273 research outputs found
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
- …