Stabilizing Estimates of Shapley Values with Control Variates

Shapley values are among the most popular tools for explaining predictions of blackbox machine learning models. However, their high computational cost motivates the use of sampling approximations, inducing a considerable degree of uncertainty. To stabilize these model explanations, we propose ControlSHAP, an approach based on the Monte Carlo technique of control variates. Our methodology is applicable to any machine learning model and requires virtually no extra computation or modeling effort. On several high-dimensional datasets, we find it can produce dramatic reductions in the Monte Carlo variability of Shapley estimates

Forest Fire Clustering: Cluster-oriented Label Propagation Clustering and Monte Carlo Verification Inspired by Forest Fire Dynamics

Clustering methods group data points together and assign them group-level labels. However, it has been difficult to evaluate the confidence of the clustering results. Here, we introduce a novel method that could not only find robust clusters but also provide a confidence score for the labels of each data point. Specifically, we reformulated label-propagation clustering to model after forest fire dynamics. The method has only one parameter - a fire temperature term describing how easily one label propagates from one node to the next. Through iteratively starting label propagations through a graph, we can discover the number of clusters in a dataset with minimum prior assumptions. Further, we can validate our predictions and uncover the posterior probability distribution of the labels using Monte Carlo simulations. Lastly, our iterative method is inductive and does not need to be retrained with the arrival of new data. Here, we describe the method and provide a summary of how the method performs against common clustering benchmarks.Comment: 9 pages, 8 figure

TP53, STK11 , and EGFR Mutations Predict Tumor Immune Profile and the Response to Anti–PD-1 in Lung Adenocarcinoma

International audienc

Toward a network sociality

This article explores some current transformations of the social. It argues for a shift from a model of sociality based on community towards a network sociality. This shift is particularly visible in urban spaces and in the cultural industries. However, it seems to become paradigmatic more widely of the information society. The article is to be read as a cultural hypothesis. In the first part I introduce some examples that document the rise of a network sociality. Most of these examples are drawn from a two-year ethnographic study of London's new media. The second part consists of a critique of some theoretical accounts of contemporary transformations of sociality. The third part is an attempt to outline the concept of network sociality. It is a form of sociality that is ephemeral but intense, it is informational and technological, it combines work and play, it is disembedded and generic, and it emerges in the context of individualization

Severe Monkeypox in Hospitalized Patients - United States, August 10-October 10, 2022.

As of October 21, 2022, a total of 27,884 monkeypox cases (confirmed and probable) have been reported in the United States.§ Gay, bisexual, and other men who have sex with men have constituted a majority of cases, and persons with HIV infection and those from racial and ethnic minority groups have been disproportionately affected (1,2). During previous monkeypox outbreaks, severe manifestations of disease and poor outcomes have been reported among persons with HIV infection, particularly those with AIDS (3-5). This report summarizes findings from CDC clinical consultations provided for 57 patients aged ≥18 years who were hospitalized with severe manifestations of monkeypox¶ during August 10-October 10, 2022, and highlights three clinically representative cases. Overall, 47 (82%) patients had HIV infection, four (9%) of whom were receiving antiretroviral therapy (ART) before monkeypox diagnosis. Most patients were male (95%) and 68% were non-Hispanic Black (Black). Overall, 17 (30%) patients received intensive care unit (ICU)-level care, and 12 (21%) have died. As of this report, monkeypox was a cause of death or contributing factor in five of these deaths; six deaths remain under investigation to determine whether monkeypox was a causal or contributing factor; and in one death, monkeypox was not a cause or contributing factor.** Health care providers and public health professionals should be aware that severe morbidity and mortality associated with monkeypox have been observed during the current outbreak in the United States (6,7), particularly among highly immunocompromised persons. Providers should test all sexually active patients with suspected monkeypox for HIV at the time of monkeypox testing unless a patient is already known to have HIV infection. Providers should consider early commencement and extended duration of monkeypox-directed therapy†† in highly immunocompromised patients with suspected or laboratory-diagnosed monkeypox.§§ Engaging all persons with HIV in sustained care remains a critical public health priority