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Contextual models for object detection using boosted random fields
(2004-06-25)
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which uses Boosting to learn the graph structure and ...
Definition and Expansion of Composite Automata in IOA
(2004-07-19)
The IOA language provides notations for defining both primitive and composite I/O automata.This note describes, both formally and with examples, the constraints on these definitions, thecomposability requirements for the ...
Systematic Removal of Nondeterminism for Code Generation in I/O Automata
(2004-07-19)
The Input/Output (I/O) automaton model developed by Lynch and Tuttle models components in asynchronous concurrentsystems as labeled transition systems. IOA is a precise language for describing I/O automata and for stating ...
Discovering Latent Classes in Relational Data
(2004-07-22)
We present a framework for learning abstract relational knowledge with the aimof explaining how people acquire intuitive theories of physical, biological, orsocial systems. Our approach is based on a generative relational ...
A Constant-Factor Approximation Algorithm for Embedding Unweighted Graphs into Trees
(2004-07-05)
We present a constant-factor approximation algorithm for computing anembedding of the shortest path metric of an unweighted graph into atree, that minimizes the multiplicative distortion.
Dynamically Resizable Static CMOS Logic for Fine-Grain Leakage
(2004-07-12)
Digital circuits often have a critical path that runs through a smallsubset of the component subblocks, but where the path changes dynamicallyduring operation. Dynamically resizable static CMOS (DRCMOS) logic isproposed ...
Optimal Approximations of the Frequency Moments
(2004-07-02)
We give a one-pass, O~(m^{1-2/k})-space algorithm for estimating the k-th frequency moment of a data stream for any real k>2. Together with known lower bounds, this resolves the main problem left open by Alon, Matias, ...
Face processing in humans is compatible with a simple shape-based model of vision
(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 ...
Selecting Relevant Genes with a Spectral Approach
(2004-01-27)
Array technologies have made it possible to record simultaneously the expression pattern of thousands of genes. A fundamental problem in the analysis of gene expression data is the identification of highly relevant genes ...
On the difficulty of feature-based attentional modulations in visual object recognition: A modeling study.
(2004-01-14)
Numerous psychophysical experiments have shown an important role for attentional modulations in vision. Behaviorally, allocation of attention can improve performance in object detection and recognition tasks. At the neural ...