Publications | Empirical Inference - Max Planck Institute for Intelligent Systems

166 results (View BibTeX file of all listed publications)

2014

Juggling revisited — A voxel based morphometry study with expert jugglers

Gerber, P., Schlaffke, L., Heba, S., Greenlee, M., Schultz, T., Schmidt-Wilcke, T.

NeuroImage, 95, pages: 320-325, 2014 (article)

2014

Gerber, P., Schlaffke, L., Heba, S., Greenlee, M., Schultz, T., Schmidt-Wilcke, T. Juggling revisited — A voxel based morphometry study with expert jugglers NeuroImage, 95, pages: 320-325, 2014 (article)

Web DOI [BibTex]

Assessing attention and cognitive function in completely locked-in state with event-related brain potentials and epidural electrocorticography

Bensch, M., Martens, S., Halder, S., Hill, J., Nijboer, F., Ramos, A., Birbaumer, N., Bodgan, M., Kotchoubey, B., Rosenstiel, W., Schölkopf, B., Gharabaghi, A.

Journal of Neural Engineering, 11(2):026006, 2014 (article)

Abstract

Objective. Patients in the completely locked-in state (CLIS), due to, for example, amyotrophic lateral sclerosis (ALS), no longer possess voluntary muscle control. Assessing attention and cognitive function in these patients during the course of the disease is a challenging but essential task for both nursing staff and physicians. Approach. An electrophysiological cognition test battery, including auditory and semantic stimuli, was applied in a late-stage ALS patient at four different time points during a six-month epidural electrocorticography (ECoG) recording period. Event-related cortical potentials (ERP), together with changes in the ECoG signal spectrum, were recorded via 128 channels that partially covered the left frontal, temporal and parietal cortex. Main results. Auditory but not semantic stimuli induced significant and reproducible ERP projecting to specific temporal and parietal cortical areas. N1/P2 responses could be detected throughout the whole study period. The highest P3 ERP was measured immediately after the patient's last communication through voluntary muscle control, which was paralleled by low theta and high gamma spectral power. Three months after the patient's last communication, i.e., in the CLIS, P3 responses could no longer be detected. At the same time, increased activity in low-frequency bands and a sharp drop of gamma spectral power were recorded. Significance. Cortical electrophysiological measures indicate at least partially intact attention and cognitive function during sparse volitional motor control for communication. Although the P3 ERP and frequency-specific changes in the ECoG spectrum may serve as indicators for CLIS, a close-meshed monitoring will be required to define the exact time point of the transition.

DOI [BibTex]

Bensch, M., Martens, S., Halder, S., Hill, J., Nijboer, F., Ramos, A., Birbaumer, N., Bodgan, M., Kotchoubey, B., Rosenstiel, W., Schölkopf, B., Gharabaghi, A. Assessing attention and cognitive function in completely locked-in state with event-related brain potentials and epidural electrocorticography Journal of Neural Engineering, 11(2):026006, 2014 (article)

DOI [BibTex]

Identifiability of Gaussian Structural Equation Models with Equal Error Variances

Peters, J., Bühlman, P.

Biometrika, 101(1):219-228, 2014 (article)

DOI [BibTex]

Peters, J., Bühlman, P. Identifiability of Gaussian Structural Equation Models with Equal Error Variances Biometrika, 101(1):219-228, 2014 (article)

DOI [BibTex]

Quantifying the effect of intertrial dependence on perceptual decisions

Fründ, I., Wichmann, F., Macke, J.

Journal of Vision, 14(7):1-16, 2014 (article)

Web PDF link (url) DOI [BibTex]

Fründ, I., Wichmann, F., Macke, J. Quantifying the effect of intertrial dependence on perceptual decisions Journal of Vision, 14(7):1-16, 2014 (article)

Web PDF link (url) DOI [BibTex]

Two numerical models designed to reproduce Saturn ring temperatures as measured by Cassini-CIRS

Altobelli, N., Lopez-Paz, D., Pilorz, S., Spilker, L., Morishima, R., Brooks, S., Leyrat, C., Deau, E., Edgington, S., Flandes, A.

Icarus, 238(0):205 - 220, 2014 (article)

Web link (url) DOI [BibTex]

Altobelli, N., Lopez-Paz, D., Pilorz, S., Spilker, L., Morishima, R., Brooks, S., Leyrat, C., Deau, E., Edgington, S., Flandes, A. Two numerical models designed to reproduce Saturn ring temperatures as measured by Cassini-CIRS Icarus, 238(0):205 - 220, 2014 (article)

Web link (url) DOI [BibTex]

CAM: Causal Additive Models, high-dimensional order search and penalized regression

Bühlmann, P., Peters, J., Ernest, J.

Annals of Statistics, 42(6):2526-2556, 2014 (article)

DOI [BibTex]

Bühlmann, P., Peters, J., Ernest, J. CAM: Causal Additive Models, high-dimensional order search and penalized regression Annals of Statistics, 42(6):2526-2556, 2014 (article)

DOI [BibTex]

Policy Evaluation with Temporal Differences: A Survey and Comparison

Dann, C., Neumann, G., Peters, J.

