AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks

Existing fine-tuning methods use a single learning rate over all layers. In this paper, first, we discuss that trends of layer-wise weight variations by fine-tuning using a single learning rate do not match the well-known notion that lower-level layers extract general features and higher-level layers extract specific features. Based on our discussion, we propose an algorithm that improves fine-tuning performance and reduces network complexity through layer-wise pruning and auto-tuning of layer-wise learning rates. The proposed algorithm has verified the effectiveness by achieving state-of-the-art performance on the image retrieval benchmark datasets (CUB-200, Cars-196, Stanford online product, and Inshop). Code is available at https://github.com/youngminPIL/AutoLR.Comment: Accepted to AAAI 202

The impact of a firm’s make, pseudoâ make, or buy strategy on product performance

The bulk of the product architecture and makeâ buy choice literature deals with product architecture changes from integral to modular form. This development is often associated with a firm’s tendency to change from a make to a buy strategy. However, a few studies investigate the change of product architecture in the reverse direction â from modular to integral form â and the subsequent change in the firm sourcing decision from a buy to a make strategy. These studies hold to the presumption that a firm following a make strategy will outperform firms following a buy strategy in dealing with integral product architectures. Based on the knowledgeâ based view, we argue for the viability of a sourcing strategy between the pure make and buy strategies â a pseudoâ make strategy. We also argue that as product architecture changes from a modular to integral form, firms adopting this pseudoâ make strategy are likely to show better product performance than firms following a pure make or buy strategy due to the relative knowledge advantages of the pseudoâ make strategy in dealing with the integral product architecture. We examine the impact of the make/pseudoâ make/buy strategies on product performance in the U.S. bicycle derailleur and freewheel market from 1980 to 1992 and provide theoretical and managerial implications of our results. Our findings highlight an important distinction between the pseudoâ make and makeâ buy strategies that has not previously been fully appreciated in the extant literature, and as a result increases our understanding of why some firms do not switch strategies from a buy to a make strategy when product architecture changes from modular to integral form as previously expected.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146818/1/joom289.pd

Backbone Can Not be Trained at Once: Rolling Back to Pre-trained Network for Person Re-Identification

In person re-identification (ReID) task, because of its shortage of trainable dataset, it is common to utilize fine-tuning method using a classification network pre-trained on a large dataset. However, it is relatively difficult to sufficiently fine-tune the low-level layers of the network due to the gradient vanishing problem. In this work, we propose a novel fine-tuning strategy that allows low-level layers to be sufficiently trained by rolling back the weights of high-level layers to their initial pre-trained weights. Our strategy alleviates the problem of gradient vanishing in low-level layers and robustly trains the low-level layers to fit the ReID dataset, thereby increasing the performance of ReID tasks. The improved performance of the proposed strategy is validated via several experiments. Furthermore, without any add-ons such as pose estimation or segmentation, our strategy exhibits state-of-the-art performance using only vanilla deep convolutional neural network architecture.Comment: Accepted to AAAI 201

Pure nongestational choriocarcinoma of the ovary: a case report

Abstract Pure ovarian choriocarcinoma can be gestational or nongestational in origin. Nongestational choriocarcinoma of the ovary is extremely rare, and its diagnosis is very difficult during the reproductive years. We present a case of a 33-year-old woman diagnosed with pure nongestational ovarian choriocarcinoma. Following surgery, multiple courses of a chemotherapy regimen of etoposide, methotrexate, and actinomycin-D (EMA) were effective.</p

Functional Benefit after Modification of Radial Forearm Free Flap for Soft Palate Reconstruction

ObjectivesTo compare the velopharyngeal function, swallowing and speech of the conventional and modified radial forearm free flap (RFFF) for soft palate reconstruction.MethodsRetrospective clinical study. Twenty-eight patients who underwent oropharyngeal reconstruction with RFFF were divided into two groups: 10 patients had conventional folded RFFF and 18 patients underwent modified method.ResultsThe average speech intelligibility score in modified RFFF group was 8.0±2.4, and 6.2±2.2 in conventional RFFF group (P<0.05). The nasalance was 27.4±7.8% in modified group and 38.6±2.7% in conventional group during no nasal passage reading and 43.6±7.3% in modified group, 55.2±7.6% in conventional group during high nasal passage reading (P<0.05). The subjective swallowing functional score was 2.8 in modified group and 2.1 in conventional group.ConclusionThe speech assessment and nasalance demonstrate a more favorable outcome in modified group than conventional group

Bedside prediction of right subclavian venous catheter insertion length

AbstractBackground and objectiveThe present study aimed to evaluate whether right subclavian vein (SCV) catheter insertion depth can be predicted reliably by the distances from the SCV insertion site to the ipsilateral clavicular notch directly (denoted as I-IC), via the top of the SCV arch, or via the clavicle (denoted as I-T-IC and I-C-IC, respectively).MethodIn total, 70 SCV catheterizations were studied. The I-IC, I-T-IC, and I-C-IC distances in each case were measured after ultrasound-guided SCV catheter insertion. The actual length of the catheter between the insertion site and the ipsilateral clavicular notch, denoted as L, was calculated by using chest X-ray.ResultsL differed from the I-T-IC, I-C-IC, and I-IC distances by 0.14±0.53, 2.19±1.17, and −0.45±0.68cm, respectively. The mean I-T-IC distance was the most similar to the mean L (intraclass correlation coefficient=0.89). The mean I-IC was significantly shorter than L, while the mean I-C-IC was significantly longer. Linear regression analysis provided the following formula: Predicted SCV catheter insertion length (cm)=−0.037+0.036×Height (cm)+0.903×I-T-IC (cm) (adjusted r2=0.64).ConclusionThe I-T-IC distance may be a reliable bedside predictor of the optimal insertion length for a right SCV cannulation

Permanent Percutaneous Epidural Stimulation of the Spinal Cord for Post-herpetic Neuralgia

An 82 year old man who had suffered from intractable post-herpetic neuralgic pain received percutaneous permanent spinal cord stimulator implantation. Pain relief was so remarkable that he could sleep without the interference of frequent acute sharp attacks of pain, and at the same time, he could do his work again, which had been impossible before he received this treatment. We recommend this procedure for several kinds of intractable pain, including peripheral nerve and root lesions. spinal cord lesions and peripheral vascular disease, after careful selection of the patient

EFFECTIVE DOSE MEASUREMENT FOR CONE BEAM COMPUTED TOMOGRAPHY USING GLASS DOSIMETER

During image-guided radiation therapy, the patient is exposed to unwanted radiation from imaging devices built into the medical LINAC. In the present study, the effective dose delivered to a patient from a cone beam computed tomography (CBCT) machine was measured. Absorbed doses in specific organs listed in ICRP Publication 103 were measured with glass dosimeters calibrated with kilovolt (kV) X-rays using a whole body physical phantom for typical radiotherapy sites, including the head and neck, chest, and pelvis. The effective dose per scan for the head and neck, chest, and pelvis were 3.37±0.29, 7.36±0.33, and 4.09±0.29 mSv, respectively. The results highlight the importance of the compensation of treatment dose by managing imaging dose