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Piezoelectric Ultrasonic Micromotors
(1995-06-01)
This report describes development of micro-fabricated piezoelectric ultrasonic motors and bulk-ceramic piezoelectric ultrasonic motors. Ultrasonic motors offer the advantage of low speed, high torque operation without ...
Implementing Distributed Systems Using Linear Naming
(1993-03-01)
Linear graph reduction is a simple computational model in which the cost of naming things is explicitly represented. The key idea is the notion of "linearity". A name is linear if it is only used once, so with linear ...
Prototype of a Configurable Web-Based Assessment System
(1996-06-01)
The MIT Prototype Educational Assessment System provides subjects and courses at MIT with the ability to perform online assessment. The system includes polices to handle harassment and electronic "flaming" while ...
Maximum Entropy Discrimination
(1999-12-01)
We present a general framework for discriminative estimation based on the maximum entropy principle and its extensions. All calculations involve distributions over structures and/or parameters rather than specific ...
Learning from Ambiguity
(1998-12-01)
There are many learning problems for which the examples given by the teacher are ambiguously labeled. In this thesis, we will examine one framework of learning from ambiguous examples known as Multiple-Instance learning. ...
Concurrent Smalltalk on the Message-Driven Processor
(1991-09-01)
Concurrent Smalltalk is the primary language used for programming the J- Machine, a MIMD message-passing computer containing thousands of 36-bit processors connected by a very low latency network. This thesis describes ...
Pre-Attentive Segmentation in the Primary Visual Cortex
(1998-06-30)
Stimuli outside classical receptive fields have been shown to exert significant influence over the activities of neurons in primary visual cortexWe propose that contextual influences are used for pre-attentive visual ...
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers
(1996-12-01)
The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special ...
A Trainable Object Detection System: Car Detection in Static Images
(1999-10-13)
This paper describes a general, trainable architecture for object detection that has previously been applied to face and peoplesdetection with a new application to car detection in static images. Our technique is a ...
Learning-Based Approach to Real Time Tracking and Analysis of Faces
(1999-09-23)
This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this ...