Diversification Benefits of European Small- Cap Stocks After the Global Financial Crisis and Brexit

In this paper we investigate the diversification gains obtained from investing in European small-cap stocks, focusing on the periods since the Global Financial Crisis and Brexit. We find mixed evidence to support the assertion that European small-caps provide diversification benefits to a benchmark portfolio of large US stocks. The benefits are further reduced when benchmark assets include both a US large-cap portfolio as well as a portfolio of European large-cap stocks. After Brexit, US investors achieve diversification benefits from investments in European large-cap stocks. However, after Brexit, small-cap stocks from only one country in the EU are shown to provide further diversification gains

Vizualizace konceptů pomocí generování obrazu

Název: Vizualizace konceptů pomocí generování obrazu Autor: Tien Dat Nguyen Katedra: Ústav formální a aplikované lingvistiky Vedoucí práce: RNDr. Pavel Pecina, Ph.D., Ústav formální a aplikované lingvistiky MFF UK a Angeliki Lazaridou, Ra_aella Bernardi, Marco Baroni (University of Trento), Počítačová lingvistika a počítačové vidění mají společný způsob, jak zachytit sémantiku lingvistických/vizuálních jednotek pomocí vektorové reprezentace. Navíc kvalitní sémantická reprezentace může být efektivně sestrojena pomocí nedávných pokroků v metodách neuronových sítí. Avšak jejich pochopení zůstává omezené a je nutné je posuzovat intuitivně. Mezimodální mapování je mapování mezi vektorovou sémantikou zabudovanou do slov a vizuálních reprezentací odpovídajících objektů v obrazu. Invertování obrazové reprezentace zahrnuje učení inverze obrazu vizuálních vektorů (SIFT, HOG a CNN rysy) pro rekonstrukci původní informace. Cílem této práce je vybudování úplné pipeline, ve které jsou slovní reprezentace transformovány do obrazových vektorů pomocí mezimodálního mapování a tyto vektory jsou promítnuty do pixelového prostoru použitím inverze. Ukazuje se, že tento způsob může být průlomovým prostředkem, jakým lze zkontrolovat a vyhodnotit sémantiku zakódovanou v reprezentaci slov generováním obrázků, které jej reprezentují.Title: Toward concept visualization through image generation Author: Tien Dat Nguyen Department: Institute of Formal and Applied Linguistics Supervisors: Pavel Pecina (Charles University in Prague), Angeliki Lazaridou, Raffaella Bernardi, Marco Baroni (University of Trento), Abstract: Computational linguistic and computer vision have a common way to embed the semantics of linguistic/visual units through vector representation. In addition, high-quality semantic representations can be effectively constructed thanks to recent advances in neural network methods. Nevertheless, the under- standing of these representations remains limited, so they need to be assessed in an intuitive way. Cross-modal mapping is mapping between vector semantic embedding of words and the visual representations of the corresponding objects from images. Inverting image representation involves learning an image inversion of visual vectors (SIFT, HOG and CNN features) to reconstruct the original one. The goal of this project is to build a complete pipeline, in which word represen- tations are transformed into image vectors using cross modal mapping and these vectors are projected to pixel space using inversion. This suggests that there might be a groundbreaking way to inspect and evaluate the semantics encoded in word representations by...Institute of Formal and Applied LinguisticsÚstav formální a aplikované lingvistikyMatematicko-fyzikální fakultaFaculty of Mathematics and Physic

Phenolic glucosides from the leaves of Desmodium gangeticum (L.) DC

From the water-soluble extract of the leaves of Desmodium gangeticum, three phenolic glucosides were isolated. By means of spectroscopic methods they were identified as methyl salicylate β-D-glucopyranoside (1), leonuriside A (2) and syringaresinol-4'-O-β-D-glucopyranoside (3). These compounds were isolated for the first time from the genus Desmodium. Compound 1 significantly inhibited a-glucosidase in comparison with diabetic drug acarbose

Thread Reconstruction in Conversational Data using Neural Coherence Models

Discussion forums are an important source of information. They are often used to answer specific questions a user might have and to discover more about a topic of interest. Discussions in these forums may evolve in intricate ways, making it difficult for users to follow the flow of ideas. We propose a novel approach for automatically identifying the underlying thread structure of a forum discussion. Our approach is based on a neural model that computes coherence scores of possible reconstructions and then selects the highest scoring, i.e., the most coherent one. Preliminary experiments demonstrate promising results outperforming a number of strong baseline methods.Comment: Neu-IR: Workshop on Neural Information Retrieval 201

Learning Symmetrization for Equivariance with Orbit Distance Minimization

We present a general framework for symmetrizing an arbitrary neural-network architecture and making it equivariant with respect to a given group. We build upon the proposals of Kim et al. (2023); Kaba et al. (2023) for symmetrization, and improve them by replacing their conversion of neural features into group representations, with an optimization whose loss intuitively measures the distance between group orbits. This change makes our approach applicable to a broader range of matrix groups, such as the Lorentz group O(1, 3), than these two proposals. We experimentally show our method's competitiveness on the SO(2) image classification task, and also its increased generality on the task with O(1, 3). Our implementation will be made accessible at https://github.com/tiendatnguyen-vision/Orbit-symmetrize.Comment: 16 pages, 1 figur

Drama with Unique Setting and Profession based on the Point of View of Korean Drama Connoisseurs

This article aims to discuss K-Drama with a unique work profession background through the abstinence point of k-drama fans. The modern Korean entertainment landscape would not be complete without K-drama. Millions of people around the world enjoy watching Korean dramas. Many parallels are made between the characters, allowing viewers to gain a better understanding of Korean culture. K-drama fans will be paired with Korean drama works to write here. They are not your ordinary doctors, lawyers or professors, but people from all walks of lif