Mirror Descent View for Neural Network Quantization

Quantizing large Neural Networks (NN) while maintaining the performance is highly desirable for resource-limited devices due to reduced memory and time complexity. It is usually formulated as a constrained optimization problem and optimized via a modified version of gradient descent. In this work, by interpreting the continuous parameters (unconstrained) as the dual of the quantized ones, we introduce a Mirror Descent (MD) framework for NN quantization. Specifically, we provide conditions on the projections (i.e., mapping from continuous to quantized ones) which would enable us to derive valid mirror maps and in turn the respective MD updates. Furthermore, we present a numerically stable implementation of MD that requires storing an additional set of auxiliary variables (unconstrained), and show that it is strikingly analogous to the Straight Through Estimator (STE) based method which is typically viewed as a "trick" to avoid vanishing gradients issue. Our experiments on CIFAR-10/100, TinyImageNet, and ImageNet classification datasets with VGG-16, ResNet-18, and MobileNetV2 architectures show that our MD variants obtain quantized networks with state-of-the-art performance. Code is available at https://github.com/kartikgupta-at-anu/md-bnn.Comment: This paper was accepted at AISTATS 202

Prognostic signifi cance of diff erentiating necrosis from fl uid collection on endoscopic ultrasound in patients with presumed isolated extrapancreatic necrosis

Abstract Background Extrapancreatic necrosis is diagnosed on computed tomography (CT) as extrapancreatic changes that are more than fat stranding; both fl uid collections and necrosis would have a similar appearance. Th e aim of this study was to determine the prognostic signifi cance of diff erentiating peripancreatic necrosis from fl uid collection on endoscopic ultrasound (EUS) in patients with presumed isolated extrapancreatic necrosis

HIV Testing among Patients with Presumptive Tuberculosis: How Do We Implement in a Routine Programmatic Setting? Results of a Large Operational Research from India.

BACKGROUND: In March 2012, World Health Organization recommended that HIV testing should be offered to all patients with presumptive TB (previously called TB suspects). How this is best implemented and monitored in routine health care settings in India was not known. An operational research was conducted in Karnataka State (South India, population 64 million, accounts for 10% of India's HIV burden), to test processes and learn results and challenges of screening presumptive TB patients for HIV within routine health care settings. METHODS: In this cross-sectional study conducted between January-March 2012, all presumptive TB patients attending public sector sputum microscopy centres state-wide were offered HIV testing by the laboratory technician, and referred to the nearest public sector HIV counselling and testing services, usually within the same facility. The HIV status of the patients was recorded in the routine TB laboratory form and TB laboratory register. The laboratory register was compiled to obtain the number of presumptive TB patients whose HIV status was ascertained, and the number found HIV positive. Aggregate data on reasons for non-testing were compiled at district level. RESULTS: Overall, 115,308 patients with presumptive TB were examined for sputum smear microscopy at 645 microscopy centres state-wide. Of these, HIV status was ascertained for 62,847(55%) among whom 7,559(12%) were HIV-positive, and of these, 3,034(40%) were newly diagnosed. Reasons for non-testing were reported for 37,700(72%) of the 52,461 patients without HIV testing; non-availability of testing services at site of sputum collection was cited by health staff in 54% of respondents. Only 4% of patients opted out of HIV testing. CONCLUSION: Offering HIV testing routinely to presumptive TB patients detected large numbers of previously-undetected instances of HIV infection. Several operational challenges were noted which provide useful lessons for improving uptake of HIV testing in this important group

Ageratum enation virus Infection Induces Programmed Cell Death and Alters Metabolite Biosynthesis in Papaver somniferum

A previously unknown disease which causes severe vein thickening and inward leaf curl was observed in a number of opium poppy (Papaver somniferum L.) plants. The sequence analysis of full-length viral genome and associated betasatellite reveals the occurrence of Ageratum enation virus (AEV) and Ageratum leaf curl betasatellite (ALCB), respectively. Co-infiltration of cloned agroinfectious DNAs of AEV and ALCB induces the leaf curl and vein thickening symptoms as were observed naturally. Infectivity assay confirmed this complex as the cause of disease and also satisfied the Koch’s postulates. Comprehensive microscopic analysis of infiltrated plants reveals severe structural anomalies in leaf and stem tissues represented by unorganized cell architecture and vascular bundles. Moreover, the characteristic blebs and membranous vesicles formed due to the virus-induced disintegration of the plasma membrane and intracellular organelles were also present. An accelerated nuclear DNA fragmentation was observed by Comet assay and confirmed by TUNEL and Hoechst dye staining assays suggesting virus-induced programmed cell death. Virus-infection altered the biosynthesis of several important metabolites. The biosynthesis potential of morphine, thebaine, codeine, and papaverine alkaloids reduced significantly in infected plants except for noscapine whose biosynthesis was comparatively enhanced. The expression analysis of corresponding alkaloid pathway genes by real time-PCR corroborated well with the results of HPLC analysis for alkaloid perturbations. The changes in the metabolite and alkaloid contents affect the commercial value of the poppy plants

Deep learning enables genetic analysis of the human thoracic aorta

Genome-wide association analyses identify variants associated with thoracic aortic diameter. A polygenic score for ascending aortic diameter was associated with a diagnosis of thoracic aortic aneurysm in independent samples. Enlargement or aneurysm of the aorta predisposes to dissection, an important cause of sudden death. We trained a deep learning model to evaluate the dimensions of the ascending and descending thoracic aorta in 4.6 million cardiac magnetic resonance images from the UK Biobank. We then conducted genome-wide association studies in 39,688 individuals, identifying 82 loci associated with ascending and 47 with descending thoracic aortic diameter, of which 14 loci overlapped. Transcriptome-wide analyses, rare-variant burden tests and human aortic single nucleus RNA sequencing prioritized genes including SVIL, which was strongly associated with descending aortic diameter. A polygenic score for ascending aortic diameter was associated with thoracic aortic aneurysm in 385,621 UK Biobank participants (hazard ratio = 1.43 per s.d., confidence interval 1.32-1.54, P = 3.3 x 10(-20)). Our results illustrate the potential for rapidly defining quantitative traits with deep learning, an approach that can be broadly applied to biomedical images

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016