Publications | Empirical Inference - Max Planck Institute for Intelligent Systems

121 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)

PDF DOI [BibTex]

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)

DOI [BibTex]

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]

2012

Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices

Cherian, A., Sra, S., Banerjee, A., Papanikolopoulos, N.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2161-2174, December 2012 (article)

DOI [BibTex]

2012

Cherian, A., Sra, S., Banerjee, A., Papanikolopoulos, N. Jensen-Bregman LogDet Divergence with Application to Efficient Similarity Search for Covariance Matrices IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2161-2174, December 2012 (article)

DOI [BibTex]

Hippocampal-Cortical Interaction during Periods of Subcortical Silence

Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A.

Nature, 491, pages: 547-553, November 2012 (article)

Abstract

Hippocampal ripples, episodic high-frequency field-potential oscillations primarily occurring during sleep and calmness, have been described in mice, rats, rabbits, monkeys and humans, and so far they have been associated with retention of previously acquired awake experience. Although hippocampal ripples have been studied in detail using neurophysiological methods, the global effects of ripples on the entire brain remain elusive, primarily owing to a lack of methodologies permitting concurrent hippocampal recordings and whole-brain activity mapping. By combining electrophysiological recordings in hippocampus with ripple-triggered functional magnetic resonance imaging, here we show that most of the cerebral cortex is selectively activated during the ripples, whereas most diencephalic, midbrain and brainstem regions are strongly and consistently inhibited. Analysis of regional temporal response patterns indicates that thalamic activity suppression precedes the hippocampal population burst, which itself is temporally bounded by massive activations of association and primary cortical areas. These findings suggest that during off-line memory consolidation, synergistic thalamocortical activity may be orchestrating a privileged interaction state between hippocampus and cortex by silencing the output of subcortical centres involved in sensory processing or potentially mediating procedural learning. Such a mechanism would cause minimal interference, enabling consolidation of hippocampus-dependent memory.

Web DOI [BibTex]

Logothetis, N., Eschenko, O., Murayama, Y., Augath, M., Steudel, T., Evrard, H., Besserve, M., Oeltermann, A. Hippocampal-Cortical Interaction during Periods of Subcortical Silence Nature, 491, pages: 547-553, November 2012 (article)

Web DOI [BibTex]

Thermodynamic limits of dynamic cooling

Allahverdyan, A., Hovhannisyan, K., Janzing, D., Mahler, G.

Physical Review E, 84(4):16, October 2012 (article)

Abstract

We study dynamic cooling, where an externally driven two-level system is cooled via reservoir, a quantum system with initial canonical equilibrium state. We obtain explicitly the minimal possible temperature Tmin>0 reachable for the two-level system. The minimization goes over all unitary dynamic processes operating on the system and reservoir and over the reservoir energy spectrum. The minimal work needed to reach Tmin grows as 1/Tmin. This work cost can be significantly reduced, though, if one is satisfied by temperatures slightly above Tmin. Our results on Tmin>0 prove unattainability of the absolute zero temperature without ambiguities that surround its derivation from the entropic version of the third law. We also study cooling via a reservoir consisting of N≫1 identical spins. Here we show that Tmin∝1/N and find the maximal cooling compatible with the minimal work determined by the free energy. Finally we discuss cooling by reservoir with an initially microcanonic state and show that although a purely microcanonic state can yield the zero temperature, the unattainability is recovered when taking into account imperfections in preparing the microcanonic state.

Web DOI [BibTex]

Allahverdyan, A., Hovhannisyan, K., Janzing, D., Mahler, G. Thermodynamic limits of dynamic cooling Physical Review E, 84(4):16, October 2012 (article)

Web DOI [BibTex]

GLIDE: GPU-Based Linear Regression for Detection of Epistasis

Kam-Thong, T., Azencott, C., Cayton, L., Pütz, B., Altmann, A., Karbalai, N., Sämann, P., Schölkopf, B., Müller-Myhsok, B., Borgwardt, K.

Human Heredity, 73(4):220-236, September 2012 (article)

Abstract

Due to recent advances in genotyping technologies, mapping phenotypes to single loci in the genome has become a standard technique in statistical genetics. However, one-locus mapping fails to explain much of the phenotypic variance in complex traits. Here, we present GLIDE, which maps phenotypes to pairs of genetic loci and systematically searches for the epistatic interactions expected to reveal part of this missing heritability. GLIDE makes use of the computational power of consumer-grade graphics cards to detect such interactions via linear regression. This enabled us to conduct a systematic two-locus mapping study on seven disease data sets from the Wellcome Trust Case Control Consortium and on in-house hippocampal volume data in 6 h per data set, while current single CPU-based approaches require more than a year’s time to complete the same task.

Web [BibTex]

Kam-Thong, T., Azencott, C., Cayton, L., Pütz, B., Altmann, A., Karbalai, N., Sämann, P., Schölkopf, B., Müller-Myhsok, B., Borgwardt, K. GLIDE: GPU-Based Linear Regression for Detection of Epistasis Human Heredity, 73(4):220-236, September 2012 (article)

Web [BibTex]

Fast projection onto mixed-norm balls with applications

Sra, S.

