FreezeOut: Accelerate Training by Progressively Freezing Layers

The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set portion of the training run, freezing them out one-by-one and excluding them from the backward pass. Through experiments on CIFAR, we empirically demonstrate that FreezeOut yields savings of up to 20% wall-clock time during training with 3% loss in accuracy for DenseNets, a 20% speedup without loss of accuracy for ResNets, and no improvement for VGG networks. Our code is publicly available at https://github.com/ajbrock/FreezeOutComment: Extended Abstrac

SMASH: One-Shot Model Architecture Search through HyperNetworks

Designing architectures for deep neural networks requires expert knowledge and substantial computation time. We propose a technique to accelerate architecture selection by learning an auxiliary HyperNet that generates the weights of a main model conditioned on that model's architecture. By comparing the relative validation performance of networks with HyperNet-generated weights, we can effectively search over a wide range of architectures at the cost of a single training run. To facilitate this search, we develop a flexible mechanism based on memory read-writes that allows us to define a wide range of network connectivity patterns, with ResNet, DenseNet, and FractalNet blocks as special cases. We validate our method (SMASH) on CIFAR-10 and CIFAR-100, STL-10, ModelNet10, and Imagenet32x32, achieving competitive performance with similarly-sized hand-designed networks. Our code is available at https://github.com/ajbrock/SMAS

Generative and Discriminative Voxel Modeling with Convolutional Neural Networks

When working with three-dimensional data, choice of representation is key. We explore voxel-based models, and present evidence for the viability of voxellated representations in applications including shape modeling and object classification. Our key contributions are methods for training voxel-based variational autoencoders, a user interface for exploring the latent space learned by the autoencoder, and a deep convolutional neural network architecture for object classification. We address challenges unique to voxel-based representations, and empirically evaluate our models on the ModelNet benchmark, where we demonstrate a 51.5% relative improvement in the state of the art for object classification.Comment: 9 pages, 5 figures, 2 table

Outpatient Treatment of Tuberculosis: A Study of 604 Cases in Which Artificial Pneumothorax Treatment Was Attempted

Abstract Not Provided

Evolution of entanglement within classical light states

We investigate the evolution of quantum correlations over the lifetime of a multi-photon state. Measurements reveal time-dependent oscillations of the entanglement fidelity for photon pairs created by a single semiconductor quantum dot. The oscillations are attributed to the phase acquired in the intermediate, non-degenerate, exciton-photon state and are consistent with simulations. We conclude that emission of photon pairs by a typical quantum dot with finite polarisation splitting is in fact entangled in a time-evolving state, and not classically correlated as previously regarded

What is a manufacturing job?

Policy initiatives in the UK targeting manufacturing industries have for a number of years been driven by a perceived importance of this sector to the economy. In order to target such policies, it is important to establish the true size of this sector and to accurately quantify its decline. This, as well as many other economic analyses, relies upon classification of businesses into exclusive industrial categories. This paper considers whether standard methods of enterprise classification may mask the numbers and true activity of workers who are employed by so-called ‘manufacturers’.Calculating the extent of this effect, we estimate that the number of manufacturing jobs ‘hidden’ within the service sector is more than offset by service sector jobs hidden within manufacturing. This is important for government policies which target manufacturing jobs. We therefore consider whether protecting ‘manufacturing’ is a meaningful policy target.This analysis uses data from the UK official statistics system. However, given the methodological similarity across countries, particularly in the EU, the findings here are relevant for policy analysis in many countries

Restrictive antibiotic stewardship associated with reduced hospital mortality in gram-negative infection

Introduction: Antimicrobial stewardship has an important role in the control of Clostridium difficile infection (CDI) and antibiotic resistance. An important component of UK stewardship interventions is the restriction of broad-spectrum beta-lactam antibiotics and promotion of agents associated with a lower risk of CDI such as gentamicin. Whilst the introduction of restrictive antibiotic guidance has been associated with improvements in CDI and antimicrobial resistance evidence of the effect on outcome following severe infection is lacking. Methods: In 2008, Glasgow hospitals introduced a restrictive antibiotic guideline. A retrospective before/after study assessed outcome following gram-negative bacteraemia in the 2-year period around implementation. Results: Introduction of restrictive antibiotic guidelines was associated with a reduction in utilisation of ceftriaxone and co-amoxiclav and an increase in amoxicillin and gentamicin. 1593 episodes of bacteraemia were included in the study. The mortality over 1 year following gram-negative bacteraemia was lower in the period following guideline implementation (RR 0.852, P = 0.045). There was no evidence of a difference in secondary outcomes including ITU admission, length of stay, readmission, recurrence of bacteraemia and need for renal replacement therapy. There was a fall in CDI (RR 0.571, P = 0.014) and a reduction in bacterial resistance to ceftriaxone and co-amoxiclav but no evidence of an increase in gentamicin resistance after guideline implementation. Conclusion: Restrictive antibiotic guidelines were associated with a reduction in CDI and bacterial resistance but no evidence of adverse outcomes following gram-negative bacteraemia. There was a small reduction in one year mortality

Where science meets practice: Olympic coaches’ crafting of the tapering process

Although there is research providing physiologically-based guidance for the content of the taper, this study was the first to examine how coaches actually implement the taper. The purpose of this study was to examine the taper planning and implementation processes of successful Olympic coaches leading up to major competitions and how they learned about tapering. Seven track and field coaches participated in semi-structured interviews exploring their tapering processes. To be considered for inclusion, coaches were required to have coached one or more athletes to an Olympic or Paralympic medal. Through a process of axial and open coding interview transcripts were analysed and lower and higher order themes developed describing the coaches’ tapering processes. Our findings indicate that the strategies employed to achieve the desired physiological adaptions of the taper were consistent with research (e.g., reduction in volume whilst maintaining intensity and frequency). However, our findings also suggest that tapering is far from a straight forward “textbook” process. The taper was not restricted to physiological outcomes with coaches considering athletes’ psychological as well as physical state. Coaches also involved the athlete in the process, adapted the taper to the athlete, continually monitored its progress, and adapted it further as required