Journal of Machine Learning Research, 15, pages: 809-883, 2014 (article)

PDF [BibTex]

Dann, C., Neumann, G., Peters, J. Policy Evaluation with Temporal Differences: A Survey and Comparison Journal of Machine Learning Research, 15, pages: 809-883, 2014 (article)

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Uncovering the Structure and Temporal Dynamics of Information Propagation

Gomez Rodriguez, M., Leskovec, J., Balduzzi, D., Schölkopf, B.

Network Science, 2(1):26-65, 2014 (article)

Abstract

Time plays an essential role in the diffusion of information, influence, and disease over networks. In many cases we can only observe when a node is activated by a contagion—when a node learns about a piece of information, makes a decision, adopts a new behavior, or becomes infected with a disease. However, the underlying network connectivity and transmission rates between nodes are unknown. Inferring the underlying diffusion dynamics is important because it leads to new insights and enables forecasting, as well as influencing or containing information propagation. In this paper we model diffusion as a continuous temporal process occurring at different rates over a latent, unobserved network that may change over time. Given information diffusion data, we infer the edges and dynamics of the underlying network. Our model naturally imposes sparse solutions and requires no parameter tuning. We develop an efficient inference algorithm that uses stochastic convex optimization to compute online estimates of the edges and transmission rates. We evaluate our method by tracking information diffusion among 3.3 million mainstream media sites and blogs, and experiment with more than 179 million different instances of information spreading over the network in a one-year period. We apply our network inference algorithm to the top 5,000 media sites and blogs and report several interesting observations. First, information pathways for general recurrent topics are more stable across time than for on-going news events. Second, clusters of news media sites and blogs often emerge and vanish in a matter of days for on-going news events. Finally, major events, for example, large scale civil unrest as in the Libyan civil war or Syrian uprising, increase the number of information pathways among blogs, and also increase the network centrality of blogs and social media sites.

DOI [BibTex]

Gomez Rodriguez, M., Leskovec, J., Balduzzi, D., Schölkopf, B. Uncovering the Structure and Temporal Dynamics of Information Propagation Network Science, 2(1):26-65, 2014 (article)

DOI [BibTex]

Causal discovery via reproducing kernel Hilbert space embeddings

Chen, Z., Zhang, K., Chan, L., Schölkopf, B.

Neural Computation, 26(7):1484-1517, 2014 (article)

DOI [BibTex]

Chen, Z., Zhang, K., Chan, L., Schölkopf, B. Causal discovery via reproducing kernel Hilbert space embeddings Neural Computation, 26(7):1484-1517, 2014 (article)

DOI [BibTex]

Impact of Large-Scale Climate Extremes on Biospheric Carbon Fluxes: An Intercomparison Based on MsTMIP Data

Global Biogeochemical Cycles, 2014 (article)

Web DOI [BibTex]

Zscheischler, J., Michalak, A., Schwalm, M., Mahecha, M., Huntzinger, D., Reichstein, M., Berthier, G., Ciais, P., Cook, R., El-Masri, B., Huang, M., Ito, A., Jain, A., King, A., Lei, H., Lu, C., Mao, J., Peng, S., Poulter, B., Ricciuto, D., Shi, X., Tao, B., Tian, H., Viovy, N., Wang, W., Wei, Y., Yang, J., Zeng, N. Impact of Large-Scale Climate Extremes on Biospheric Carbon Fluxes: An Intercomparison Based on MsTMIP Data Global Biogeochemical Cycles, 2014 (article)

Web DOI [BibTex]

A Brain-Computer Interface Based on Self-Regulation of Gamma-Oscillations in the Superior Parietal Cortex

Grosse-Wentrup, M., Schölkopf, B.

Journal of Neural Engineering, 11(5):056015, 2014 (article)

Abstract

Objective. Brain–computer interface (BCI) systems are often based on motor- and/or sensory processes that are known to be impaired in late stages of amyotrophic lateral sclerosis (ALS). We propose a novel BCI designed for patients in late stages of ALS that only requires high-level cognitive processes to transmit information from the user to the BCI. Approach. We trained subjects via EEG-based neurofeedback to self-regulate the amplitude of gamma-oscillations in the superior parietal cortex (SPC). We argue that parietal gamma-oscillations are likely to be associated with high-level attentional processes, thereby providing a communication channel that does not rely on the integrity of sensory- and/or motor-pathways impaired in late stages of ALS. Main results. Healthy subjects quickly learned to self-regulate gamma-power in the SPC by alternating between states of focused attention and relaxed wakefulness, resulting in an average decoding accuracy of 70.2%. One locked-in ALS patient (ALS-FRS-R score of zero) achieved an average decoding accuracy significantly above chance-level though insufficient for communication (55.8%). Significance. Self-regulation of gamma-power in the SPC is a feasible paradigm for brain–computer interfacing and may be preserved in late stages of ALS. This provides a novel approach to testing whether completely locked-in ALS patients retain the capacity for goal-directed thinking.

Web DOI [BibTex]

Grosse-Wentrup, M., Schölkopf, B. A Brain-Computer Interface Based on Self-Regulation of Gamma-Oscillations in the Superior Parietal Cortex Journal of Neural Engineering, 11(5):056015, 2014 (article)

Web DOI [BibTex]

On power law distributions in large-scale taxonomies

Babbar, R., Metzig, C., Partalas, I., Gaussier, E., Amini, M.

