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    NIPS
    1998
    100views Information Technology» more  NIPS 1998»
    Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks
    14 years 26 days ago
    Almost Linear VC Dimension Bounds for Piecewise Polynomial Networks
    Download  webee.technion.ac.il
    Peter L. Bartlett, Vitaly Maiorov, Ron Meir
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    NIPS
    1998
    154views Information Technology» more  NIPS 1998»
    Semi-Supervised Support Vector Machines
    14 years 26 days ago
    Semi-Supervised Support Vector Machines
    Download  www1.cs.columbia.edu
    We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
    Kristin P. Bennett, Ayhan Demiriz
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    NIPS
    1998
    129views Information Technology» more  NIPS 1998»
    Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
    14 years 26 days ago
    Probabilistic Modeling for Face Orientation Discrimination: Learning from Labeled and Unlabeled Data
    Download  www.ri.cmu.edu
    This paper presents probabilistic modeling methods to solve the problem of discriminating between five facial orientations with very little labeled data. Three models are explored...
    Shumeet Baluja
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    NIPS
    1998
    164views Information Technology» more  NIPS 1998»
    Making Templates Rotationally Invariant. An Application to Rotated Digit Recognition
    14 years 26 days ago
    Making Templates Rotationally Invariant. An Application to Rotated Digit Recognition
    Download  www.ri.cmu.edu
    This paper describes a simple and efficient method to make template-based object classification invariant to in-plane rotations. The task is divided into two parts: orientation di...
    Shumeet Baluja
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    NIPS
    1998
    140views Information Technology» more  NIPS 1998»
    Gradient Descent for General Reinforcement Learning
    14 years 26 days ago
    Gradient Descent for General Reinforcement Learning
    Download  www.ri.cmu.edu
    A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
    Leemon C. Baird III, Andrew W. Moore
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