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Now showing items 11-20 of 26
Learning by Failing to Explain
(1986-05-01)
Explanation-based Generalization requires that the learner obtain an explanation of why a precedent exemplifies a concept. It is, therefore, useless if the system fails to find this explanation. However, it is not ...
Learning object segmentation from video data
(2003-09-08)
This memo describes the initial results of a project to create aself-supervised algorithm for learning object segmentation from videodata. Developmental psychology and computational experience havedemonstrated that the ...
Learning Commonsense Categorical Knowledge in a Thread Memory System
(2004-05-18)
If we are to understand how we can build machines capable of broadpurpose learning and reasoning, we must first aim to build systemsthat can represent, acquire, and reason about the kinds of commonsenseknowledge that we ...
Recognition and Structure from One 2D Model View: Observations on Prototypes, Object Classes and Symmetries
(1992-02-01)
In this note we discuss how recognition can be achieved from a single 2D model view exploiting prior knowledge of an object's structure (e.g. symmetry). We prove that for any bilaterally symmetric 3D object one non- ...
Task and Object Learning in Visual Recognition
(1991-01-01)
Human performance in object recognition changes with practice, even in the absence of feedback to the subject. The nature of the change can reveal important properties of the process of recognition. We report an ...
Generalizing on Multiple Grounds: Performance Learning in Model-Based Technology
(1989-02-01)
This thesis explores ways to augment a model-based diagnostic program with a learning component, so that it speeds up as it solves problems. Several learning components are proposed, each exploiting a different kind ...
Probabilistic Independence Networks for Hidden Markov Probability Models
(1996-03-13)
Graphical techniques for modeling the dependencies of randomvariables have been explored in a variety of different areas includingstatistics, statistical physics, artificial intelligence, speech recognition, image ...
Neural Networks
(1996-03-13)
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 about data, and view ...
Interaction and Intelligent Behavior
(1994-08-01)
We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, ...
Learning object segmentation from video data
(2003-09-08)
This memo describes the initial results of a project to create a self-supervised algorithm for learning object segmentation from video data. Developmental psychology and computational experience have demonstrated that the ...