Privacy protection of users' entire contribution of samples is important in distributed

This paper introduces a novel prior called Diversified Block Sparse Prior to characterize the widespread block sparsity phenomenon in real-world data.

Although this problem is significant for safer and smarter driving systems, the exploration of this problem remains limited.

More recently, Newton-type methods using sparsified Hessian matrices have demonstrated promising results on OT computation, but there still remain a lot of unresolved open questions.