A Rigorous Framework for the Mean Field Limit of Multilayer Neural Networks

We develop a mathematically rigorous framework for multilayer neural networks in the mean field regime. As the network's width increases, the network's learning trajectory is shown to be well captured by a meaningful and dynamically nonlinear limit (the \textit{mean field} limit), which is characterized by a system of ODEs. Our framework applies to a broad range of network architectures, learning dynamics and network initializations. Central to the framework is the new idea of a \textit{neuronal embedding}, which comprises of a non-evolving probability space that allows to embed neural networks of arbitrary widths. We demonstrate two applications of our framework. Firstly the framework gives a principled way to study the simplifying effects that independent and identically distributed initializations have on the mean field limit. Secondly we prove a global convergence guarantee for two-layer and three-layer networks. Unlike previous works that rely on convexity, our result requires a certain universal approximation property, which is a distinctive feature of infinite-width neural networks. To the best of our knowledge, this is the first time global convergence is established for neural networks of more than two layers in the mean field regime

SkipFlow: Incorporating Neural Coherence Features for End-to-End Automatic Text Scoring

Deep learning has demonstrated tremendous potential for Automatic Text Scoring (ATS) tasks. In this paper, we describe a new neural architecture that enhances vanilla neural network models with auxiliary neural coherence features. Our new method proposes a new \textsc{SkipFlow} mechanism that models relationships between snapshots of the hidden representations of a long short-term memory (LSTM) network as it reads. Subsequently, the semantic relationships between multiple snapshots are used as auxiliary features for prediction. This has two main benefits. Firstly, essays are typically long sequences and therefore the memorization capability of the LSTM network may be insufficient. Implicit access to multiple snapshots can alleviate this problem by acting as a protection against vanishing gradients. The parameters of the \textsc{SkipFlow} mechanism also acts as an auxiliary memory. Secondly, modeling relationships between multiple positions allows our model to learn features that represent and approximate textual coherence. In our model, we call this \textit{neural coherence} features. Overall, we present a unified deep learning architecture that generates neural coherence features as it reads in an end-to-end fashion. Our approach demonstrates state-of-the-art performance on the benchmark ASAP dataset, outperforming not only feature engineering baselines but also other deep learning models.Comment: Accepted to AAAI 201

Simple and Effective Curriculum Pointer-Generator Networks for Reading Comprehension over Long Narratives

This paper tackles the problem of reading comprehension over long narratives where documents easily span over thousands of tokens. We propose a curriculum learning (CL) based Pointer-Generator framework for reading/sampling over large documents, enabling diverse training of the neural model based on the notion of alternating contextual difficulty. This can be interpreted as a form of domain randomization and/or generative pretraining during training. To this end, the usage of the Pointer-Generator softens the requirement of having the answer within the context, enabling us to construct diverse training samples for learning. Additionally, we propose a new Introspective Alignment Layer (IAL), which reasons over decomposed alignments using block-based self-attention. We evaluate our proposed method on the NarrativeQA reading comprehension benchmark, achieving state-of-the-art performance, improving existing baselines by $51\%$ relative improvement on BLEU-4 and $17\%$ relative improvement on Rouge-L. Extensive ablations confirm the effectiveness of our proposed IAL and CL components.Comment: Accepted to ACL 201

SỰ LÂY LAN RỦI RO GIỮA TỶ GIÁ ĐỒNG VIỆT NAM VỚI CÁC ĐỒNG TIỀN CHỦ CHỐT CHÂU Á TRƯỚC VÀ TRONG ĐẠI DỊCH COVID-19

This research utilizes the framework of forecast error variance decomposition to examine the extent of risk spillovers between the Vietnamese dong (VND) and vital Asian currencies before and during the Covid-19 pandemic. The findings show that, in general, the risk contagion between the VND and other crucial Asian currencies in the study is modest. Second, the intensity of risk spillovers is not constant but varies over time, spiking significantly when Covid-19 became a pandemic. Third, the VND is a net-risk receiver currency, especially from stronger currencies such as KRW, SGD, or JPY, and becomes more vulnerable during the disease occurrence.Nghiên cứu áp dụng khung phân tích phân rã phương sai sai số dự báo để khảo sát mức độ lây lan rủi ro tỷ giá giữa đồng tiền Việt Nam (VND) với các đồng tiền chủ chốt trong khu vực châu Á trước và trong đại dịch Covid-19. Kết quả nghiên cứu cho thấy: Một là, nhìn chung mức lây lan rủi ro giữa VND với các đồng tiền châu Á chủ chốt trong nghiên cứu ở mức khiêm tốn. Hai là, cường độ lây lan rủi ro không cố định mà có sự thay đổi theo thời gian, tăng đột biến khi Covid-19 trở thành đại dịch. Ba là, đồng VND là đồng tiền nhận ròng rủi ro, đặc biệt từ các đồng tiền mạnh như KRW, SGD hay JPY và trở nên dễ bị tổn thương hơn khi dịch bệnh xảy ra

The Effect of ENSO on Hydrological Structure and Environment in the South Central Coast – Vietnam

