Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  give algorithms with provable guarantees that learn a class of deep nets in the generative model view popularized by Hinton and others. Our generative model is an n node multilayer network that has degree at most nγ for some γ < 1 and each edge has a random edge ight in [-1, 1]. Our algorithm learns almost all networks in this class with polynomial running time. The sample complexity is quadratic or cubic depending upon the details of the model.#R##N##R##N#The algorithm uses layerwise learning. It is based upon a novel idea of observing correlations among features and using these to infer the underlying edge structure via a global graph recovery procedure. The analysis of the algorithm reveals interesting structure of neural nets with random edge ights.
['Sanjeev Arora', 'Aditya Bhaskara', 'Rong Ge', 'Tengyu Ma']
I am writing a research paper on a idea Provable Bounds for Learning Some Deep Representations
[{"from": "human", "value": "I am writing a research paper on a idea Provable Bounds for Learning Some Deep Representations"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  give algorithms with provable guarantees that learn a class of deep nets in the generative model view popularized by Hinton and others. Our generative model is an n node multilayer network that has degree at most n\u03b3 for some \u03b3 < 1 and each edge has a random edge ight in [-1, 1]. Our algorithm learns almost all networks in this class with polynomial running time. The sample complexity is quadratic or cubic depending upon the details of the model.#R##N##R##N#The algorithm uses layerwise learning. It is based upon a novel idea of observing correlations among features and using these to infer the underlying edge structure via a global graph recovery procedure. The analysis of the algorithm reveals interesting structure of neural nets with random edge ights."}]