Crosslingual Document Embedding as Reduced-Rank Ridge Regression

There has recently been much interest in extending vector-based word representations to multiple languages, such that words can be compared across languages. In this paper, we shift the focus from words to documents and introduce a method for embedding documents written in any language into a single, language-independent vector space. For training, our approach leverages a multilingual corpus where the same concept is covered in multiple languages (but not necessarily via exact translations), such as Wikipedia. Our method, Cr5 (Crosslingual reduced-rank ridge regression), starts by training a ridge-regression-based classifier that uses language-specific bag-of-word features in order to predict the concept that a given document is about. We show that, when constraining the learned weight matrix to be of low rank, it can be factored to obtain the desired mappings from language-specific bags-of-words to language-independent embeddings. As opposed to most prior methods, which use pretrained monolingual word vectors, postprocess them to make them crosslingual, and finally average word vectors to obtain document vectors, Cr5 is trained end-to-end and is thus natively crosslingual as well as document-level. Moreover, since our algorithm uses the singular value decomposition as its core operation, it is highly scalable. Experiments show that our method achieves state-of-the-art performance on a crosslingual document retrieval task. Finally, although not trained for embedding sentences and words, it also achieves competitive performance on crosslingual sentence and word retrieval tasks.Comment: In The Twelfth ACM International Conference on Web Search and Data Mining (WSDM '19

Exploiting Social Network Structure for Person-to-Person Sentiment Analysis

Person-to-person evaluations are prevalent in all kinds of discourse and important for establishing reputations, building social bonds, and shaping public opinion. Such evaluations can be analyzed separately using signed social networks and textual sentiment analysis, but this misses the rich interactions between language and social context. To capture such interactions, we develop a model that predicts individual A's opinion of individual B by synthesizing information from the signed social network in which A and B are embedded with sentiment analysis of the evaluative texts relating A to B. We prove that this problem is NP-hard but can be relaxed to an efficiently solvable hinge-loss Markov random field, and we show that this implementation outperforms text-only and network-only versions in two very different datasets involving community-level decision-making: the Wikipedia Requests for Adminship corpus and the Convote U.S. Congressional speech corpus

Faster valuation of financial derivatives

Monte Carlo simulation is widely used to value complex financial instruments. An alternative to Monte Carlo is to use "low discrepancy" methods. Theory suggests that low discrepancy methods might be superior to the Monte Carlo method. We compared the performance of low discrepancy methods with Monte Carlo on a Collateralized Mortgage Obligation (CMO) with ten tranches. We found that a particular low discrepancy method based on Sobol points consistently outperforms Monte Carlo. Although our tests were for a CMO, we believe it will be advantageous to use the Sobol method for many other types of instruments. We have made major improvements in published routines for generating Sobol points which we have embedded in a software system called FINDER

Holistic Deep Learning

There is much interest in deep learning to solve challenges in applying neural network models in real-world environments. In particular, three areas have received considerable attention: adversarial robustness, parameter sparsity, and output stability. Despite numerous attempts to solve these problems independently, little work simultaneously addresses the challenges. In this paper, we address the problem of constructing holistic deep learning models by proposing a novel formulation that solves these issues in combination. Real-world experiments on both tabular and MNIST datasets show that our formulation can simultaneously improve the accuracy, robustness, stability, and sparsity over traditional deep learning models among many others.Comment: In preparation for Machine Learnin

Algorithms and Subsystems for Next Generation Optical Networks

This thesis investigates algorithms and subsystems for digital coherent optical networks to alleviate system requirements and enable spectrally efficient systems. Spectral shaping of individual channel is investigated to mitigate backreflections in bi-directional Passive Optical Network (PON) enabling more than 1000 users operating at 10 Gbit/s. It is then shown that temporal delay skews, caused by misalignment in the coherent receiver, induce a large penalty for Nyquist filtered signals. An adaptive 4×4 equaliser is developed to compensate the imperfections dynamically. This is subsequently demonstrated experimentally with Polarisation Division Multiplexed (PDM) Quadrature Phase Shift Keying (QPSK) and 16-level Quadrature Amplitude Modulation (QAM). Furthermore, a modified blind equaliser is designed to adaptively compensate for unknown amount of Chromatic Dispersion (CD). The equaliser is demonstrated experimentally using 10.7 GBd PDM-QPSK transmission over 5,200 km. To simplify the computational complexity of the equalisers a multiplier free update scheme is explored in simulations. Optical frequency combs are investigated as phase and frequency synchronised sub- carrier sources for Dense Wavelength Division Multiplexing (DWDM) systems. The effect of phase synchronisation between sub-channels of a superchannel is examined in simulations without showing performance deviation when no additional optical or digital processing is applied. Afterwards, the transmission performance of two generation techniques implementing 400 Gbit/s superchannels, utilising PDM-16QAM, is evaluated. Although, the average performance of the two combs is identical subchannel fluctuations are observed due to uneven spectral profile. Carrier Phase Estimation (CPE) is explored for both single channel and superchannels systems. An equaliser interleaved with CPE, is explored for PDM-64QAM with minor improvement. Alternatively, Digital Coherence Enhancement (DCE) allowed the detection of 6 GBd PDM-64QAM with a 1.4 MHz linewidth laser, an order of magnitude improvement in linewidth tolerance. Finally, a joint CPE across a comb superchannel is demonstrated with a factor of 5 tolerance improvement