SIGKDD Explorations, Special Issue on Big Data, 16(1):47-56, 2014 (article)

[BibTex]

Babbar, R., Metzig, C., Partalas, I., Gaussier, E., Amini, M. On power law distributions in large-scale taxonomies SIGKDD Explorations, Special Issue on Big Data, 16(1):47-56, 2014 (article)

[BibTex]

Predicting Motor Learning Performance from Electroencephalographic Data

Meyer, T., Peters, J., Zander, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of NeuroEngineering and Rehabilitation, 11:24, 2014 (article)

PDF DOI [BibTex]

Meyer, T., Peters, J., Zander, T., Schölkopf, B., Grosse-Wentrup, M. Predicting Motor Learning Performance from Electroencephalographic Data Journal of NeuroEngineering and Rehabilitation, 11:24, 2014 (article)

PDF DOI [BibTex]

Special issue on autonomous grasping and manipulation

Ben Amor, H., Saxena, A., Hudson, N., Peters, J.

Autonomous Robots, 36(1-2):1-3, 2014 (article)

DOI [BibTex]

Ben Amor, H., Saxena, A., Hudson, N., Peters, J. Special issue on autonomous grasping and manipulation Autonomous Robots, 36(1-2):1-3, 2014 (article)

DOI [BibTex]

Evaluation of Positron Emission Tomographic Tracers for Imaging of Papillomavirus-Induced Tumors in Rabbits

Probst, S., Wiehr, S., Mantlik, F., Schmidt, H., Kolb, A., Münch, P., Delcuratolo, M., Stubenrauch, F., Pichler, B., Iftner, T.

Molecular Imaging, 13(1):1536-0121, 2014 (article)

Web [BibTex]

Probst, S., Wiehr, S., Mantlik, F., Schmidt, H., Kolb, A., Münch, P., Delcuratolo, M., Stubenrauch, F., Pichler, B., Iftner, T. Evaluation of Positron Emission Tomographic Tracers for Imaging of Papillomavirus-Induced Tumors in Rabbits Molecular Imaging, 13(1):1536-0121, 2014 (article)

Web [BibTex]

Extreme events in gross primary production: a characterization across continents

Zscheischler, J., Reichstein, M., Harmeling, S., Rammig, A., Tomelleri, E., Mahecha, M.

Biogeosciences, 11, pages: 2909-2924, 2014 (article)

PDF Web DOI [BibTex]

Zscheischler, J., Reichstein, M., Harmeling, S., Rammig, A., Tomelleri, E., Mahecha, M. Extreme events in gross primary production: a characterization across continents Biogeosciences, 11, pages: 2909-2924, 2014 (article)

PDF Web DOI [BibTex]

Indirect Robot Model Learning for Tracking Control

Bocsi, B., Csató, L., Peters, J.

Advanced Robotics, 28(9):589-599, 2014 (article)

PDF DOI [BibTex]

Bocsi, B., Csató, L., Peters, J. Indirect Robot Model Learning for Tracking Control Advanced Robotics, 28(9):589-599, 2014 (article)

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An extended approach for spatiotemporal gapfilling: dealing with large and systematic gaps in geoscientific datasets

v Buttlar, J., Zscheischler, J., Mahecha, M.

Nonlinear Processes in Geophysics, 21(1):203-215, 2014 (article)

PDF DOI [BibTex]

v Buttlar, J., Zscheischler, J., Mahecha, M. An extended approach for spatiotemporal gapfilling: dealing with large and systematic gaps in geoscientific datasets Nonlinear Processes in Geophysics, 21(1):203-215, 2014 (article)

PDF DOI [BibTex]

On the Quantification Accuracy, Homogeneity, and Stability of Simultaneous Positron Emission Tomography/Magnetic Resonance Imaging Systems

Schmidt, H., Schwenzer, N., Bezrukov, I., Mantlik, F., Kolb, A., Kupferschläger, J., Pichler, B.

Investigative Radiology, 49(6):373-381, 2014 (article)

Web DOI [BibTex]

Schmidt, H., Schwenzer, N., Bezrukov, I., Mantlik, F., Kolb, A., Kupferschläger, J., Pichler, B. On the Quantification Accuracy, Homogeneity, and Stability of Simultaneous Positron Emission Tomography/Magnetic Resonance Imaging Systems Investigative Radiology, 49(6):373-381, 2014 (article)

Web DOI [BibTex]

Natural Evolution Strategies

Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J., Schmidhuber, J.

Journal of Machine Learning Research, 15, pages: 949-980, 2014 (article)

PDF [BibTex]

Wierstra, D., Schaul, T., Glasmachers, T., Sun, Y., Peters, J., Schmidhuber, J. Natural Evolution Strategies Journal of Machine Learning Research, 15, pages: 949-980, 2014 (article)

PDF [BibTex]

Factors controlling decomposition rates of fine root litter in temperate forests and grasslands

Solly, E., Schöning, I., Boch, S., Kandeler, E., Marhan, S., Michalzik, B., Müller, J., Zscheischler, J., Trumbore, S., Schrumpf, M.

