Local Algorithms for Block Models with Side Information

There has been a recent interest in understanding the power of local algorithms for optimization and inference problems on sparse graphs. Gamarnik and Sudan (2014) showed that local algorithms are weaker than global algorithms for finding large independent sets in sparse random regular graphs. Montanari (2015) showed that local algorithms are suboptimal for finding a community with high connectivity in the sparse Erd\H{o}s-R\'enyi random graphs. For the symmetric planted partition problem (also named community detection for the block models) on sparse graphs, a simple observation is that local algorithms cannot have non-trivial performance. In this work we consider the effect of side information on local algorithms for community detection under the binary symmetric stochastic block model. In the block model with side information each of the $n$ vertices is labeled $+$ or $-$ independently and uniformly at random; each pair of vertices is connected independently with probability $a/n$ if both of them have the same label or $b/n$ otherwise. The goal is to estimate the underlying vertex labeling given 1) the graph structure and 2) side information in the form of a vertex labeling positively correlated with the true one. Assuming that the ratio between in and out degree $a/b$ is $\Theta(1)$ and the average degree $(a+b) / 2 = n^{o(1)}$, we characterize three different regimes under which a local algorithm, namely, belief propagation run on the local neighborhoods, maximizes the expected fraction of vertices labeled correctly. Thus, in contrast to the case of symmetric block models without side information, we show that local algorithms can achieve optimal performance for the block model with side information.Comment: Due to the limitation "The abstract field cannot be longer than 1,920 characters", the abstract here is shorter than that in the PDF fil

Privacy-preserving biometric-based remote user authentication with leakage resilience

National Research Foundation (NRF) Singapor

Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis Standard Reporting and Evaluation Guidelines Results of a National Institutes of Health Working Group

Importance: Toxic epidermal necrolysis (TEN) and Stevens-Johnson Syndrome (SJS) are rare, acute, life-threatening dermatologic disorders involving the skin and mucous membranes. Research into these conditions is hampered by a lack of standardization of case reporting and data collection. Objective: To establish a standardized case report form to facilitate comparisons and maintain data quality based on an international panel of SJS/TEN experts who performed a Delphi consensus-building exercise. Evidence Review: The elements presented for committee scrutiny were adapted from previous case report forms and from PubMed literature searches of highly cited manuscripts pertaining to SJS/TEN. The expert opinions and experience of the members of the consensus group were included in the discussion. Findings: Overall, 21 out of 29 experts who were invited to participate in the online Delphi exercise agreed to participate. Surveys at each stage were administered via an online survery software tool. For the first 2 Delphi rounds, results were analyzed using the Interpercentile Range Adjusted for Symmetry method and statements that passed consensus formulated a new case report form. For the third Delphi round, the case report form was presented to the committee, who agreed that it was "appropriate and useful" for documenting cases of SJS/TEN, making it more reliable and valuable for future research endeavors. Conclusions and Relevance: With the consensus of international experts, a case report form for SJS/TEN has been created to help standardize the collection of patient information in future studies and the documentation of individual cases

Exercise therapy in Type 2 diabetes

Structured exercise is considered an important cornerstone to achieve good glycemic control and improve cardiovascular risk profile in Type 2 diabetes. Current clinical guidelines acknowledge the therapeutic strength of exercise intervention. This paper reviews the wide pathophysiological problems associated with Type 2 diabetes and discusses the benefits of exercise therapy on phenotype characteristics, glycemic control and cardiovascular risk profile in Type 2 diabetes patients. Based on the currently available literature, it is concluded that Type 2 diabetes patients should be stimulated to participate in specifically designed exercise intervention programs. More attention should be paid to cardiovascular and musculoskeletal deconditioning as well as motivational factors to improve long-term treatment adherence and clinical efficacy. More clinical research is warranted to establish the efficacy of exercise intervention in a more differentiated approach for Type 2 diabetes subpopulations within different stages of the disease and various levels of co-morbidity