Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks

Architecture optimization, which is a technique for finding an efficient neural network that meets certain requirements, generally reduces to a set of multiple-choice selection problems among alternative sub-structures or parameters. The discrete nature of the selection problem, however, makes this optimization difficult. To tackle this problem we introduce a novel concept of a trainable gate function. The trainable gate function, which confers a differentiable property to discretevalued variables, allows us to directly optimize loss functions that include non-differentiable discrete values such as 0-1 selection. The proposed trainable gate can be applied to pruning. Pruning can be carried out simply by appending the proposed trainable gate functions to each intermediate output tensor followed by fine-tuning the overall model, using any gradient-based training methods. So the proposed method can jointly optimize the selection of the pruned channels while fine-tuning the weights of the pruned model at the same time. Our experimental results demonstrate that the proposed method efficiently optimizes arbitrary neural networks in various tasks such as image classification, style transfer, optical flow estimation, and neural machine translation.Comment: Accepted to AAAI 2020 (Poster

Comparing Sample-wise Learnability Across Deep Neural Network Models

Estimating the relative importance of each sample in a training set has important practical and theoretical value, such as in importance sampling or curriculum learning. This kind of focus on individual samples invokes the concept of sample-wise learnability: How easy is it to correctly learn each sample (cf. PAC learnability)? In this paper, we approach the sample-wise learnability problem within a deep learning context. We propose a measure of the learnability of a sample with a given deep neural network (DNN) model. The basic idea is to train the given model on the training set, and for each sample, aggregate the hits and misses over the entire training epochs. Our experiments show that the sample-wise learnability measure collected this way is highly linearly correlated across different DNN models (ResNet-20, VGG-16, and MobileNet), suggesting that such a measure can provide deep general insights on the data's properties. We expect our method to help develop better curricula for training, and help us better understand the data itself.Comment: Accepted to AAAI 2019 Student Abstrac

The Initial Extent of Malapposition in ST-Elevation Myocardial Infarction Treated with Drug-Eluting Stent: The Usefulness of Optical Coherence Tomography

PURPOSE: The aim of this study is to identify the extent of initial malapposition using optical coherence tomography (OCT) in ST-elevation myocardial infarctions (STEMI) treated with different types of drug-eluting stents (DES). MATERIALS AND METHODS: Twenty four STEMI patients that underwent primary percutaneous coronary intervention (PCI) were enrolled. The OCT and intravascular ultrasound (IVUS) were performed within 72 hours after the primary PCI. Distances between the endo-luminal surface of the strut reflection and the vessel wall and the extent of malapposition were measured and analyzed. RESULTS: Sirolimus-eluting stents (SES), paclitaxel-eluting stents (PES) and zotarolimus-eluting stents (ZES) were deployed in 7 patients (29%), 7 patients (29%) and 10 patients (42%). In total, 4951 struts in 620 mm single-stent segments were analyzed (1463 struts in SES, 1522 in PES, and 1966 in ZES). In strut analysis by OCT, the incidence of malapposition was 17 % (860/4951) and in stent analysis by IVUS, malapposition rate was 21% (5/24). The malapposition rate of strut level using OCT in 5 patients who had malapposition in IVUS was significantly higher than the 19 of those who had not (32 +/- 5% vs. 12 +/- 6%, p = 0.001). In addition, the frequency of malapposition was also significantly different (28% in SES, 11% in PES, 10% in ZES, p = 0.001). The use of SES was an independent predictor of malapposed struts. CONCLUSION: The incidence of malapposition using OCT was quite prevalent in STEMI after primary PCI with DES implantation and SES has especially higher rates of malapposition compared to other DESs.ope

A Secure Storage System for Sensitive Data Protection Based on Mobile Virtualization

Recently, the development of smart phones has been reported the number of security vulnerabilities. Although these smart phones have a concept of Sandbox for the security, sensitive personal information has been still exposed by internal data exchange or root privilege acquisition. In this paper, we propose a system framework for secure storage of sensitive data in smartphone. The system is divided into general domain (GD) and secure domain (SD) in mobile device utilizing domain separation technique of virtualization, and SD provides a secure execution environment to protect sensitive data and secure services. In addition, our system introduces the secure functions such as authentication/access control, and encryption/key management and secures filesystem to be run in SD and addresses a detailed secure filesystem as a key function for secure storage. Lastly, the experiments are conducted to measure the performance overhead imposed by security features in SD and by overall system with interdomain communication from GD to SD. These experiment results show suitability of our system and suggest applicability of various secure functions which can be applied in our secure storage system

Complete Genome Sequence Analysis of Two Divergent Groups of Sweet potato chlorotic fleck virus Isolates Collected from Korea

The Sweet potato chlorotic fleck virus (SPCFV), of the genus Carlavirus (family Betaflexiviridae), was first detected as one of several viruses infecting sweet potatoes (Ipomea batatas L.) in Korea. Out of 154 sweet potato samples collected in 2012 that were showing virus-like symptoms, 47 (31%) were infected with SPCFV, along with other viruses. The complete genome sequences of four SPCFV isolates were determined and analyzed using previously reported genome sequences. The complete genomes were found to contain 9,104-9,108 nucleotides, excluding the poly-A tail, containing six putative open reading frames (ORFs). Further, the SPCFV Korean isolates were divided into two groups (Group I and Group II) by phylogenetic analysis based on the complete nucleotide sequences; Group I and Group II had low nucleotide sequence identities of about 73%. For the first time, we determined the complete genome sequence for the Group II SPCFV isolates. The amino acid sequence identity in coat proteins (CP) between the two groups was over 90%, whereas the amino acid sequence identity in other proteins was less than 80%. In addition, SPCFV Korean isolates had a low amino acid sequence identity (61% CPs and 47% in the nucleotide- binding protein [NaBp] region) to that of Melon yellowing-associated virus (MYaV), a typical Carlavirus