Plant and Soil, 2014 (article)

PDF DOI [BibTex]

Solly, E., Schöning, I., Boch, S., Kandeler, E., Marhan, S., Michalzik, B., Müller, J., Zscheischler, J., Trumbore, S., Schrumpf, M. Factors controlling decomposition rates of fine root litter in temperate forests and grasslands Plant and Soil, 2014 (article)

PDF DOI [BibTex]

Causal Discovery with Continuous Additive Noise Models

Peters, J., Mooij, J., Janzing, D., Schölkopf, B.

Journal of Machine Learning Research, 15, pages: 2009-2053, 2014 (article)

PDF Web [BibTex]

Peters, J., Mooij, J., Janzing, D., Schölkopf, B. Causal Discovery with Continuous Additive Noise Models Journal of Machine Learning Research, 15, pages: 2009-2053, 2014 (article)

PDF Web [BibTex]

A few extreme events dominate global interannual variability in gross primary production

Zscheischler, J., Mahecha, M., v Buttlar, J., Harmeling, S., Jung, M., Rammig, A., Randerson, J., Schölkopf, B., Seneviratne, S., Tomelleri, E., Zaehle, S., Reichstein, M.

Environmental Research Letters, 9(3):035001, 2014 (article)

PDF Web DOI [BibTex]

Zscheischler, J., Mahecha, M., v Buttlar, J., Harmeling, S., Jung, M., Rammig, A., Randerson, J., Schölkopf, B., Seneviratne, S., Tomelleri, E., Zaehle, S., Reichstein, M. A few extreme events dominate global interannual variability in gross primary production Environmental Research Letters, 9(3):035001, 2014 (article)

PDF Web DOI [BibTex]

Learning Strategies in Table Tennis using Inverse Reinforcement Learning

Mülling, K., Boularias, A., Mohler, B., Schölkopf, B., Peters, J.

Biological Cybernetics, 108(5):603-619, 2014 (article)

PDF DOI [BibTex]

Mülling, K., Boularias, A., Mohler, B., Schölkopf, B., Peters, J. Learning Strategies in Table Tennis using Inverse Reinforcement Learning Biological Cybernetics, 108(5):603-619, 2014 (article)

PDF DOI [BibTex]

Kernel methods in system identification, machine learning and function estimation: A survey

Pillonetto, G., Dinuzzo, F., Chen, T., De Nicolao, G., Ljung, L.

Automatica, 50(3):657-682, 2014 (article)

Web DOI [BibTex]

Pillonetto, G., Dinuzzo, F., Chen, T., De Nicolao, G., Ljung, L. Kernel methods in system identification, machine learning and function estimation: A survey Automatica, 50(3):657-682, 2014 (article)

Web DOI [BibTex]

Development of a novel depth of interaction PET detector using highly multiplexed G-APD cross-strip encoding

Kolb, A., Parl, C., Mantlik, F., Liu, C., Lorenz, E., Renker, D., Pichler, B.

Medical Physics, 41(8), 2014 (article)

Web DOI [BibTex]

Kolb, A., Parl, C., Mantlik, F., Liu, C., Lorenz, E., Renker, D., Pichler, B. Development of a novel depth of interaction PET detector using highly multiplexed G-APD cross-strip encoding Medical Physics, 41(8), 2014 (article)

Web DOI [BibTex]

Epidural electrocorticography for monitoring of arousal in locked-in state

Martens, S., Bensch, M., Halder, S., Hill, J., Nijboer, F., Ramos-Murguialday, A., Schölkopf, B., Birbaumer, N., Gharabaghi, A.

Frontiers in Human Neuroscience, 8(861), 2014 (article)

DOI [BibTex]

Martens, S., Bensch, M., Halder, S., Hill, J., Nijboer, F., Ramos-Murguialday, A., Schölkopf, B., Birbaumer, N., Gharabaghi, A. Epidural electrocorticography for monitoring of arousal in locked-in state Frontiers in Human Neuroscience, 8(861), 2014 (article)

DOI [BibTex]

Simultaneous Whole-Body PET/MR Imaging in Comparison to PET/CT in Pediatric Oncology: Initial Results

Schäfer, J. F., Gatidis, S., Schmidt, H., Gückel, B., Bezrukov, I., Pfannenberg, C. A., Reimold, M., M., E., Fuchs, J., Claussen, C. D., Schwenzer, N. F.

Radiology, 273(1):220-231, 2014 (article)

DOI [BibTex]

Schäfer, J. F., Gatidis, S., Schmidt, H., Gückel, B., Bezrukov, I., Pfannenberg, C. A., Reimold, M., M., E., Fuchs, J., Claussen, C. D., Schwenzer, N. F. Simultaneous Whole-Body PET/MR Imaging in Comparison to PET/CT in Pediatric Oncology: Initial Results Radiology, 273(1):220-231, 2014 (article)

DOI [BibTex]

Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification

Persello, C., Boularias, A., Dalponte, M., Gobakken, T., Naesset, E., Schölkopf, B.

