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A Virtual Machine for a Type-omega Denotational Proof Language
(2002-06-01)
In this thesis, I designed and implemented a virtual machine (VM) for a monomorphic variant of Athena, a type-omega denotational proof language (DPL). This machine attempts to maintain the minimum state required to ...
A Detailed Look at Scale and Translation Invariance in a Hierarchical Neural Model of Visual Object Recognition
(2002-08-01)
The HMAX model has recently been proposed by Riesenhuber & Poggio as a hierarchical model of position- and size-invariant object recognition in visual cortex. It has also turned out to model successfully a number of ...
The Individual is Nothing, the Class Everything: Psychophysics and Modeling of Recognition in Obect Classes
(2000-05-01)
Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often ...
Exploring Object Perception with Random Image Structure Evolution
(2001-03-01)
We have developed a technique called RISE (Random Image Structure Evolution), by which one may systematically sample continuous paths in a high-dimensional image space. A basic RISE sequence depicts the evolution of an ...
An Empirical Comparison of SNoW and SVMs for Face Detection
(2001-01-01)
Impressive claims have been made for the performance of the SNoW algorithm on face detection tasks by Yang et. al. [7]. In particular, by looking at both their results and those of Heisele et. al. [3], one could infer that ...
Policy Improvement for POMDPs Using Normalized Importance Sampling
(2001-03-20)
We present a new method for estimating the expected return of a POMDP from experience. The estimator does not assume any knowle ge of the POMDP and allows the experience to be gathered with an arbitrary set of policies. ...
Face Detection in Still Gray Images
(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 ...
Computational Models of Object Recognition in Cortex: A Review
(2000-08-07)
Understanding how biological visual systems perform object recognition is one of the ultimate goals in computational neuroscience. Among the biological models of recognition the main distinctions are between feedforward ...
People Recognition in Image Sequences by Supervised Learning
(2000-06-01)
We describe a system that learns from examples to recognize people in images taken indoors. Images of people are represented by color-based and shape-based features. Recognition is carried out through combinations of Support ...
An Electronic Market-Maker
(2001-04-17)
This paper presents an adaptive learning model for market-making under the reinforcement learning framework. Reinforcement learning is a learning technique in which agents aim to maximize the long-term accumulated rewards. ...