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Yeo, Gene, Poggio, Tomaso,
A novel approach to multiclass tumor classification using Artificial Neural Networks (ANNs) was introduced in a recent paper cite{Khan2001}. The method successfully classified and diagnosed small, rou...
complete descriptionhttp://hdl.handle.net/1721.1/7238
Mukherjee, Sayan, Vapnik, Vladimir,
We formulate density estimation as an inverse operator problem. We then use convergence results of empirical distribution functions to true distribution functions to develop an algorithm for multivari...
complete descriptionhttp://hdl.handle.net/1721.1/7260
Jordan, Michael I., Bishop, Christopher M.,
We present an overview of current research on artificial neural networks, emphasizing a statistical perspective. We view neural networks as parameterized graphs that make probabilistic assumptions abo...
complete descriptionhttp://hdl.handle.net/1721.1/7186
Poggio, Tomaso, Girosi, Federico,
We derive a new representation for a function as a linear combination of local correlation kernels at optimal sparse locations and discuss its relation to PCA, regularization, sparsity principles and ...
complete descriptionhttp://hdl.handle.net/1721.1/7255
Mohan, Anuj,
In this paper we present a component based person detection system that is capable of detecting frontal, rear and near side views of people, and partially occluded persons in cluttered scenes. The fra...
complete descriptionhttp://hdl.handle.net/1721.1/7293
Poggio, Tomaso, Hurlbert, Anya,
This paper sketches a hypothetical cortical architecture for visual 3D object recognition based on a recent computational model. The view-centered scheme relies on modules for learning from examples, ...
complete descriptionhttp://hdl.handle.net/1721.1/7217
Jordan, Michael, Xu, Lei,
"Expectation-Maximization'' (EM) algorithm and gradient-based approaches for maximum likelihood learning of finite Gaussian mixtures. We show that the EM step in parameter space is obtained from the g...
complete descriptionhttp://hdl.handle.net/1721.1/7195
Stein, Gideon P., Shashua, Amnon,
This paper investigates the linear degeneracies of projective structure estimation from point and line features across three views. We show that the rank of the linear system of equations for recoveri...
complete descriptionhttp://hdl.handle.net/1721.1/7251
Jaakkola, Tommi, Jordan, Michael I., Singh, Satinder P.,
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms, including the TD(lambda) a...
complete descriptionhttp://hdl.handle.net/1721.1/7205
Pontil, Massimiliano, Mukherjee, Sayan, Girosi, Federico,
Support Vector Machines Regression (SVMR) is a regression technique which has been recently introduced by V. Vapnik and his collaborators (Vapnik, 1995; Vapnik, Golowich and Smola, 1996). In SVMR the ...
complete descriptionhttp://hdl.handle.net/1721.1/7259