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Screening Rules for Convex Problems

Raj, A., Olbrich, J., Gärtner, B., Schölkopf, B., Jaggi, M.

2016 (unpublished) Submitted

[BibTex]

[BibTex]

2014


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Modeling the polygenic architecture of complex traits

Rakitsch, Barbara

Eberhard Karls Universität Tübingen, November 2014 (phdthesis)

[BibTex]

2014

[BibTex]


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A Novel Causal Inference Method for Time Series

Shajarisales, N.

Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (mastersthesis)

PDF [BibTex]

PDF [BibTex]


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A global analysis of extreme events and consequences for the terrestrial carbon cycle

Zscheischler, J.

Diss. No. 22043, ETH Zurich, Switzerland, ETH Zurich, Switzerland, 2014 (phdthesis)

[BibTex]

[BibTex]


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Development of advanced methods for improving astronomical images

Schmeißer, N.

Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (diplomathesis)

[BibTex]

[BibTex]


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The Feasibility of Causal Discovery in Complex Systems: An Examination of Climate Change Attribution and Detection

Lacosse, E.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

[BibTex]

[BibTex]


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Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size

Huang, B.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

[BibTex]

[BibTex]


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Analysis of Distance Functions in Graphs

Alamgir, M.

University of Hamburg, Germany, University of Hamburg, Germany, 2014 (phdthesis)

[BibTex]

[BibTex]

2013


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Camera-specific Image Denoising

Schober, M.

Eberhard Karls Universität Tübingen, Germany, October 2013 (diplomathesis)

PDF [BibTex]

2013

PDF [BibTex]


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Modelling and Learning Approaches to Image Denoising

Burger, HC.

Eberhard Karls Universität Tübingen, Germany, 2013 (phdthesis)

[BibTex]

[BibTex]


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Linear mixed models for genome-wide association studies

Lippert, C.

University of Tübingen, Germany, 2013 (phdthesis)

[BibTex]

[BibTex]


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Modeling and Learning Complex Motor Tasks: A case study on Robot Table Tennis

Mülling, K.

Technical University Darmstadt, Germany, 2013 (phdthesis)

[BibTex]

2012


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Scalable graph kernels

Shervashidze, N.

Eberhard Karls Universität Tübingen, Germany, October 2012 (phdthesis)

Web [BibTex]

2012

Web [BibTex]


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Probabilistic Modelling of Expression Variation in Modern eQTL Studies

Zwießele, M.

Eberhard Karls Universität Tübingen, Germany, October 2012 (mastersthesis)

[BibTex]

[BibTex]


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Learning Motor Skills: From Algorithms to Robot Experiments

Kober, J.

Technische Universität Darmstadt, Germany, March 2012 (phdthesis)

PDF [BibTex]

PDF [BibTex]


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Structure and Dynamics of Diffusion Networks

Gomez Rodriguez, M.

Department of Electrical Engineering, Stanford University, 2012 (phdthesis)

Web [BibTex]

Web [BibTex]


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Blind Deconvolution in Scientific Imaging & Computational Photography

Hirsch, M.

Eberhard Karls Universität Tübingen, Germany, 2012 (phdthesis)

Web [BibTex]

Web [BibTex]


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Mining correlated loci at a genome-wide scale

Velkov, V.

Eberhard Karls Universität Tübingen, Germany, 2012 (mastersthesis)

[BibTex]

[BibTex]

2010


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Approximate Inference in Graphical Models

Hennig, P.

University of Cambridge, November 2010 (phdthesis)

Web [BibTex]

2010

Web [BibTex]


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Bayesian Inference and Experimental Design for Large Generalised Linear Models

Nickisch, H.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, September 2010 (phdthesis)

PDF Web [BibTex]

PDF Web [BibTex]


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Inferring High-Dimensional Causal Relations using Free Probability Theory

Zscheischler, J.

Humboldt Universität Berlin, Germany, August 2010 (diplomathesis)

PDF [BibTex]

PDF [BibTex]


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Predictive Representations For Sequential Decision Making Under Uncertainty

Boularias, A.

Université Laval, Quebec, Canada, July 2010 (phdthesis)

Abstract
The problem of making decisions is ubiquitous in life. This problem becomes even more complex when the decisions should be made sequentially. In fact, the execution of an action at a given time leads to a change in the environment of the problem, and this change cannot be predicted with certainty. The aim of a decision-making process is to optimally select actions in an uncertain environment. To this end, the environment is often modeled as a dynamical system with multiple states, and the actions are executed so that the system evolves toward a desirable state. In this thesis, we proposed a family of stochastic models and algorithms in order to improve the quality of of the decision-making process. The proposed models are alternative to Markov Decision Processes, a largely used framework for this type of problems. In particular, we showed that the state of a dynamical system can be represented more compactly if it is described in terms of predictions of certain future events. We also showed that even the cognitive process of selecting actions, known as policy, can be seen as a dynamical system. Starting from this observation, we proposed a panoply of algorithms, all based on predictive policy representations, in order to solve different problems of decision-making, such as decentralized planning, reinforcement learning, or imitation learning. We also analytically and empirically demonstrated that the proposed approaches lead to a decrease in the computational complexity and an increase in the quality of the decisions, compared to standard approaches for planning and learning under uncertainty.