IEEE Transactions on Geoscience and Remote Sensing, 10(52):6652 - 6664, 2014 (article)

DOI [BibTex]

Persello, C., Boularias, A., Dalponte, M., Gobakken, T., Naesset, E., Schölkopf, B. Cost-Sensitive Active Learning With Lookahead: Optimizing Field Surveys for Remote Sensing Data Classification IEEE Transactions on Geoscience and Remote Sensing, 10(52):6652 - 6664, 2014 (article)

DOI [BibTex]

Modular proximal optimization with application to total variation regularization

Barbero, A. J., Sra, S.

2014 (article) In revision

link (url) [BibTex]

Barbero, A. J., Sra, S. Modular proximal optimization with application to total variation regularization 2014 (article) In revision

link (url) [BibTex]

Principles of PET/MR Imaging

Disselhorst, J. A., Bezrukov, I., Kolb, A., Parl, C., Pichler, B. J.

Journal of Nuclear Medicine, 55(6, Supplement 2):2S-10S, 2014 (article)

DOI [BibTex]

Disselhorst, J. A., Bezrukov, I., Kolb, A., Parl, C., Pichler, B. J. Principles of PET/MR Imaging Journal of Nuclear Medicine, 55(6, Supplement 2):2S-10S, 2014 (article)

DOI [BibTex]

IM3SHAPE: Maximum likelihood galaxy shear measurement code for cosmic gravitational lensing

Zuntz, J., Kacprzak, T., Voigt, L., Hirsch, M., Rowe, B., Bridle, S.

Astrophysics Source Code Library, 1, pages: 09013, 2014 (article)

link (url) [BibTex]

Zuntz, J., Kacprzak, T., Voigt, L., Hirsch, M., Rowe, B., Bridle, S. IM3SHAPE: Maximum likelihood galaxy shear measurement code for cosmic gravitational lensing Astrophysics Source Code Library, 1, pages: 09013, 2014 (article)

link (url) [BibTex]

Efficient nearest neighbors via robust sparse hashing

Cherian, A., Sra, S., Morellas, V., Papanikolopoulos, N.

IEEE Transactions on Image Processing, 23(8):3646-3655, 2014 (article)

DOI [BibTex]

Cherian, A., Sra, S., Morellas, V., Papanikolopoulos, N. Efficient nearest neighbors via robust sparse hashing IEEE Transactions on Image Processing, 23(8):3646-3655, 2014 (article)

DOI [BibTex]

Domain adaptation-can quantity compensate for quality?

Ben-David, S., Urner, R.

Annals of Mathematics and Artificial Intelligence, 70(3):185-202, 2014 (article)

link (url) DOI [BibTex]

Ben-David, S., Urner, R. Domain adaptation-can quantity compensate for quality? Annals of Mathematics and Artificial Intelligence, 70(3):185-202, 2014 (article)

link (url) DOI [BibTex]

Sérsic galaxy models in weak lensing shape measurement: model bias, noise bias and their interaction

Kacprzak, T., Bridle, S., Rowe, B., Voigt, L., Zuntz, J., Hirsch, M., MacCrann, N.

Monthly Notices of the Royal Astronomical Society, 441(3):2528-2538, Oxford University Press, 2014 (article)

DOI [BibTex]

Kacprzak, T., Bridle, S., Rowe, B., Voigt, L., Zuntz, J., Hirsch, M., MacCrann, N. Sérsic galaxy models in weak lensing shape measurement: model bias, noise bias and their interaction Monthly Notices of the Royal Astronomical Society, 441(3):2528-2538, Oxford University Press, 2014 (article)

DOI [BibTex]

Diminished White Matter Integrity in Patients with Systemic Lupus Erythematosus

Schmidt-Wilcke, T., Cagnoli, P., Wang, P., Schultz, T., Lotz, A., Mccune, W. J., Sundgren, P. C.

NeuroImage: Clinical, 5, pages: 291-297, 2014 (article)

DOI [BibTex]

Schmidt-Wilcke, T., Cagnoli, P., Wang, P., Schultz, T., Lotz, A., Mccune, W. J., Sundgren, P. C. Diminished White Matter Integrity in Patients with Systemic Lupus Erythematosus NeuroImage: Clinical, 5, pages: 291-297, 2014 (article)

DOI [BibTex]

Information-Theoretic Bounded Rationality and ϵ-Optimality

Braun, DA, Ortega, PA

Entropy, 16(8):4662-4676, August 2014 (article)

Abstract

Bounded rationality concerns the study of decision makers with limited information processing resources. Previously, the free energy difference functional has been suggested to model bounded rational decision making, as it provides a natural trade-off between an energy or utility function that is to be optimized and information processing costs that are measured by entropic search costs. The main question of this article is how the information-theoretic free energy model relates to simple \(\epsilon\)-optimality models of bounded rational decision making, where the decision maker is satisfied with any action in an \(\epsilon\)-neighborhood of the optimal utility. We find that the stochastic policies that optimize the free energy trade-off comply with the notion of \(\epsilon\)-optimality. Moreover, this optimality criterion even holds when the environment is adversarial. We conclude that the study of bounded rationality based on \(\epsilon\)-optimality criteria that abstract away from the particulars of the information processing constraints is compatible with the information-theoretic free energy model of bounded rationality.

