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    NIPS
    2007
    131views Information Technology» more  NIPS 2007»
    Measuring Neural Synchrony by Message Passing
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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
    14 years 1 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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