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15,417
Myrinet: A Gigabit-per-Second Local Area Network
- IEEE Micro
, 1995
"... Abstract. Myrinet is a new type of local-area network (LAN) based on the technology used for packet communication and switching within "massivelyparallel processors " (MPPs). Think of Myrinet as an MPP message-passing network that can span campus dimensions, rather than as a wide-a ..."
Abstract
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Cited by 1011 (0 self)
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Abstract. Myrinet is a new type of local-area network (LAN) based on the technology used for packet communication and switching within "massivelyparallel processors " (MPPs). Think of Myrinet as an MPP message-passing network that can span campus dimensions, rather than as a wide
Self-Similarity in World Wide Web Traffic: Evidence and Possible Causes
, 1996
"... Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to the self-similarity of network traffic. We present a hypothesized explanation for the possible self-similarity of traffic by using a p ..."
Abstract
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Cited by 1416 (26 self)
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Recently the notion of self-similarity has been shown to apply to wide-area and local-area network traffic. In this paper we examine the mechanisms that give rise to the self-similarity of network traffic. We present a hypothesized explanation for the possible self-similarity of traffic by using a
Determining Optical Flow
- ARTIFICIAL INTELLIGENCE
, 1981
"... Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent veloc ..."
Abstract
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Cited by 2404 (9 self)
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Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent
Real-time human pose recognition in parts from single depth images
- IN CVPR
, 2011
"... We propose a new method to quickly and accurately predict 3D positions of body joints from a single depth image, using no temporal information. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler p ..."
Abstract
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Cited by 568 (17 self)
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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
Reliable Communication in the Presence of Failures
- ACM Transactions on Computer Systems
, 1987
"... The design and correctness of a communication facility for a distributed computer system are reported on. The facility provides support for fault-tolerant process groups in the form of a family of reliable multicast protocols that can be used in both local- and wide-area networks. These protocols at ..."
Abstract
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Cited by 546 (18 self)
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The design and correctness of a communication facility for a distributed computer system are reported on. The facility provides support for fault-tolerant process groups in the form of a family of reliable multicast protocols that can be used in both local- and wide-area networks. These protocols
Scale-space and edge detection using anisotropic diffusion
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1990
"... Abstract-The scale-space technique introduced by Witkin involves generating coarser resolution images by convolving the original image with a Gaussian kernel. This approach has a major drawback: it is difficult to obtain accurately the locations of the “semantically mean-ingful ” edges at coarse sca ..."
Abstract
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Cited by 1887 (1 self)
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scales. In this paper we suggest a new definition of scale-space, and introduce a class of algorithms that realize it using a diffusion process. The diffusion coefficient is chosen to vary spatially in such a way as to encourage intraregion smoothing in preference to interregion smoothing. It is shown
Loopy belief propagation for approximate inference: An empirical study. In:
- Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract
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Cited by 676 (15 self)
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tiply connected networks: When loops are present, the network is no longer singly connected and local propaga tion schemes will invariably run into trouble . We believe there are general undiscovered theorems about the performance of belief propagation on loopy DAGs. These theo rems, which may have
FARSITE: Federated, Available, and Reliable Storage for an Incompletely Trusted Environment
- IN PROCEEDINGS OF THE 5TH SYMPOSIUM ON OPERATING SYSTEMS DESIGN AND IMPLEMENTATION (OSDI
, 2002
"... Farsite is a secure, scalable file system that logically functions as a centralized file server but is physically distributed among a set of untrusted computers. Farsite provides file availability and reliability through randomized replicated storage; it ensures the secrecy of file contents with cry ..."
Abstract
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Cited by 487 (13 self)
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with cryptographic techniques; it maintains the integrity of file and directory data with a Byzantine-fault-tolerant protocol; it is designed to be scalable by using a distributed hint mechanism and delegation certificates for pathname translations; and it achieves good performance by locally caching file data
A New Voronoi-Based Surface Reconstruction Algorithm
, 2002
"... We describe our experience with a new algorithm for the reconstruction of surfaces from unorganized sample points in R³. The algorithm is the first for this problem with provable guarantees. Given a “good sample” from a smooth surface, the output is guaranteed to be topologically correct and converg ..."
Abstract
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Cited by 414 (9 self)
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and convergent to the original surface as the sampling density increases. The definition of a good sample is itself interesting: the required sampling density varies locally, rigorously capturing the intuitive notion that featureless areas can be reconstructed from fewer samples. The output mesh interpolates
Greedy layer-wise training of deep networks
, 2006
"... Complexity theory of circuits strongly suggests that deep architectures can be much more efficient (sometimes exponentially) than shallow architectures, in terms of computational elements required to represent some functions. Deep multi-layer neural networks have many levels of non-linearities allow ..."
Abstract
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Cited by 394 (48 self)
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-linearities allowing them to compactly represent highly non-linear and highly-varying functions. However, until recently it was not clear how to train such deep networks, since gradient-based optimization starting from random initialization appears to often get stuck in poor solutions. Hin-ton et al. recently
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