Minining and Knowledge Discovery (DMKD), 25(2):358-377, September 2012 (article)

DOI [BibTex]

Sra, S. Fast projection onto mixed-norm balls with applications Minining and Knowledge Discovery (DMKD), 25(2):358-377, September 2012 (article)

DOI [BibTex]

Bayesian estimation of free energies from equilibrium simulations

Habeck, M.

Physical Review Letters, 109(10):5, September 2012 (article)

Abstract

Free energy calculations are an important tool in statistical physics and biomolecular simulation. This Letter outlines a Bayesian method to estimate free energies from equilibrium Monte Carlo simulations. A Gibbs sampler is developed that allows efficient sampling of free energies and the density of states. The Gibbs sampling output can be used to estimate expected free energy differences and their uncertainties. The probabilistic formulation offers a unifying framework for existing methods such as the weighted histogram analysis method and the multistate Bennett acceptance ratio; both are shown to be approximate versions of the full probabilistic treatment.

Web DOI [BibTex]

Habeck, M. Bayesian estimation of free energies from equilibrium simulations Physical Review Letters, 109(10):5, September 2012 (article)

Web DOI [BibTex]

PAC-Bayesian Inequalities for Martingales

Seldin, Y., Laviolette, F., Cesa-Bianchi, N., Shawe-Taylor, J., Auer, P.

IEEE Transactions on Information Theory, 58(12):7086-7093, June 2012 (article)

Abstract

We present a set of high-probability inequalities that control the concentration of weighted averages of multiple (possibly uncountably many) simultaneously evolving and interdependent martingales. We also present a comparison inequality that bounds expectation of a convex function of martingale difference type variables by expectation of the same function of independent Bernoulli variables. This inequality is applied to derive a tighter analog of Hoeffding-Azuma inequality.

PDF Web DOI [BibTex]

Seldin, Y., Laviolette, F., Cesa-Bianchi, N., Shawe-Taylor, J., Auer, P. PAC-Bayesian Inequalities for Martingales IEEE Transactions on Information Theory, 58(12):7086-7093, June 2012 (article)

PDF Web DOI [BibTex]

Entropy Search for Information-Efficient Global Optimization

Hennig, P., Schuler, C.

Journal of Machine Learning Research, 13, pages: 1809-1837, -, June 2012 (article)

Abstract

Contemporary global optimization algorithms are based on local measures of utility, rather than a probability measure over location and value of the optimum. They thus attempt to collect low function values, not to learn about the optimum. The reason for the absence of probabilistic global optimizers is that the corresponding inference problem is intractable in several ways. This paper develops desiderata for probabilistic optimization algorithms, then presents a concrete algorithm which addresses each of the computational intractabilities with a sequence of approximations and explicitly adresses the decision problem of maximizing information gain from each evaluation.

PDF Web Project Page [BibTex]

Hennig, P., Schuler, C. Entropy Search for Information-Efficient Global Optimization Journal of Machine Learning Research, 13, pages: 1809-1837, -, June 2012 (article)

PDF Web Project Page [BibTex]

A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

Nere, A., Olcese, U., Balduzzi, D., Tononi, G.

PLoS ONE, 7(5):17, May 2012 (article)

Abstract

In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips.

PDF Web DOI [BibTex]

Nere, A., Olcese, U., Balduzzi, D., Tononi, G. A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP PLoS ONE, 7(5):17, May 2012 (article)

PDF Web DOI [BibTex]

Online Kernel-based Learning for Task-Space Tracking Robot Control

Nguyen-Tuong, D., Peters, J.

IEEE Transactions on Neural Networks and Learning Systems, 23(9):1417-1425, May 2012 (article)

Abstract

Abstract—Task-space control of redundant robot systems based on analytical models is known to be susceptive to modeling errors. Here, data driven model learning methods may present an interesting alternative approach. However, learning models for task-space tracking control from sampled data is an illposed problem. In particular, the same input data point can yield many different output values, which can form a non-convex solution space. Because the problem is ill-posed, models cannot be learned from such data using common regression methods. While learning of task-space control mappings is globally illposed, it has been shown in recent work that it is locally a well-defined problem. In this paper, we use this insight to formulate a local, kernel-based learning approach for online model learning for task-space tracking control. We propose a parametrization for the local model which makes an application in task-space tracking control of redundant robots possible. The model parametrization further allows us to apply the kerneltrick and, therefore, enables a formulation within the kernel learning framework. For evaluations, we show the ability of the method for online model learning for task-space tracking control of redundant robots.

PDF DOI [BibTex]

Nguyen-Tuong, D., Peters, J. Online Kernel-based Learning for Task-Space Tracking Robot Control IEEE Transactions on Neural Networks and Learning Systems, 23(9):1417-1425, May 2012 (article)

PDF DOI [BibTex]

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