In this paper we introduce a compression scheme suitable for large CAD (Computer Aided Design) models. We assume as input a large model in IGES and VRML formats that encode e ciently and transmit to a client for remote display and modeling. To this end we focus on two main issues: (a) space e cient encoding of IGES and VRML les, (b) fragmentation of the compressed model into small independent u...

Raymond E. Arvidson McDonnell Center for the Space Sciences, Department of Earth and Planetary Sciences, Washington University in St. Louis, St. Louis, Missouri 63130 e-mail: [email protected] Karl D. Iagnemma Robotic Mobility Group, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 e-mail: [email protected] Mark Maimone California Institute of Technology/ Jet Propulsion L...

Geographically dispersed sellers in electronic reverse-marketplaces such as those hosted by Freemarkets are uncertain about the number of competitors they face in any given market-session. Over the course of several market-sessions they learn about the competitive nature of the marketplace. How sellers learn to reduce the market-structure uncertainty depends on the market-transparency scheme, o...

introduction: in order to determine the multidrug resistance (mdr) phenotype due to p-glycoprotein expression in haematological malignancies including acute myeloblastic leukemia (aml), a well-characterized p-gp expressing cell line was required to validate and standardize flow cytometric assays and to calibrate instruments. therefore, this resistant subline of k562 was established for the firs...

We have built and evaluated software that supports students to reason about a phenomenon and develop hypotheses to explain it. The goal is for students to ask their own questions, engage in hypothesis generation and make and test predictions about theories. Intelligent tutoring and a discovery approach guide students’ inquiry in these problem-based modules. The inquiry infrastructure provides a...

Solutions of learning problems by Empirical Risk Minimization (ERM) – and almost-ERM when the minimizer does not exist – need to be consistent, so that they may be predictive. They also need to be well-posed in the sense of being stable, so that they might be used robustly. We propose a statistical form of leave-one-out stability, called CVEEEloo stability. We prove that for bounded loss classe...

Baylis & Driver [1] have recently presented data on the response of neurons in macaque inferotemporal cortex (IT) to various stimulus transformations. They report that neurons can generalize over contrast and mirror reversal, but not over figure-ground reversal. This finding is taken to demonstrate that “the selectivity of IT neurons is not determined simply by the distinctive contours in a dis...

Solutions of learning problems by Empirical Risk Minimization (ERM) – and almost-ERM when the minimizer does not exist – need to be consistent, so that they may be predictive. They also need to be well-posed in the sense of being stable, so that they might be used robustly. We propose a statistical form of stability, defined in terms of the property of cross-validation leaveone-out (CVloo) stab...

Solutions of learning problems by Empirical Risk Minimization (ERM) – and almost-ERM when the minimizer does not exist – need to be consistent, so that they may be predictive. They also need to be well-posed in the sense of being stable, so that they might be used robustly. We propose a statistical form of leave-one-out stability, called CVEEEloo stability. Our main new results are two. We prov...