ОСТАТОЧНАЯ ДЕФОРМАЦИЯ ПОСЛЕ ДВУСТОРОННЕГО ЭНДОПРОТЕЗИРОВАНИЯ КОЛЕННЫХ СУСТАВОВ: ВЛИЯНИЕ НА КРАТКОСРОЧНЫЕ РЕЗУЛЬТАТЫ

Purpose — to evaluate the impact of frontal positioning of prosthesis components after bilateral Tka on short term functional outcomes. Material and Methods. The authors performed a retrospective analysis of teleroentgenograms of 466 patients after bilateral Tka with initial varus deformity. Functional and roentgenological outcomes were evaluated at average in 16,4±2,9 months postoperatively. Mean preoperative varus deformity was 10° (from 5 to 25°), initial angle between the anatomical and mechanical femoral axis (FVa) was 6,7±2° (from 3 to 12°). The neutral axis of both lower limbs (Hka = 180±0,5°) was obtained in 99 (21,2%) out of 466 patients. Residual deformity in one of the limbs above 3° with the neutral alignment of the contralateral limb was observed in 44 (9,4%) patients, bilateral residual deformity – in 32 (6,9%) patients. Other 291 patients demonstrated the deviation from mechanical axis in the range from 1 to 3° (±0,5°). all patients were divided into three groups: first group consisted of 10 patients with neutral axis of one limb and varus deformity of the other limb above 3°; second group — 10 patients with bilateral residual varus deformity above 3°; third group — 12 patients with neutral axis of both limbs (Hka = 180°). The angle of residual deformity averaged 3,7° (from 3,2 to 5,1°).Results. No statistically significant differences between the groups were observed for dynamometric parameters and SF-36 scores, as well as for functional kSS scores (p0,05). However, the authors reported in patients of the first group a stance phase on the side of residual varus deformity longer at 15% (p0,05) and transfer phase shorter at 17% (p0,05) as compared to contralateral limb (with neutral alignment, Hka = 180°), which is indicative of load asymmetry and can have a negative impact at a later stage.Conclusion. Symmetrical residual varus deformity of lower limbs in the rage of 3,2–5,1° has no negative impact of short term clinical and functional outcomes of Tka. Muscular function and gait properties in patients with neutral axis of the lower limbs and in patients with symmetrical residual varus deformity after Tka were similar 16,4±2,9 months postoperatively.Цель исследования — оценить влияние фронтального положения компонентов эндопротеза после двустороннего тотального эндопротезирования коленного сустава на краткосрочные функциональные результаты.Материал и методы. проведен ретроспективный анализ телерентгенограмм 466 пациентов после двустороннего тотального эндопротезирования коленных суставов (Тэкс) с исходной варусной деформацией. Функциональные и рентгенологические результаты оценивали в среднем через 16,4±2,9 мес. до операции варусная деформация в среднем составляла 10° (от 5 до 25°), исходный угол между анатомической и механической осями бедра (FVa) — 6,7±2° (от 3 до 12°). Из 466 пациентов после Тэкс нейтральная ось обеих конечностей (Hka = 180±0,5°) была получена у 99 (21,2%) пациентов. остаточная деформация одной конечности более 3° при нейтрально выравненной оси противоположной конечности наблюдалась у 44 (9,4%) пациентов, а двусторонняя — у 32 (6,9%). у остальных 291 пациента отклонение от механической оси варьировало в пределах от 1 до 3°(±0,5°). пациенты были поделены на три группы: 1-я группа — 10 пациентов с нейтральной осью одной конечности и варусной деформацией другой конечности более 3°; 2-я группа — 10 пациентов с двусторонней остаточной варусной деформацией более 3°; 3-я группа — 12 пациентов с нейтральной осью обеих нижних конечностей (Hka = 180°). угол остаточной деформации в среднем составил 3,7° (от 3,2 до 5,1°).Результаты. статистически значимых различий между группами по динамометрическим показателям и оценке по шкале SF-36 и функциональной главе шкалы kSS выявлено не было (p0,05). однако у пациентов 1-й группы на стороне остаточной варусной деформации отмечено увеличение периода опоры на 15% (p0,05) и уменьшение периода переноса на 17% (p0,05) по сравнению с контралатеральной конечностью (нейтрально выравненной, Hka = 180°), что является признаком асимметрии нагрузки и может негативно сказаться в отдаленном периоде.Заключение. симметричная остаточная варусная деформация нижних конечностей в 3,2–5,1° не оказывает негативного влияния на краткосрочные клинико-функциональные результаты Тэкс. Мышечная функция и качество походки у пациентов с нейтральной осью нижних конечностей и симметричной остаточной варусной деформацией через 16,4±2,9 мес. после Тэкс не имеют статистически значимых различий

Quantum field theory for discrepancies

The concept of discrepancy plays an important role in the study of uniformity properties of point sets. For sets of random points, the discrepancy is a random variable. We apply techniques from quantum field theory to translate the problem of calculating the probability density of (quadratic) discrepancies into that of evaluating certain path integrals. Both their perturbative and non-perturbative properties are discussed.Comment: 26 page

Gaussian limits for discrepancies. I: Asymptotic results

We consider the problem of finding, for a given quadratic measure of non-uniformity of a set of $N$ points (such as $L_2$ star-discrepancy or diaphony), the asymptotic distribution of this discrepancy for truly random points in the limit $N\to\infty$. We then examine the circumstances under which this distribution approaches a normal distribution. For large classes of non-uniformity measures, a Law of Many Modes in the spirit of the Central Limit Theorem can be derived.Comment: 25 pages, Latex, uses fleqn.sty, a4wide.sty, amsmath.st