The authors addressed the limitations and potential negative societal impact of their work. However, there are some concerns as follows: 1.The main concern is the innovation of this paper. Firstly, laplacian score is proposed by Ref.13 for feature selection as an unsupervised measure. Secondly, i think that the main contribution of this paper is stochastic gates, but in Ref.36, the technology of stochastic gates is already used in supervised feature selection. Finally, authors focus on the traditional unsupervised feature selection problem. Thus i think that the core contribution of this paper is that authors extend the supervised problem in Ref.36 to the unsupervised problem without theoretical guarantees. Even authors introduce the importance of unsupervised feature selection from a diffusion perspective, but i don't think this is the core contribution of this article. For this question, if the authors can persuade me , I will change my score. 2.Authors introduce the importance of unsupervised feature selection from a diffusion perspective and i think this is a very novel thing for feature selection, but i can't understand what is the difference between similarity and exit times in nature. I hope the author can give me a more detailed explanation to understand the difference. 3.Authors sample a stochastic gate (STG) vector in algorithm 1 and thus i think that the proposed method should have randomness. But in the main experiment of this paper, i don't see this randomness analyzed by authors. 4.It would be better if the authors add some future work.
2.Authors introduce the importance of unsupervised feature selection from a diffusion perspective and i think this is a very novel thing for feature selection, but i can't understand what is the difference between similarity and exit times in nature. I hope the author can give me a more detailed explanation to understand the difference.