Results 1  10
of
289,756
RCMap: Efficiently Creating HighQuality Euclidean Embeddings
"... For many applications in computer vision and multimedia, similarity between objects is measured by a dissimilarity function that is complex, expensive to compute, and often nonmetric. To allow fast distance computations, these objects may be embedded into a vector space, where the distance between ..."
Abstract
 Add to MetaCart
quality, and may create embeddings that do not approximate the original dissimilarities well. BoostMap improves embedding quality, but incurs high computational cost. In this work, we propose RCMap, a technique that offers significant speedup over Boostmap, with minimal loss in embedding quality. 1
Efficient similarity search in sequence databases
, 1994
"... We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong. Anot ..."
Abstract

Cited by 505 (21 self)
 Add to MetaCart
. Another important observation is Parseval's theorem, which specifies that the Fourier transform preserves the Euclidean distance in the time or frequency domain. Having thus mapped sequences to a lowerdimensionality space by using only the first few Fourier coe cients, we use Rtrees to index
Efficient and Effective Querying by Image Content
 Journal of Intelligent Information Systems
, 1994
"... In the QBIC (Query By Image Content) project we are studying methods to query large online image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include med ..."
Abstract

Cited by 500 (13 self)
 Add to MetaCart
, and of images of airplane silhouettes. We also consider the efficient indexing of these features, specifically addre...
An Efficient Boosting Algorithm for Combining Preferences
, 1999
"... The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new boosting ..."
Abstract

Cited by 707 (18 self)
 Add to MetaCart
The problem of combining preferences arises in several applications, such as combining the results of different search engines. This work describes an efficient algorithm for combining multiple preferences. We first give a formal framework for the problem. We then describe and analyze a new
Quantization Index Modulation: A Class of Provably Good Methods for Digital Watermarking and Information Embedding
 IEEE TRANS. ON INFORMATION THEORY
, 1999
"... We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing informationembedding rate, mini ..."
Abstract

Cited by 495 (15 self)
 Add to MetaCart
We consider the problem of embedding one signal (e.g., a digital watermark), within another "host" signal to form a third, "composite" signal. The embedding is designed to achieve efficient tradeoffs among the three conflicting goals of maximizing informationembedding rate
An EnergyEfficient MAC Protocol for Wireless Sensor Networks
, 2002
"... This paper proposes SMAC, a mediumaccess control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use batteryoperated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect senso ..."
Abstract

Cited by 1488 (37 self)
 Add to MetaCart
This paper proposes SMAC, a mediumaccess control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use batteryoperated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in almost every way: energy conservation and selfconfiguration are primary goals, while pernode fairness and latency are less important. SMAC uses three novel techniques to reduce energy consumption and support selfconfiguration. To reduce energy consumption in listening to an idle channel, nodes periodically sleep. Neighboring nodes form virtual clusters to autosynchronize on sleep schedules. Inspired by PAMAS, SMAC also sets the radio to sleep during transmissions of other nodes. Unlike PAMAS, it only uses inchannel signaling. Finally, SMAC applies message passing to reduce contention latency for sensornetwork applications that require storeandforward processing as data move through the network. We evaluate our implementation of SMAC over a sample sensor node, the Mote, developed at University of California, Berkeley. The experiment results show that, on a source node, an 802.11like MAC consumes 26 times more energy than SMAC for traffic load with messages sent every 110s.
Mtree: An Efficient Access Method for Similarity Search in Metric Spaces
, 1997
"... A new access meth d, called Mtree, is proposed to organize and search large data sets from a generic "metric space", i.e. whE4 object proximity is only defined by a distance function satisfyingth positivity, symmetry, and triangle inequality postulates. We detail algorith[ for insertion o ..."
Abstract

Cited by 652 (38 self)
 Add to MetaCart
A new access meth d, called Mtree, is proposed to organize and search large data sets from a generic "metric space", i.e. whE4 object proximity is only defined by a distance function satisfyingth positivity, symmetry, and triangle inequality postulates. We detail algorith[ for insertion of objects and split management, whF h keep th Mtree always balanced  severalheralvFV split alternatives are considered and experimentally evaluated. Algorithd for similarity (range and knearest neigh bors) queries are also described. Results from extensive experimentationwith a prototype system are reported, considering as th performance criteria th number of page I/O's and th number of distance computations. Th results demonstratethm th Mtree indeed extendsth domain of applicability beyond th traditional vector spaces, performs reasonably well inhE[94Kv#E44V[vh data spaces, and scales well in case of growing files. 1
Social capital, intellectual capital, and the organizational advantage
 Academy of Management Review
, 1998
"... Scholars of the theory of the firm have begun to emphasize the sources and conditions of what has been described a s "the organizational advantage, " rather than focus on the causes and consequences of market failure. Typically, researchers see such organizational advantage a s accruing fr ..."
Abstract

Cited by 1100 (1 self)
 Add to MetaCart
settings. a re conducive to the development of high levels of social capital. and (3) it is because of their more dense social capital that firms. within certain limits. have a n advantage over markets in creating and sharing intellectual capital. We present a model that incorporates this overall argument
Primitives for the manipulation of general subdivisions and the computations of Voronoi diagrams
 ACM Tmns. Graph
, 1985
"... The following problem is discussed: Given n points in the plane (the sites) and an arbitrary query point 4, find the site that is closest to q. This problem can be solved by constructing the Voronoi diagram of the given sites and then locating the query point in one of its regions. Two algorithms ar ..."
Abstract

Cited by 543 (11 self)
 Add to MetaCart
to the separation of the geometrical and topological aspects of the problem and to the use of two simple but powerful primitives, a geometric predicate and an operator for manipulating the topology of the diagram. The topology is represented by a new data structure for generalized diagrams, that is, embeddings
Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
, 2004
"... Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear m ..."
Abstract

Cited by 1513 (20 self)
 Add to MetaCart
Suppose we are given a vector f in RN. How many linear measurements do we need to make about f to be able to recover f to within precision ɛ in the Euclidean (ℓ2) metric? Or more exactly, suppose we are interested in a class F of such objects— discrete digital signals, images, etc; how many linear
Results 1  10
of
289,756