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    NIPS
    2004
    88views Information Technology» more  NIPS 2004»
    Spike Sorting: Bayesian Clustering of Non-Stationary Data
    14 years 28 days ago
    Spike Sorting: Bayesian Clustering of Non-Stationary Data
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    Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
    Aharon Bar-Hillel, Adam Spiro, Eran Stark
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    NIPS
    2004
    241views Information Technology» more  NIPS 2004»
    The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
    14 years 28 days ago
    The Correlated Correspondence Algorithm for Unsupervised Registration of Nonrigid Surfaces
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    We present an unsupervised algorithm for registering 3D surface scans of an object undergoing significant deformations. Our algorithm does not need markers, nor does it assume pri...
    Dragomir Anguelov, Praveen Srinivasan, Hoi-Cheung ...
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    NIPS
    2004
    199views Information Technology» more  NIPS 2004»
    Computing regularization paths for learning multiple kernels
    14 years 28 days ago
    Computing regularization paths for learning multiple kernels
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    The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
    Francis R. Bach, Romain Thibaux, Michael I. Jordan
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    NIPS
    2004
    196views Information Technology» more  NIPS 2004»
    Blind One-microphone Speech Separation: A Spectral Learning Approach
    14 years 28 days ago
    Blind One-microphone Speech Separation: A Spectral Learning Approach
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    We present an algorithm to perform blind, one-microphone speech separation. Our algorithm separates mixtures of speech without modeling individual speakers. Instead, we formulate ...
    Francis R. Bach, Michael I. Jordan
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    NIPS
    2004
    220views Information Technology» more  NIPS 2004»
    The power of feature clustering: An application to object detection
    14 years 28 days ago
    The power of feature clustering: An application to object detection
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    We give a fast rejection scheme that is based on image segments and demonstrate it on the canonical example of face detection. However, instead of focusing on the detection step w...
    Shai Avidan, Moshe Butman
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    NIPS
    2004
    133views Information Technology» more  NIPS 2004»
    Comparing Beliefs, Surveys, and Random Walks
    14 years 28 days ago
    Comparing Beliefs, Surveys, and Random Walks
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    Survey propagation is a powerful technique from statistical physics that has been applied to solve the 3-SAT problem both in principle and in practice. We give, using only probabi...
    Erik Aurell, Uri Gordon, Scott Kirkpatrick
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    NIPS
    2004
    105views Information Technology» more  NIPS 2004»
    Harmonising Chorales by Probabilistic Inference
    14 years 28 days ago
    Harmonising Chorales by Probabilistic Inference
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    We describe how we used a data set of chorale harmonisations composed by Johann Sebastian Bach to train Hidden Markov Models. Using a probabilistic framework allows us to create a...
    Moray Allan, Christopher K. I. Williams
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    NIPS
    2004
    128views Information Technology» more  NIPS 2004»
    Learning Preferences for Multiclass Problems
    14 years 28 days ago
    Learning Preferences for Multiclass Problems
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    Many interesting multiclass problems can be cast in the general framework of label ranking defined on a given set of classes. The evaluation for such a ranking is generally given ...
    Fabio Aiolli, Alessandro Sperduti
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    NIPS
    2004
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    A Large Deviation Bound for the Area Under the ROC Curve
    14 years 28 days ago
    A Large Deviation Bound for the Area Under the ROC Curve
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    The area under the ROC curve (AUC) has been advocated as an evaluation criterion for the bipartite ranking problem. We study large deviation properties of the AUC; in particular, ...
    Shivani Agarwal, Thore Graepel, Ralf Herbrich, Dan...
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    NIPS
    2004
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    Support Vector Classification with Input Data Uncertainty
    14 years 28 days ago
    Support Vector Classification with Input Data Uncertainty
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    This paper investigates a new learning model in which the input data is corrupted with noise. We present a general statistical framework to tackle this problem. Based on the stati...
    Jinbo Bi, Tong Zhang
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