DOI [BibTex]

Braun, DA, Ortega, PA Information-Theoretic Bounded Rationality and ϵ-Optimality Entropy, 16(8):4662-4676, August 2014 (article)

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Occam’s Razor in sensorimotor learning

Genewein, T, Braun, D

Proceedings of the Royal Society of London B, 281(1783):1-7, May 2014 (article)

Abstract

A large number of recent studies suggest that the sensorimotor system uses probabilistic models to predict its environment and makes inferences about unobserved variables in line with Bayesian statistics. One of the important features of Bayesian statistics is Occam's Razor—an inbuilt preference for simpler models when comparing competing models that explain some observed data equally well. Here, we test directly for Occam's Razor in sensorimotor control. We designed a sensorimotor task in which participants had to draw lines through clouds of noisy samples of an unobserved curve generated by one of two possible probabilistic models—a simple model with a large length scale, leading to smooth curves, and a complex model with a short length scale, leading to more wiggly curves. In training trials, participants were informed about the model that generated the stimulus so that they could learn the statistics of each model. In probe trials, participants were then exposed to ambiguous stimuli. In probe trials where the ambiguous stimulus could be fitted equally well by both models, we found that participants showed a clear preference for the simpler model. Moreover, we found that participants’ choice behaviour was quantitatively consistent with Bayesian Occam's Razor. We also show that participants’ drawn trajectories were similar to samples from the Bayesian predictive distribution over trajectories and significantly different from two non-probabilistic heuristics. In two control experiments, we show that the preference of the simpler model cannot be simply explained by a difference in physical effort or by a preference for curve smoothness. Our results suggest that Occam's Razor is a general behavioural principle already present during sensorimotor processing.

DOI [BibTex]

Genewein, T, Braun, D Occam’s Razor in sensorimotor learning Proceedings of the Royal Society of London B, 281(1783):1-7, May 2014 (article)

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Generalized Thompson sampling for sequential decision-making and causal inference

Ortega, PA, Braun, DA

Complex Adaptive Systems Modeling, 2(2):1-23, March 2014 (article)

Abstract

Purpose Sampling an action according to the probability that the action is believed to be the optimal one is sometimes called Thompson sampling. Methods Although mostly applied to bandit problems, Thompson sampling can also be used to solve sequential adaptive control problems, when the optimal policy is known for each possible environment. The predictive distribution over actions can then be constructed by a Bayesian superposition of the policies weighted by their posterior probability of being optimal. Results Here we discuss two important features of this approach. First, we show in how far such generalized Thompson sampling can be regarded as an optimal strategy under limited information processing capabilities that constrain the sampling complexity of the decision-making process. Second, we show how such Thompson sampling can be extended to solve causal inference problems when interacting with an environment in a sequential fashion. Conclusion In summary, our results suggest that Thompson sampling might not merely be a useful heuristic, but a principled method to address problems of adaptive sequential decision-making and causal inference.

DOI [BibTex]

Ortega, PA, Braun, DA Generalized Thompson sampling for sequential decision-making and causal inference Complex Adaptive Systems Modeling, 2(2):1-23, March 2014 (article)

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Assessing randomness and complexity in human motion trajectories through analysis of symbolic sequences

Peng, Z, Genewein, T, Braun, DA

Frontiers in Human Neuroscience, 8(168):1-13, March 2014 (article)

Abstract

Complexity is a hallmark of intelligent behavior consisting both of regular patterns and random variation. To quantitatively assess the complexity and randomness of human motion, we designed a motor task in which we translated subjects' motion trajectories into strings of symbol sequences. In the first part of the experiment participants were asked to perform self-paced movements to create repetitive patterns, copy pre-specified letter sequences, and generate random movements. To investigate whether the degree of randomness can be manipulated, in the second part of the experiment participants were asked to perform unpredictable movements in the context of a pursuit game, where they received feedback from an online Bayesian predictor guessing their next move. We analyzed symbol sequences representing subjects' motion trajectories with five common complexity measures: predictability, compressibility, approximate entropy, Lempel-Ziv complexity, as well as effective measure complexity. We found that subjects’ self-created patterns were the most complex, followed by drawing movements of letters and self-paced random motion. We also found that participants could change the randomness of their behavior depending on context and feedback. Our results suggest that humans can adjust both complexity and regularity in different movement types and contexts and that this can be assessed with information-theoretic measures of the symbolic sequences generated from movement trajectories.

DOI [BibTex]

Peng, Z, Genewein, T, Braun, DA Assessing randomness and complexity in human motion trajectories through analysis of symbolic sequences Frontiers in Human Neuroscience, 8(168):1-13, March 2014 (article)

DOI [BibTex]

2011

Causal Inference on Discrete Data using Additive Noise Models

Peters, J., Janzing, D., Schölkopf, B.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(12):2436-2450, December 2011 (article)

Abstract

Inferring the causal structure of a set of random variables from a finite sample of the joint distribution is an important problem in science. The case of two random variables is particularly challenging since no (conditional) independences can be exploited. Recent methods that are based on additive noise models suggest the following principle: Whenever the joint distribution {\bf P}^{(X,Y)} admits such a model in one direction, e.g., Y=f(X)+N, N \perp\kern-6pt \perp X, but does not admit the reversed model X=g(Y)+\tilde{N}, \tilde{N} \perp\kern-6pt \perp Y, one infers the former direction to be causal (i.e., X\rightarrow Y). Up to now, these approaches only dealt with continuous variables. In many situations, however, the variables of interest are discrete or even have only finitely many states. In this work, we extend the notion of additive noise models to these cases. We prove that it almost never occurs that additive noise models can be fit in both directions. We further propose an efficient algorithm that is able to perform this way of causal inference on finite samples of discrete variables. We show that the algorithm works on both synthetic and real data sets.