ENSO (El Niño-Southern Oscillation) phenomena have impacted on the hydrodynamic regime and environmental factors of the tropical ocean in general. In case of Vietnamese South-Central Waters, impacts of ENSO only focused on issues of changing seasonal wind, seawater temperature anomalies, changing of water masses as the air-sea interaction. Based on several data sets collecting in the period of 2003-2017, new finding of seawater temperature, salinity and environmental factors was identified in the water masses of Vietnamese South-Central Waters. The highest salinity was 35.4 ‰. During the El Nino event, increasing water temperature and salinity caused to move the deeper water masses to be closer to the sea surface than that initial depth in the neutral period. During the La Nina event, the temperature of most water masses reduced by 0.1-3°C, and then these water masses could be affected to the deeper layer. During the phase from strong ENSO event towards the neutral time, nutrient salts of the 4 water masses were lower concentration in the neutral year, causing the lack of phosphorus in sea surface water masses

Vietnam geographical exploitation under the United Nations Convention on the Law of the Sea in 1982 (UNCLOS 1982)

As an active member of the United Nations Convention on the Law of the Sea - UNCLOS, Vietnam has completed 3 Reports on the Limits of the Continental Shelf and has submitted two of them to the Commission on the Limits of the Continental Shelf - CLCS, before the deadline 13-5-2009. Those are: (1) Outer Limits of the Vietnam’s Extended Continental Shelf: North Area (VNM-N); (2) Outer Limits of the Vietnam’s Extended Continental Shelf: Middle Area (VNM-M) and (3) Vietnam - Malaysia Joint Continental Shelf Submission. The VNM-M has not yet been submitted but it was mentioned to the CLCS and will be submitted in the appropriate time.Vietnam’s submissions were highly appreciated by CLCS; although the CLCS has not yet organized a special sub-committee to look at our reports, the secretariat of CLCS has already posted the executive reports of our submissions, with our principle claims on the continental shelf, on the website of the CLCS since May 2009. This paper presents shortly the UNCLOS and its application in Vietnam case

Coot Bird Behavior-Based Optimization Algorithm For Optimal Placement Of Thyristor Controlled Series Compensator Devices In Transmission Power Networks

This study presents the new application of Coot bird behavior-based optimization algorithm (COOTBA) for optimal placement of Thyristor Con- trolled Series Compensator (TCSC) devices in an IEEE 30-node transmission power network with three single objectives, including fuel cost, power loss, and voltage deviation. COOTBA is implemented for the system with one case without TCSC devices and three others with TCSC. COOTBA can reach smaller cost and loss than previous algorithms by from 0.04% to 3.78%, and from 6.7% to 40.3% in the first case with- out TCSC. In the second case with TCSC, COOTBA can reach smaller cost than others by from 0.008% to 0.66%. In addition, the comparisons of results from COOTBA in the three cases with TCSC indicate that TCSC should be optimized for both location and reac- tance, and the limitation of TCSC devices should be high enough. Thus, COOTBA is an effective algorithm for optimizing TCSC devices on transmission power systems

The application of (Y,Gd)BO3:Tb3+ and CaGa2S4:Mn2+ phosphors to remote white light-emitting diodes

The remote phosphor structure is superior to the conformal phosphor and the in-cup phosphor in terms of lighting efficiency; however, managing the color quality of the remote phosphor structure has been a nuisance to the manufacturers. To address this problem, many researches were conducted and the results suggested that using dual-layer phosphor structure and triple-layer phosphor structure could improve the color quality in remote phosphor structures. The purpose of this article is to study which one between the two configurations mentioned above allows multi-chip white LEDs (WLEDs) to reach highest indexes in color rendering index (CRI), color quality scale (CQS), luminous flux (LF), and color uniformity. The color temperature of the WLEDs used for the experiments in this article is 8500 K. The result of this research shows that the triple-layer phosphor configuration has higher CRI, CQS, and LE and also able to reduce color deviation resulting in better color uniformity. This conclusion can be verified by analyzing the scattering features of the phosphor layers using the Mie-theory. Being verifiable increases the reliability of the research result and makes it a valuable reference for producing better quality WLEDs

Enhancing the CRI and lumen output for the 6600 K WLED with convex-dual-layer remote phosphor geometry by applying red-emitting MGSR3SI2O8:EU2+,MN2+ phosphor

The traditional white LED product established with a single chip and a single phosphor results in a low color rendering index (CRI). The upgrade of LED package is comprised of two chips and one phosphor material and gives the higher CRI while keeping high luminous efficiency. Based on previous findings, the research paper performs the application of the two chips and two phosphors to enhance the color tunability of LEDs with different amounts and intensities of the two employed phosphors. Additionally, a color design model is built to serve the purpose of bettering the color fine-tuning of the white-light LED module. The maximum value of the difference between the measured CIE 1931 color coordinates and that of the simulated model is approximately 0.0063 around the 6600 K correlated color temperature (CCT). From the results, this study offers a quick approach to achieve the color fine tuning of a white-light LED module with a high CRI and luminous efficiency