22 research outputs found
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
5G 3GPP-like Channel Models for Outdoor Urban Microcellular and Macrocellular Environments
For the development of new 5G systems to operate in bands up to 100 GHz,
there is a need for accurate radio propagation models at these bands that
currently are not addressed by existing channel models developed for bands
below 6 GHz. This document presents a preliminary overview of 5G channel models
for bands up to 100 GHz. These have been derived based on extensive measurement
and ray tracing results across a multitude of frequencies from 6 GHz to 100
GHz, and this document describes an initial 3D channel model which includes: 1)
typical deployment scenarios for urban microcells (UMi) and urban macrocells
(UMa), and 2) a baseline model for incorporating path loss, shadow fading, line
of sight probability, penetration and blockage models for the typical
scenarios. Various processing methodologies such as clustering and antenna
decoupling algorithms are also presented.Comment: To be published in 2016 IEEE 83rd Vehicular Technology Conference
Spring (VTC 2016-Spring), Nanjing, China, May 201
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
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