number of iterations. Hierarchical reduction comple-ments the software pipelining technique, permitting a consis-tent performance improvement be obtained. The techniques proposed have been validated by an im-plementation of a compiler for Warp, a systolic array consist-ing of 10 VLIW processors

algorithm's predictions on new unlabeled examples are used to enlarge the training set of the other. Our goal in this paper is to provide a PAC-style analysis for this setting, and, more broadly, a PAC-style framework for the general problem of learning from both labeled and unlabeled data. We also

Our possessions are a major contributor to and reflection of our identities. A variety of evidence is presented supporting this simple and compelling premise. Related streans of research are identified and drawn upon in devetopJng this concept and implications are derived for consumer behavior

and over-comes some of their limitations. Our techniques can be applied to model arbitrarily complex shapes, which include shapes with significant protrusions, and to situations where no a priori as-sumption about the object’s topology is made. A single instance of our model, when presented with an image

The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices

sharing many of the same goals as previous dis-tributed file systems, our design has been driven by obser-vations of our application workloads and technological envi-ronment, both current and anticipated, that reflect a marked departure from some earlier file system assumptions. This has led us

per-pixel classification problem. Our large and highly varied training dataset allows the classifier to estimate body parts invariant to pose, body shape, clothing, etc. Finally we generate confidence-scored 3D proposals of several body joints by reprojecting the classification result and finding

that disconnected operation is feasible, efficient and usable by describing its design and implementation in the Coda File System. The central idea behind our work is that caching of data, now widely used for performance, can also be exploited to improve availability.

play Man and Superman. "He who can, does. He who cannot, teaches" is a calamitous insult to our profes-sion, yet one readily repeated even by teachers. More worrisome, its philosophy often appears to under-lie the policies concerning the occu-pation and activities of teaching. Where did

pyramid ” is a simple and computationally efficient extension of an orderless bag-of-features image representation, and it shows significantly improved performance on challenging scene categorization tasks. Specifically, our proposed method exceeds the state of the art on the Caltech-101 database