Decoupled Training for Long-Tailed Classification With Stochastic Representations

Decoupling representation learning and classifier learning has been shown to be effective in classification with long-tailed data. There are two main ingredients in constructing a decoupled learning scheme; 1) how to train the feature extractor for representation learning so that it provides generalizable representations and 2) how to re-train the classifier that constructs proper decision boundaries by handling class imbalances in long-tailed data. In this work, we first apply Stochastic Weight Averaging (SWA), an optimization technique for improving the generalization of deep neural networks, to obtain better generalizing feature extractors for long-tailed classification. We then propose a novel classifier re-training algorithm based on stochastic representation obtained from the SWA-Gaussian, a Gaussian perturbed SWA, and a self-distillation strategy that can harness the diverse stochastic representations based on uncertainty estimates to build more robust classifiers. Extensive experiments on CIFAR10/100-LT, ImageNet-LT, and iNaturalist-2018 benchmarks show that our proposed method improves upon previous methods both in terms of prediction accuracy and uncertainty estimation.Comment: ICLR 202

Bioinformatics services for analyzing massive genomic datasets

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating down-stream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/. ?? 2020, Korea Genome Organization

Novel Therapeutic Strategies in the Management of Non-Variceal Upper Gastrointestinal Bleeding

Non-variceal upper gastrointestinal bleeding, the most common etiology of which is peptic ulcer disease, remains a persistent challenge despite a reduction in both its incidence and mortality. Both pharmacologic and endoscopic techniques have been developed to achieve hemostasis, with varying degrees of success. Among the pharmacologic therapies, proton pump inhibitors remain the mainstay of treatment, as they reduce the risk of rebleeding and requirement for recurrent endoscopic evaluation. Tranexamic acid, a derivative of the amino acid lysine, is an antifibrinolytic agent whose role requires further investigation before application. Endoscopically delivered pharmacotherapy, including Hemospray (Cook Medical), EndoClot (EndoClot Plus Inc.), and Ankaferd Blood Stopper (Ankaferd Health Products), in addition to standard epinephrine, show promise in this regard, although their mechanisms of action require further investigation. Non-pharmacologic endoscopic techniques use one of the following two methods to achieve hemostasis: ablation or mechanical tamponade, which may involve using endoscopic clips, cautery, argon plasma coagulation, over-the-scope clipping devices, radiofrequency ablation, and cryotherapy. This review aimed to highlight these novel and fundamental hemostatic strategies and the research supporting their efficacy

Future Perspectives on Endoscopic Ultrasonography-Guided Therapy for Pancreatic Neoplasm

Endoscopic ultrasonography (EUS)-guided therapy with ethanol injection or catheter-based radiofrequency ablation for pancreatic neoplasm has been conducted as a potential alternate treatment modality for patients who are not eligible for surgery. On the basis of the limited number of studies available, EUS-guided ablation therapy with the aforementioned methods for small pancreatic neoplasms has demonstrated promising technical feasibility and safety profiles. To be considered as a legitimate alternative option to surgery, however, EUS-guided ablation therapy must provide a long-term efficacy profile along with the consensus among experts regarding its treatment parameter. This review focuses on the clinical issues and future perspectives of EUS-guided therapy for pancreatic neoplasm