No More Pesky Learning Rates

The performance of stochastic gradient descent (SGD) depends critically on how learning rates are tuned and decreased over time. We propose a method to automatically adjust multiple learning rates so as to minimize the expected error at any one time. The method relies on local gradient variations across samples. In our approach, learning rates can increase as well as decrease, making it suitable for non-stationary problems. Using a number of convex and non-convex learning tasks, we show that the resulting algorithm matches the performance of SGD or other adaptive approaches with their best settings obtained through systematic search, and effectively removes the need for learning rate tuning

Phase Harmonic Correlations and Convolutional Neural Networks

A major issue in harmonic analysis is to capture the phase dependence of frequency representations, which carries important signal properties. It seems that convolutional neural networks have found a way. Over time-series and images, convolutional networks often learn a first layer of filters which are well localized in the frequency domain, with different phases. We show that a rectifier then acts as a filter on the phase of the resulting coefficients. It computes signal descriptors which are local in space, frequency and phase. The non-linear phase filter becomes a multiplicative operator over phase harmonics computed with a Fourier transform along the phase. We prove that it defines a bi-Lipschitz and invertible representation. The correlations of phase harmonics coefficients characterise coherent structures from their phase dependence across frequencies. For wavelet filters, we show numerically that signals having sparse wavelet coefficients can be recovered from few phase harmonic correlations, which provide a compressive representationComment: 26 pages, 8 figure

Exploring Teaching Language with Culture

This portfolio contains the author\u27s insights into teaching a second language, which she gained while in the Master of Second Language Teaching (MSLT) program at Utah State University (USU). It is organized in two major sections: teaching perspectives and research perspectives. The content reflects the author’s main focus and value on language teaching as a graduate instructor and student. In the teaching perspectives section, the author shares the professional environment that she wants to work in, her teaching philosophy statement, and the professional development in language education through observing her colleagues’ teaching. In the research perspectives, two research papers and an annotated bibliography are included, which are tightly related to the author’s philosophy in teaching a second language

ORGB: Offset Correction in RGB Color Space for Illumination-Robust Image Processing

Single materials have colors which form straight lines in RGB space. However, in severe shadow cases, those lines do not intersect the origin, which is inconsistent with the description of most literature. This paper is concerned with the detection and correction of the offset between the intersection and origin. First, we analyze the reason for forming that offset via an optical imaging model. Second, we present a simple and effective way to detect and remove the offset. The resulting images, named ORGB, have almost the same appearance as the original RGB images while are more illumination-robust for color space conversion. Besides, image processing using ORGB instead of RGB is free from the interference of shadows. Finally, the proposed offset correction method is applied to road detection task, improving the performance both in quantitative and qualitative evaluations.Comment: Project website: https://baidut.github.io/ORGB

Sustainable Tourism: A Case Study on Salt Spring Island

Over the past few decades, tourism hasbecome one of the mainstay industries for manycommunities. Salt Spring Island, an island thesouth of Vancouver Island, is no exception to thebenefits of tourism. Sustainable tourism is anecessary and useful pattern to Salt Spring Island.Under this perspective, there are some challengesthat exist on Salt Spring Island regarding thetourism industry. Seasonality and inconvenienttransportation are the major challenges, forseasonality will cause unstable revenue and underorunemployment issues, which will affectresidents’ quality of life; the inconvenienttransportation will not only influence the locals’daily life, but also reduce tourists’ interest intravelling. The paper contains three sections: thechallenges that exist on Salt Spring Island tourismindustries, the measures are using on Salt SpringIsland, and innovative approaches from outside theregion to help Salt Spring Island to improve itstourism development and sustainability. Despitethe local people’s efforts to come up with solutionsto the issues, these solutions cannot solve theproblems because these solutions do not addressthe root of the problems. Therefore, the authorssuggest three innovations to solve these twoproblems, including building greenways andautomatic rental bicycle system, creating a themefor events, and developing wellness tourism

Solvent Analysis of Phenolic Resin Glass Fiber Reinforced Prepreg During Out-time

Phenolic resin glass fiber reinforced prepregs are highly suitable for airplane interior components due to their high fire resistance, high temperature performance, and low-density characteristics. Safran Cabin seeks to improve their storage of the phenolic resin prepreg during their manufacturing process. The issues the company faces are the occasional delamination of prepreg laminas or the loss of tackiness rendering the lamina unfit for use. The area of investigation was determining the weight loss of volatiles during out-time. The term “out-time” consists of the time the prepreg experiences in transit, on the shop floor, and in short-term temperature-controlled storage. Simulated storage conditions were investigated to three different temperature ranges that the prepreg samples experience during out-time: 2.6°C, 16-18°C, and 28-33°C. The project objective was to better understand the loss of volatiles the prepreg experiences. The volatiles under investigation are from the solvent used in the preparation and manufacturing of the prepreg. The functional groups of key volatiles in the prepreg were detected and monitored using a Fourier Transform Infrared Spectroscopy (FTIR) after different simulated storage periods within the maximum out-time of 11 days. Additionally, Thermogravimetric Analysis (TGA) was used to measure the weight loss of remaining volatiles in the phenolic resin prepregs. The end results of this project suggest that the volatile loss during out-time is more temperature dependent than time dependent