Results 1  10
of
1,914,562
More is Less: Reducing Latency via Redundancy
"... Low latency is critical for interactive networked applications. But while we know how to scale systems to increase capacity, reducing latency — especially the tail of the latency distribution — can be much more difficult. We argue that the use of redundancy in the context of the widearea Internet i ..."
Abstract

Cited by 18 (2 self)
 Add to MetaCart
Low latency is critical for interactive networked applications. But while we know how to scale systems to increase capacity, reducing latency — especially the tail of the latency distribution — can be much more difficult. We argue that the use of redundancy in the context of the widearea Internet
Introduction to redundant arrays of inexpensive disks
 Proceedings of the IEEE COMPCON
, 1989
"... Abstract Increasmg performance of CPUs and memorres wrll be squandered lf not matched by a sunrlm peformance ourease m II0 Whde the capactty of Smgle Large Expenstve D&T (SLED) has grown rapuily, the performance rmprovement of SLED has been modest Redundant Arrays of Inexpensive Disks (RAID), ba ..."
Abstract

Cited by 846 (55 self)
 Add to MetaCart
Abstract Increasmg performance of CPUs and memorres wrll be squandered lf not matched by a sunrlm peformance ourease m II0 Whde the capactty of Smgle Large Expenstve D&T (SLED) has grown rapuily, the performance rmprovement of SLED has been modest Redundant Arrays of Inexpensive Disks (RAID
Feature selection based on mutual information: Criteria of maxdepe ndency, maxrelevance, and minredundancy
 IEEE Trans. Pattern Analysis and Machine Intelligence
"... Abstract—Feature selection is an important problem for pattern classification systems. We study how to select good features according to the maximal statistical dependency criterion based on mutual information. Because of the difficulty in directly implementing the maximal dependency condition, we f ..."
Abstract

Cited by 533 (7 self)
 Add to MetaCart
first derive an equivalent form, called minimalredundancymaximalrelevance criterion (mRMR), for firstorder incremental feature selection. Then, we present a twostage feature selection algorithm by combining mRMR and other more sophisticated feature selectors (e.g., wrappers). This allows us
GPSless Low Cost Outdoor Localization For Very Small Devices
, 2000
"... Instrumenting the physical world through large networks of wireless sensor nodes, particularly for applications like environmental monitoring of water and soil, requires that these nodes be very small, light, untethered and unobtrusive. The problem of localization, i.e., determining where a given no ..."
Abstract

Cited by 994 (29 self)
 Add to MetaCart
Instrumenting the physical world through large networks of wireless sensor nodes, particularly for applications like environmental monitoring of water and soil, requires that these nodes be very small, light, untethered and unobtrusive. The problem of localization, i.e., determining where a given node is physically located in a network is a challenging one, and yet extremely crucial for many of these applications. Practical considerations such as the small size, form factor, cost and power constraints of nodes preclude the reliance on GPS (Global Positioning System) on all nodes in these networks. In this paper, we review localization techniques and evaluate the effectiveness of a very simple connectivitymetric method for localization in outdoor environments that makes use of the inherent radiofrequency (RF) communications capabilities of these devices. A fixed number of reference points in the network with overlapping regions of coverage transmit periodic beacon signals. Nodes use a...
Regression Shrinkage and Selection Via the Lasso
 Journal of the Royal Statistical Society, Series B
, 1994
"... We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients that are exactl ..."
Abstract

Cited by 4055 (51 self)
 Add to MetaCart
We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to produce some coefficients
NCBI reference sequence (RefSeq): a curated nonredundant sequence database of genomes, transcripts and proteins
 Nucleic Acids Res
, 2005
"... transcripts and proteins ..."
Functional discovery via a compendium of expression profiles. Cell 102:109
, 2000
"... have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of ..."
Abstract

Cited by 537 (8 self)
 Add to MetaCart
have been devised to survey gene functions en masse either computationally (Marcotte et al., 1999) or experimentally; among these, highly parallel assays of
Parametric Shape Analysis via 3Valued Logic
, 2001
"... Shape Analysis concerns the problem of determining "shape invariants"... ..."
Abstract

Cited by 660 (79 self)
 Add to MetaCart
Shape Analysis concerns the problem of determining "shape invariants"...
Solving multiclass learning problems via errorcorrecting output codes
 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
, 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
Abstract

Cited by 730 (8 self)
 Add to MetaCart
Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass learning problems include direct application of multiclass algorithms such as the decisiontree algorithms C4.5 and CART, application of binary concept learning algorithms to learn individual binary functions for each of the k classes, and application of binary concept learning algorithms with distributed output representations. This paper compares these three approaches to a new technique in which errorcorrecting codes are employed as a distributed output representation. We show that these output representations improve the generalization performance of both C4.5 and backpropagation on a wide range of multiclass learning tasks. We also demonstrate that this approach is robust with respect to changes in the size of the training sample, the assignment of distributed representations to particular classes, and the application of over tting avoidance techniques such as decisiontree pruning. Finally,we show thatlike the other methodsthe errorcorrecting code technique can provide reliable class probability estimates. Taken together, these results demonstrate that errorcorrecting output codes provide a generalpurpose method for improving the performance of inductive learning programs on multiclass problems.
Teleporting an Unknown Quantum State via Dual Classical and EPR Channels
, 1993
"... An unknown quantum state jOEi can be disassembled into, then later reconstructed from, purely classical information and purely nonclassical EPR correlations. To do so the sender, "Alice," and the receiver, "Bob," must prearrange the sharing of an EPRcorrelated pair of particles. ..."
Abstract

Cited by 648 (22 self)
 Add to MetaCart
An unknown quantum state jOEi can be disassembled into, then later reconstructed from, purely classical information and purely nonclassical EPR correlations. To do so the sender, "Alice," and the receiver, "Bob," must prearrange the sharing of an EPRcorrelated pair of particles. Alice makes a joint measurement on her EPR particle and the unknown quantum system, and sends Bob the classical result of this measurement. Knowing this, Bob can convert the state of his EPR particle into an exact replica of the unknown state jOEi which Alice destroyed. Expanded version of manuscript submitted to Phys. Rev. Lett. December 1992 PACS numbers: 03.65.Bz, 42.50.Dv, 89.70.+c (a) Permanent address. The existence of long range correlations between EinsteinPodolskyRosen (EPR) [1] pairs of particles raises the question of their use for information transfer. Einstein himself used the word "telepathically" in this context [2]. It is known that instantaneous information transfer is definitely impossib...
Results 1  10
of
1,914,562