PDF [BibTex]


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Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data

Shelton, J.

Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 (diplomathesis)

PDF [BibTex]

PDF [BibTex]


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Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET)

Mantlik, F.

Biologische Kybernetik, Universität Mannheim, Germany, March 2010 (diplomathesis)

[BibTex]

[BibTex]


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Finding Gene-Gene Interactions using Support Vector Machines

Rakitsch, B.

Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

[BibTex]

[BibTex]


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Structural and Relational Data Mining for Systems Biology Applications

Georgii, E.

Eberhard Karls Universität Tübingen, Germany , 2010 (phdthesis)

Web [BibTex]

Web [BibTex]


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Population Coding in the Visual System: Statistical Methods and Theory

Macke, J.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

[BibTex]

[BibTex]


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Bayesian Methods for Neural Data Analysis

Gerwinn, S.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

Web [BibTex]

Web [BibTex]


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Clustering with Neighborhood Graphs

Maier, M.

Universität des Saarlandes, Saarbrücken, Germany, 2010 (phdthesis)

Web [BibTex]

Web [BibTex]


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Detecting and modeling time shifts in microarray time series data applying Gaussian processes

Zwießele, M.

Eberhard Karls Universität Tübingen, Germany, 2010 (thesis)

[BibTex]

[BibTex]


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Detecting the mincut in sparse random graphs

Köhler, R.

Eberhard Karls Universität Tübingen, Germany, 2010 (diplomathesis)

[BibTex]

[BibTex]


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A wider view on encoding and decoding in the visual brain-computer interface speller system

Martens, S.

Eberhard Karls Universität Tübingen, Germany, 2010 (phdthesis)

[BibTex]

2007


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Some Theoretical Aspects of Human Categorization Behavior: Similarity and Generalization

Jäkel, F.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, November 2007, passed with "ausgezeichnet", summa cum laude, published online (phdthesis)

PDF [BibTex]

2007

PDF [BibTex]


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Statistical Learning Theory Approaches to Clustering

Jegelka, S.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, November 2007 (diplomathesis)

PDF [BibTex]

PDF [BibTex]


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Error Correcting Codes for the P300 Visual Speller

Biessmann, F.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, July 2007 (diplomathesis)

Abstract
The aim of brain-computer interface (BCI) research is to establish a communication system based on intentional modulation of brain activity. This is accomplished by classifying patterns of brain ac- tivity, volitionally induced by the user. The BCI presented in this study is based on a classical paradigm as proposed by (Farwell and Donchin, 1988), the P300 visual speller. Recording electroencephalo- grams (EEG) from the scalp while presenting letters successively to the user, the speller can infer from the brain signal which letter the user was focussing on. Since EEG recordings are noisy, usually many repetitions are needed to detect the correct letter. The focus of this study was to improve the accuracy of the visual speller applying some basic principles from information theory: Stimulus sequences of the speller have been modified into error-correcting codes. Additionally a language model was incorporated into the probabilistic letter de- coder. Classification of single EEG epochs was less accurate using error correcting codes. However, the novel code could compensate for that such that overall, letter accuracies were as high as or even higher than for classical stimulus codes. In particular at high noise levels, error-correcting decoding achieved higher letter accuracies.

PDF [BibTex]

PDF [BibTex]


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Data-driven goodness-of-fit tests

Langovoy, MA.

Biologische Kybernetik, Georg-August-Universität Göttingen, Göttingen, Germany, July 2007 (phdthesis)

Web [BibTex]

Web [BibTex]


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Nonparametric Bayesian Discrete Latent Variable Models for Unsupervised Learning

Görür, D.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, April 2007, published online (phdthesis)

PDF PDF [BibTex]

PDF PDF [BibTex]


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Applications of Kernel Machines to Structured Data

Eichhorn, J.

Biologische Kybernetik, Technische Universität Berlin, Berlin, Germany, March 2007, passed with "sehr gut", published online (phdthesis)

PDF [BibTex]

PDF [BibTex]


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A priori Knowledge from Non-Examples

Sinz, FH.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, March 2007 (diplomathesis)

PDF Web [BibTex]

PDF Web [BibTex]


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Machine Learning for Mass Production and Industrial Engineering

Pfingsten, T.

Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, February 2007 (phdthesis)

PDF [BibTex]

PDF [BibTex]


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Development of a Brain-Computer Interface Approach Based on Covert Attention to Tactile Stimuli

Raths, C.

University of Tübingen, Germany, University of Tübingen, Germany, January 2007 (diplomathesis)

[BibTex]

[BibTex]