The pivotal approach and deviance-based approach are applied to both cases with and without nuisance parameters. We introduce an iterative sample generating procedure, which uses a cascade of random forests to gradually produce observations that are less and less distinguishable from the real ones. In our second measure we consider the reliability of each method for not yielding a node as a parent which is not. This study proposes a way to measure the impacts of hypo-thetical interventions while using machine learning algorithms instead of the commonly used linear regression approach in econometrics. One results from the proof of the identifiability of BAP models and is implemented in this thesis. The models in Word2Vec and GloVe have in common that the result- ing embedding vectors show a property called additive compositionality.

Reinforcement Learning, aided by the representation learning power of deep neural networks has enabled researchers to solve complex decision making problems, the most notable one being AlphaGO, a computer program which beat the champion of the board game GO. Traditionally, Relationship Managers are required to invest time and tedious calculations to make personalised recommendations on what new investment instruments their clients might be interested in buying. Though these approaches are extensively investigated in research community, it is still limited to different variants of matrix factorization. The optimal choice of the method depends on the objective and on the specific parameters combination. Enter your city or zip code in the “where” box to show results in your area.

For this, a model fitting procedure was determined, which is able to deal with the NA-structure in the observed temperature anomaly data and which master thesis at swissquant a reasonable computational time.

The first one addresses non-linear deterministic systems, while the second one is designed for linear stochastic systems. Our method achieved extraordinary perfor-mance in the validation set across all acronyms and remarkable generalization power in an independent dataset.

The aim of this work is to conduct a comprehensive comparison study of the existing non-parametric techniques for estimation of the Hawkes model, which without making any a priori assumptions master thesis at swissquant the correlation structure of the observables, provide us insights into the data.

For jobs in the United Master thesis at swissquant, please visit www. Bates or Gallantsuch problem has been studied almost entirely from either a Frequentist or a Bayesian perspective.

The focus lies on forward and backward pass using backpropagation through time.

We discuss an approach that could lead to a consistency proof. Models fit to the goal difference of each team are then combined for one unified prediction of the goal difference. By comparing the results when thresholds were optimized on a site- by-site basis, to those when a single threshold was master thesis at swissquant for all nine sites we found that optimal thresholds do not translate accross sites, rather they display a local behavior.

It also shows, that a possibility to estimate a causal master thesis at swissquant can be lost purely due to a master thesis at swissquant from a latent projection to a corresponding MAG and provides a criterion that specifies when it happens. It has been successfully used for representing sensory data like images and audio, also providing an explanation for many observed properties in the response of cortical simple cells.


We introduce a new theorem that can compare many valid adjustment sets in terms of their asymp- totic variance using just the graph structure of the underlying causal directed acyclic graph. Hereby, we focus on linear Structural Equation Models SEM master thesis at swissquant restrict ourselves to the situation where no hidden confounders are present. We also illustrate the developed methodology on a real-life example of stock returns.

Furthermore, we demonstrate in detail the application of the methods to a real-world study case. Interventional experiments are not without drawbacks, as producing interventional data can be rather expensive and in special cases even unethical. Forecasting parking occupancy rates in the city of Zurich Dr.

In this setting, the Random Forest algorithm proves to perform the best in both terms of goodness-of-fit and out-of-sample prediction performance. Chapter 5 deals with the hugely important concept of symmetrization and, with the ideas of Chapter 3, applies this to the non measurable map implied by the empirical process. The variance of the prediction error derivation master thesis at swissquant based on various linear approximations of the prediction error.

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The derived results were compared to manual annotations made by two human graders for the 3mm region surrounding the fovea in the central B-scan.

The studies investigate differences in molecules present in breath due to lung diseases. The models in Word2Vec and GloVe have in common that the result- ing embedding vectors show a property called additive compositionality. It was found that the GeneReader instruments are calibrated well and that their contribution to the variability of the master thesis at swissquant is relatively small.

Either to obtain a smaller set of estimated parameters that exhibits the strongest effects or to obtain a robust estimator which reduces the variability of the estimated model parameters. A generalized pattern of variation was found for temperature along master thesis at swissquant the region-season combinations analyzed, while season dependent and region dependent patterns were identified for precipitation.

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Chantal Swan contributed to this work by providing me with data and information concerning it. After gathering the simple data master thesis at swissquant the relevant websites, numerous variables are constructed to further capture the relative strength of each team. Implement a covariance master thesis at swissquant methods for inhomogeneous, asynchronous and noisy data. The thesis will focus on the estimation of high-frequency covariance dynamics for financial assets, with the purpose of developing a methodology to assess intraday portfolio risk figures.

Differential splicing experiments aim to use microarray or RNA sequencing RNA-seq technologies to detect genes exhibiting differences in splicing patterns between groups of biological samples, for example comparing diseased versus healthy samples, or treated versus untreated.


In Markowitz’s Modern Portfolio Theory, portfolio on Efficient Frontier has the minimized risk at a given level of expected return, or has the maximized expected return at a given level of risk.

Furthermore, an artificial outlier study is conducted to assess the outlier detection power of the four considered regularization methods. Then we use anl1-minimization algorithm to inpaint missingpixels of a different set of facial images, called the test set. The application on the temperature anomaly data for January in this thesis confirmed this.

The implementation was made with conditional simulations followed by an iteration process, which included kriging predictions, computing of expected loss and spatial master thesis at swissquant annealing. We show that balancing the data set improves the performance of all algorithms studied. The model GloVe Pennington, Socher, and Manning is a log-bilinear regression model based mainly on the co-occurrence statistics of master thesis at swissquant words in the text corpus.

We analyse the structure of the different models in detail, show relationships between them and further simple models and proof how additive compositionality arises in certain models under some constraints.

It shows how this basic design is weak in many situations and introduces designs which are more versatile. In master thesis at swissquant, considering our response variable is ordinal, we also proposed four “near” measures: For all the aforementioned methods, the very important step of checking the requirement assumptions is master thesis at swissquant in detail.

It does so by assessing climate change in the course of the 21st century in Switzerland with a focus on projections of temperature and precipitation. Seven different predictors are com- pared. Since a vast audience can read this work, technical rigidity is less in scope, going into the direction to a more applied master thesis at swissquant in order to understand what is going on and to take meaningful decision for the future.

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Master thesis at swissquant also introduced Critical Line Algorithm, a quadratic program- ming method for portfolio selection. For the purpose of automating this process in the context of private banking, two existing model-based collaborative filtering recommender algorithms, the Confidence Weighted model and the Adaptive Boosting Personalised Ranking AdaBPR model were master thesis at swissquant for and evaluated on two different financial datasets.

The objective of this paper is to propose a continuous version of DML method framework, and to give similar consistency and asymptotic normality result based on the proposed Continuous Double Machine Learning method CDML. This social network offers the opportunity to study the dynamics of real-world occurrences over time and how social systems react to different stimuli.