Qiang Yang

TL;DR: This paper proposes a quasi-Newton method based vertical federated learning framework for logistic regression under the additively homomorphic encryption scheme and can considerably reduce the number of communication rounds with a little additional communication cost per round.

TL;DR: Li et al. as mentioned in this paper developed a low-cost and easy-fabrication technique to substantially reduce the undesired voids in hole transport layer by modifying it with commercially available PbI2.

TL;DR: An incremental supervised subspace learning algorithm to infer an adaptive subspace by optimizing the Maximum Margin Criterion is proposed, and experimental results show that IMMC converges to the similar subspace as that of batch approach.

TL;DR: Extensive experiments substantiate that the distributed optimizer could achieve competitive effectiveness in terms of solution quality as compared to the state-of-the-art large-scale methods; accelerate the execution of the algorithm in comparison with the sequential one and obtain almost linear speedup as the number of cores increases; and preserve a good scalability to solve higher dimensional problems.

TL;DR: In this article , the influence mechanism of renewable energy and economic growth from the two dimensions of natural resources and institutional environment is explored by using the panel data (from 2002 to 2018) of 104 selected countries and regions.