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2011

Peters, J., Janzing, D., Schölkopf, B. Causal Inference on Discrete Data using Additive Noise Models IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(12):2436-2450, December 2011 (article)

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Spontaneous epigenetic variation in the Arabidopsis thaliana methylome

Becker, C., Hagmann, J., Müller, J., Koenig, D., Stegle, O., Borgwardt, K., Weigel, D.

Nature, 480(7376):245-249, December 2011 (article)

Abstract

Heritable epigenetic polymorphisms, such as differential cytosine methylation, can underlie phenotypic variation1, 2. Moreover, wild strains of the plant Arabidopsis thaliana differ in many epialleles3, 4, and these can influence the expression of nearby genes1, 2. However, to understand their role in evolution5, it is imperative to ascertain the emergence rate and stability of epialleles, including those that are not due to structural variation. We have compared genome-wide DNA methylation among 10 A. thaliana lines, derived 30 generations ago from a common ancestor6. Epimutations at individual positions were easily detected, and close to 30,000 cytosines in each strain were differentially methylated. In contrast, larger regions of contiguous methylation were much more stable, and the frequency of changes was in the same low range as that of DNA mutations7. Like individual positions, the same regions were often affected by differential methylation in independent lines, with evidence for recurrent cycles of forward and reverse mutations. Transposable elements and short interfering RNAs have been causally linked to DNA methylation8. In agreement, differentially methylated sites were farther from transposable elements and showed less association with short interfering RNA expression than invariant positions. The biased distribution and frequent reversion of epimutations have important implications for the potential contribution of sequence-independent epialleles to plant evolution.

Web DOI [BibTex]

Becker, C., Hagmann, J., Müller, J., Koenig, D., Stegle, O., Borgwardt, K., Weigel, D. Spontaneous epigenetic variation in the Arabidopsis thaliana methylome Nature, 480(7376):245-249, December 2011 (article)

Web DOI [BibTex]

HHfrag: HMM-based fragment detection using HHpred

Kalev, I., Habeck, M.

Bioinformatics, 27(22):3110-3116, November 2011 (article)

Abstract

Motivation: Over the last decade, both static and dynamic fragment libraries for protein structure prediction have been introduced. The former are built from clusters in either sequence or structure space and aim to extract a universal structural alphabet. The latter are tailored for a particular query protein sequence and aim to provide local structural templates that need to be assembled in order to build the full-length structure. Results: Here, we introduce HHfrag, a dynamic HMM-based fragment search method built on the profile–profile comparison tool HHpred. We show that HHfrag provides advantages over existing fragment assignment methods in that it: (i) improves the precision of the fragments at the expense of a minor loss in sequence coverage; (ii) detects fragments of variable length (6–21 amino acid residues); (iii) allows for gapped fragments and (iv) does not assign fragments to regions where there is no clear sequence conservation. We illustrate the usefulness of fragments detected by HHfrag on targets from most recent CASP.

Web DOI [BibTex]

Kalev, I., Habeck, M. HHfrag: HMM-based fragment detection using HHpred Bioinformatics, 27(22):3110-3116, November 2011 (article)

Web DOI [BibTex]

Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning

Hachiya, H., Peters, J., Sugiyama, M.

Neural Computation, 23(11):2798-2832, November 2011 (article)

Abstract

Direct policy search is a promising reinforcement learning framework, in particular for controlling continuous, high-dimensional systems. Policy search often requires a large number of samples for obtaining a stable policy update estimator, and this is prohibitive when the sampling cost is expensive. In this letter, we extend an expectation-maximization-based policy search method so that previously collected samples can be efficiently reused. The usefulness of the proposed method, reward-weighted regression with sample reuse (R), is demonstrated through robot learning experiments.

Web DOI [BibTex]

Hachiya, H., Peters, J., Sugiyama, M. Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning Neural Computation, 23(11):2798-2832, November 2011 (article)

Web DOI [BibTex]

Model Learning in Robotics: a Survey

Nguyen-Tuong, D., Peters, J.

Cognitive Processing, 12(4):319-340, November 2011 (article)

Abstract

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the in uence of an agent on this environment. In the context of model based learning control, we view the model from three different perspectives. First, we need to study the dierent possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.

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Nguyen-Tuong, D., Peters, J. Model Learning in Robotics: a Survey Cognitive Processing, 12(4):319-340, November 2011 (article)

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FaST linear mixed models for genome-wide association studies

Lippert, C., Listgarten, J., Liu, Y., Kadie, CM., Davidson, RI., Heckerman, D.

Nature Methods, 8(10):833–835, October 2011 (article)

Abstract

We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).

