Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Low rank representation (LRR) is widely used to construct a good affinity matrix to cluster data drawn from the union of multiple linear subspaces. Hover, it is not easy to solve the LRR problem in a closed form, and augmented Lagrange multiplier method (ALM) is usually applied. ALM takes a relative long time dealing with the real-world data. To solve the LRR problem efficiently,  propose an efficient low rank representation (eLRR) algorithm. Given a contaminated data set,  propose a novel way to solve the LRR of the data.  establish a useful theorem which directly gives an approximate solution to our LRR optimization problem. Thus,  can construct a good affinity matrix for subspace clustering. Experimental results with several public databases verify the efficiency and effectiveness of our method.
['Yuanyuan Chen', 'Lei Zhang', 'Zhang Yi']
I am writing a research paper on a idea A Novel Low Rank Representation Algorithm for Subspace Clustering
[{"from": "human", "value": "I am writing a research paper on a idea A Novel Low Rank Representation Algorithm for Subspace Clustering"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Low rank representation (LRR) is widely used to construct a good affinity matrix to cluster data drawn from the union of multiple linear subspaces. Hover, it is not easy to solve the LRR problem in a closed form, and augmented Lagrange multiplier method (ALM) is usually applied. ALM takes a relative long time dealing with the real-world data. To solve the LRR problem efficiently,  propose an efficient low rank representation (eLRR) algorithm. Given a contaminated data set,  propose a novel way to solve the LRR of the data.  establish a useful theorem which directly gives an approximate solution to our LRR optimization problem. Thus,  can construct a good affinity matrix for subspace clustering. Experimental results with several public databases verify the efficiency and effectiveness of our method."}]