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    NIPS
    2007
    131views Information Technology» more  NIPS 2007»
    Measuring Neural Synchrony by Message Passing
    13 years 11 months ago
    Measuring Neural Synchrony by Message Passing
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    A novel approach to measure the interdependence of two time series is proposed, referred to as “stochastic event synchrony” (SES); it quantifies the alignment of two point pr...
    Justin Dauwels, François B. Vialatte, Tomas...
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    NIPS
    2007
    134views Information Technology» more  NIPS 2007»
    Convex Clustering with Exemplar-Based Models
    13 years 11 months ago
    Convex Clustering with Exemplar-Based Models
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    Clustering is often formulated as the maximum likelihood estimation of a mixture model that explains the data. The EM algorithm widely used to solve the resulting optimization pro...
    Danial Lashkari, Polina Golland
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    NIPS
    2007
    136views Information Technology» more  NIPS 2007»
    Boosting the Area under the ROC Curve
    13 years 11 months ago
    Boosting the Area under the ROC Curve
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    We show that any weak ranker that can achieve an area under the ROC curve slightly better than 1/2 (which can be achieved by random guessing) can be effi
    Philip M. Long, Rocco A. Servedio
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    NIPS
    2007
    161views Information Technology» more  NIPS 2007»
    The discriminant center-surround hypothesis for bottom-up saliency
    13 years 11 months ago
    The discriminant center-surround hypothesis for bottom-up saliency
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    The classical hypothesis, that bottom-up saliency is a center-surround process, is combined with a more recent hypothesis that all saliency decisions are optimal in a decision-the...
    Dashan Gao, Vijay Mahadevan, Nuno Vasconcelos
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    NIPS
    2007
    140views Information Technology» more  NIPS 2007»
    Learning with Tree-Averaged Densities and Distributions
    13 years 11 months ago
    Learning with Tree-Averaged Densities and Distributions
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    We utilize the ensemble of trees framework, a tractable mixture over superexponential number of tree-structured distributions [1], to develop a new model for multivariate density ...
    Sergey Kirshner
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    NIPS
    2007
    171views Information Technology» more  NIPS 2007»
    Continuous Time Particle Filtering for fMRI
    13 years 11 months ago
    Continuous Time Particle Filtering for fMRI
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    We construct a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed Blood Oxygen Level Dependent (BOLD) signal in Fu...
    Lawrence Murray, Amos J. Storkey
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    NIPS
    2007
    136views Information Technology» more  NIPS 2007»
    Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
    13 years 11 months ago
    Augmented Functional Time Series Representation and Forecasting with Gaussian Processes
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    We introduce a functional representation of time series which allows forecasts to be performed over an unspecified horizon with progressively-revealed information sets. By virtue...
    Nicolas Chapados, Yoshua Bengio
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    NIPS
    2007
    129views Information Technology» more  NIPS 2007»
    Cluster Stability for Finite Samples
    13 years 11 months ago
    Cluster Stability for Finite Samples
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    Over the past few years, the notion of stability in data clustering has received growing attention as a cluster validation criterion in a sample-based framework. However, recent w...
    Ohad Shamir, Naftali Tishby
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    NIPS
    2007
    167views Information Technology» more  NIPS 2007»
    A General Boosting Method and its Application to Learning Ranking Functions for Web Search
    13 years 11 months ago
    A General Boosting Method and its Application to Learning Ranking Functions for Web Search
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    We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach...
    Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier C...
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    NIPS
    2007
    190views Information Technology» more  NIPS 2007»
    Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
    13 years 11 months ago
    Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
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    Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
    Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
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