PDF DOI [BibTex]

Lippert, C., Listgarten, J., Liu, Y., Kadie, CM., Davidson, RI., Heckerman, D. FaST linear mixed models for genome-wide association studies Nature Methods, 8(10):833–835, October 2011 (article)

PDF DOI [BibTex]

The effect of noise correlations in populations of diversely tuned neurons

Ecker, A., Berens, P., Tolias, A., Bethge, M.

Journal of Neuroscience, 31(40):14272-14283, October 2011 (article)

Abstract

The amount of information encoded by networks of neurons critically depends on the correlation structure of their activity. Neurons with similar stimulus preferences tend to have higher noise correlations than others. In homogeneous populations of neurons, this limited range correlation structure is highly detrimental to the accuracy of a population code. Therefore, reduced spike count correlations under attention, after adaptation, or after learning have been interpreted as evidence for a more efficient population code. Here, we analyze the role of limited range correlations in more realistic, heterogeneous population models. We use Fisher information and maximum-likelihood decoding to show that reduced correlations do not necessarily improve encoding accuracy. In fact, in populations with more than a few hundred neurons, increasing the level of limited range correlations can substantially improve encoding accuracy. We found that this improvement results from a decrease in noise entropy that is associated with increasing correlations if the marginal distributions are unchanged. Surprisingly, for constant noise entropy and in the limit of large populations, the encoding accuracy is independent of both structure and magnitude of noise correlations.

Web DOI [BibTex]

Ecker, A., Berens, P., Tolias, A., Bethge, M. The effect of noise correlations in populations of diversely tuned neurons Journal of Neuroscience, 31(40):14272-14283, October 2011 (article)

Web DOI [BibTex]

Analysis of Fixed-Point and Coordinate Descent Algorithms for Regularized Kernel Methods

Dinuzzo, F.

IEEE Transactions on Neural Networks, 22(10):1576-1587, October 2011 (article)

Abstract

In this paper, we analyze the convergence of two general classes of optimization algorithms for regularized kernel methods with convex loss function and quadratic norm regularization. The first methodology is a new class of algorithms based on fixed-point iterations that are well-suited for a parallel implementation and can be used with any convex loss function. The second methodology is based on coordinate descent, and generalizes some techniques previously proposed for linear support vector machines. It exploits the structure of additively separable loss functions to compute solutions of line searches in closed form. The two methodologies are both very easy to implement. In this paper, we also show how to remove non-differentiability of the objective functional by exactly reformulating a convex regularization problem as an unconstrained differentiable stabilization problem.

Web DOI [BibTex]

Dinuzzo, F. Analysis of Fixed-Point and Coordinate Descent Algorithms for Regularized Kernel Methods IEEE Transactions on Neural Networks, 22(10):1576-1587, October 2011 (article)

Web DOI [BibTex]

A biomimetic approach to robot table tennis

Mülling, K., Kober, J., Peters, J.

Adaptive Behavior , 19(5):359-376 , October 2011 (article)

Abstract

Playing table tennis is a difficult motor task that requires fast movements, accurate control and adaptation to task parameters. Although human beings see and move slower than most robot systems, they significantly outperform all table tennis robots. One important reason for this higher performance is the human movement generation. In this paper, we study human movements during table tennis and present a robot system that mimics human striking behavior. Our focus lies on generating hitting motions capable of adapting to variations in environmental conditions, such as changes in ball speed and position. Therefore, we model the human movements involved in hitting a table tennis ball using discrete movement stages and the virtual hitting point hypothesis. The resulting model was evaluated both in a physically realistic simulation and on a real anthropomorphic seven degrees of freedom Barrett WAM™ robot arm.

PDF Web DOI [BibTex]

Mülling, K., Kober, J., Peters, J. A biomimetic approach to robot table tennis Adaptive Behavior , 19(5):359-376 , October 2011 (article)

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Whole-genome sequencing of multiple Arabidopsis thaliana populations

Nature Genetics, 43(10):956–963, October 2011 (article)

Abstract

The plant Arabidopsis thaliana occurs naturally in many different habitats throughout Eurasia. As a foundation for identifying genetic variation contributing to adaptation to diverse environments, a 1001 Genomes Project to sequence geographically diverse A. thaliana strains has been initiated. Here we present the first phase of this project, based on population-scale sequencing of 80 strains drawn from eight regions throughout the species' native range. We describe the majority of common small-scale polymorphisms as well as many larger insertions and deletions in the A. thaliana pan-genome, their effects on gene function, and the patterns of local and global linkage among these variants. The action of processes other than spontaneous mutation is identified by comparing the spectrum of mutations that have accumulated since A. thaliana diverged from its closest relative 10 million years ago with the spectrum observed in the laboratory. Recent species-wide selective sweeps are rare, and potentially deleterious mutations are more common in marginal populations.

Web DOI [BibTex]

Cao, J., Schneeberger, K., Ossowski, S., Günther, T., Bender, S., Fitz, J., Koenig, D., Lanz, C., Stegle, O., Lippert, C., Wang, X., Ott, F., Müller, J., Alonso-Blanco, C., Borgwardt, K., Schmid, K., Weigel, D. Whole-genome sequencing of multiple Arabidopsis thaliana populations Nature Genetics, 43(10):956–963, October 2011 (article)

Web DOI [BibTex]

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