Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates

The privacy-sensitive nature of decentralized datasets and the robustness of eXtreme Gradient Boosting (XGBoost) on tabular data raise the needs to train XGBoost in the context of federated learning (FL). Existing works on federated XGBoost in the horizontal setting rely on the sharing of gradients, which induce per-node level communication frequency and serious privacy concerns. To alleviate these problems, we develop an innovative framework for horizontal federated XGBoost which does not depend on the sharing of gradients and simultaneously boosts privacy and communication efficiency by making the learning rates of the aggregated tree ensembles learnable. We conduct extensive evaluations on various classification and regression datasets, showing our approach achieves performance comparable to the state-of-the-art method and effectively improves communication efficiency by lowering both communication rounds and communication overhead by factors ranging from 25x to 700x.Comment: Accepted at the 3rd ACM Workshop on Machine Learning and Systems (EuroMLSys), May 8th 2023, Rome, Ital

Induced CNS expression of CXCL1 augments neurologic disease in a murine model of multiple sclerosis via enhanced neutrophil recruitment.

Increasing evidence points to an important role for neutrophils in participating in the pathogenesis of the human demyelinating disease MS and the animal model EAE. Therefore, a better understanding of the signals controlling migration of neutrophils as well as evaluating the role of these cells in demyelination is important to define cellular components that contribute to disease in MS patients. In this study, we examined the functional role of the chemokine CXCL1 in contributing to neuroinflammation and demyelination in EAE. Using transgenic mice in which expression of CXCL1 is under the control of a tetracycline-inducible promoter active within glial fibrillary acidic protein-positive cells, we have shown that sustained CXCL1 expression within the CNS increased the severity of clinical and histologic disease that was independent of an increase in the frequency of encephalitogenic Th1 and Th17 cells. Rather, disease was associated with enhanced recruitment of CD11b+ Ly6G+ neutrophils into the spinal cord. Targeting neutrophils resulted in a reduction in demyelination arguing for a role for these cells in myelin damage. Collectively, these findings emphasize that CXCL1-mediated attraction of neutrophils into the CNS augments demyelination suggesting that this signaling pathway may offer new targets for therapeutic intervention

Geographies of Outer Space : Progress and New Opportunities

Acknowledgements The editors of this forum would like to acknowledge productive contributions to a thematic session at the RGS-IBG Annual International Conference 2016 on ‘Geographies of Outer Space’. We are also grateful to the editorial board of this journal for their support of this endeavour. Declaration of conflicting interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding The author(s) received no financial support for the research, authorship, and/or publication of this article.Peer reviewedPostprin

Towards understanding interactions between Sustainable Development Goals: the role of environment–human linkages

Only 10 years remain to achieve all Sustainable Development Goals (SDGs) globally, so there is a growing need to increase the effectiveness and efficiency of action by targeting multiple SDGs. The SDGs were conceived as an ‘indivisible whole’, but interactions between SDGs need to be better understood. Several previous assessments have begun to explore interactions including synergies and possible conflicts between the SDGs, and differ widely in their conclusions. Although some highlight the role of the more environmentally-focused SDGs in underpinning sustainable development, none specifically focuses on environment-human linkages. Assessing interactions between SDGs, and the influence of environment on them, can make an important contribution to informing decisions in 2020 and beyond. Here, we review previous assessments of interactions among SDGs, apply an influence matrix to assess pairwise interactions between all SDGs, and show how viewing these from the perspective of environment-human linkages can influence the outcome. Environment, and environment-human linkages, influence most interactions between SDGs. Our action-focused assessment enables decision makers to focus environmental management to have the greatest impacts, and to identify opportunities to build on synergies and reduce trade-offs between particular SDGs. It may enable sectoral decision makers to seek support from environment managers for achieving their goals. We explore cross-cutting issues and the relevance and potential application of our approach in supporting decision making for progress to achieve the SDGs

The role of discharge variability in determining alluvial stratigraphy

We illustrate the potential for using physics-based modeling to link alluvial stratigraphy to large river morphology and dynamics. Model simulations, validated using ground penetrating radar data from the Río Paraná, Argentina, demonstrate a strong relationship between bar-scale set thickness and channel depth, which applies across a wide range of river patterns and bar types. We show that hydrologic regime, indexed by discharge variability and flood duration, exerts a first-order influence on morphodynamics and hence bar set thickness, and that planform morphology alone may be a misleading variable for interpreting deposits. Indeed, our results illustrate that rivers evolving under contrasting hydrologic regimes may have very similar morphology, yet be characterized by marked differences in stratigraphy. This realization represents an important limitation on the application of established theory that links river topography to alluvial deposits, and highlights the need to obtain field evidence of discharge variability when developing paleoenvironmental reconstructions. Model simulations demonstrate the potential for deriving such evidence using metrics of paleocurrent variance

On quantum microcanonical equilibrium

A quantum microcanonical postulate is proposed as a basis for the equilibrium properties of small quantum systems. Expressions for the corresponding density of states are derived, and are used to establish the existence of phase transitions for finite quantum systems. A grand microcanonical ensemble is introduced, which can be used to obtain new rigorous results in quantum statistical mechanics.Accepted versio