a idea Stochastic Spectral Descent for Restricted Boltzmann Machines"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Restricted Boltzmann Machines (RBMs) are widely used as building blocks for deep learning models. Learning typically proceeds by using stochastic gradient descent, and the gradients are estimated with sampling methods. Hover, the gradient estimation is a computational bottleneck, so better use of the gradients will speed up the descent algorithm. To this end,  rst derive upper bounds on the RBM cost function, then show that descent methods can have natural advantages by operating in the\u20181 and Shatten1 norm.  introduce a new method called \\Stochastic Spectral Descent\" that updates parameters in the normed space. Empirical results show dramatic improvements over stochastic gradient descent, and have only have a fractional increase on the per-iteration cost."}]