This paper proposes a reformulation of the dual of the entropy regularized wassserstein distance problem that is amenable to screening techniques. Such techniques allow to reduce the dimension of optimization problems hence reducing the computational costs. Here static screening rule is proposed, meaning that the variables are screened before running the solver which is here an L-BFGS-B quasi-Newton method. Two screening techniques are proposed, either using a fixed threshold or a fixed budget. The latter appearing easier to use. A theorem quantifying the error on the orignal problem induced by approximation and screening is provided.

Researchers have found a new artificial intelligence-based drug screening technique. Read below to know the significance and process of the experiment. Developing life-saving drugs can cost billions of dollars and take years, but researchers have found a new artificial intelligence-based drug screening technique, and by using that they assume to shorten the process. Using a process that models drug and target protein interactions using natural language processing techniques, the researchers gained up to 97% accuracy in identifying promising drug candidates. The results were published currently in the journal Briefings in Bioinformatics.