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Browsing CBCL Memos (1993 - 2004) by Title

Research and Teaching Output of the MIT Community

Browsing CBCL Memos (1993 - 2004) by Title

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  • Heisele, Bernd; Poggio, Tomaso; Pontil, Massimiliano (2000-05-01)
    We present a trainable system for detecting frontal and near-frontal views of faces in still gray images using Support Vector Machines (SVMs). We first consider the problem of detecting the whole face pattern by a single ...
  • Riesenhuber; Jarudi; Gilad; Sinha (2004-03-05)
    Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone ...
  • Rosen, Ezra (2003-06-05)
    The face inversion effect has been widely documented as an effect of the uniqueness of face processing. Using a computational model, we show that the face inversion effect is a byproduct of expertise with respect to the ...
  • Ghahramani, Zoubin; Jordan, Michael I. (1996-02-09)
    We present a framework for learning in hidden Markov models with distributed state representations. Within this framework, we derive a learning algorithm based on the Expectation--Maximization (EM) procedure for maximum ...
  • Jaakkola, Tommi S.; Saul, Lawrence K.; Jordan, Michael I. (1996-02-09)
    Sigmoid type belief networks, a class of probabilistic neural networks, provide a natural framework for compactly representing probabilistic information in a variety of unsupervised and supervised learning problems. ...
  • Betke, Margrit; Makris, Nicholas (1995-01-25)
    A fast simulated annealing algorithm is developed for automatic object recognition. The normalized correlation coefficient is used as a measure of the match between a hypothesized object and an image. Templates are ...
  • Serre, Thomas; Heisele, Bernd; Mukherjee, Sayan; Poggio, Tomaso (2000-09-01)
    We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of ...
  • Miyano, Takaya; Girosi, Federico (1994-08-01)
    Global temperature variations between 1861 and 1984 are forecast usingsregularization networks, multilayer perceptrons and linearsautoregression. The regularization network, optimized by stochasticsgradient descent associated ...
  • Sung, Kah Kay; Niyogi, Partha (1996-06-06)
    We discuss a formulation for active example selection for function learning problems. This formulation is obtained by adapting Fedorov's optimal experiment design to the learning problem. We specifically show how to ...
  • Pontil, Massimiliano; Rifkin, Ryan; Evgeniou, Theodoros (1998-11-01)
    We study the relation between support vector machines (SVMs) for regression (SVMR) and SVM for classification (SVMC). We show that for a given SVMC solution there exists a SVMR solution which is equivalent for a certain ...
  • Riesenhuber, Maximilian (2001-12-10)
    Baylis & Driver (Nature Neuroscience, 2001) have recently presented data on the response of neurons in macaque inferotemporal cortex (IT) to various stimulus transformations. They report that neurons can generalize over ...
  • Shashua, Amnon (1993-07-01)
    We investigate the differences --- conceptually and algorithmically --- between affine and projective frameworks for the tasks of visual recognition and reconstruction from perspective views. It is shown that an affine ...
  • Shadmehr, Reza; Mussa-Ivaldi, Ferdinando (1993-07-01)
    The objects with which the hand interacts with may significantly change the dynamics of the arm. How does the brain adapt control of arm movements to this new dynamic? We show that adaptation is via composition of a ...
  • Torralba, Antonio; Oliva, Aude (2001-12-01)
    In the absence of cues for absolute depth measurements as binocular disparity, motion, or defocus, the absolute distance between the observer and a scene cannot be measured. The interpretation of shading, edges and junctions ...
  • Jordan, Michael I.; Jacobs, Robert A. (1993-08-01)
    We present a tree-structured architecture for supervised learning. The statistical model underlying the architecture is a hierarchical mixture model in which both the mixture coefficients and the mixture components are ...
  • Buelthoff, Heinrich H.; Edelman, Shimon Y.; Tarr, Michael J. (1994-04-01)
    We discuss a variety of object recognition experiments in which human subjects were presented with realistically rendered images of computer-generated three-dimensional objects, with tight control over stimulus shape, ...
  • Evgeniou, Theodoros (1996-11-01)
    This paper presents an image-based rendering system using algebraic relations between different views of an object. The system uses pictures of an object taken from known positions. Given three such images it can ...
  • Avidan, Shai; Evgeniou, Theodoros; Shashua, Amnon; Poggio, Tomaso (1997-01-01)
    We present a new method for rendering novel images of flexible 3D objects from a small number of example images in correspondence. The strength of the method is the ability to synthesize images whose viewing position ...
  • Shelton, Christian Robert (2001-08-01)
    This thesis considers three complications that arise from applying reinforcement learning to a real-world application. In the process of using reinforcement learning to build an adaptive electronic market-maker, we find ...
  • Rennie, Jason D. M.; Rifkin, Ryan (2001-10-16)
    We compare Naive Bayes and Support Vector Machines on the task of multiclass text classification. Using a variety of approaches to combine the underlying binary classifiers, we find that SVMs substantially outperform Naive ...
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