Results 1 - 10 of 178,067

Learning with local and global consistency.

by Dengyong Zhou , Olivier Bousquet , Thomas Navin Lal , Jason Weston , Bernhard Schölkopf - In NIPS, , 2003
"... Abstract We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised learning is to design a classifying function which is sufficiently smooth with respect to the intr ..."
Abstract - Cited by 673 (21 self) - Add to MetaCart
to the intrinsic structure collectively revealed by known labeled and unlabeled points. We present a simple algorithm to obtain such a smooth solution. Our method yields encouraging experimental results on a number of classification problems and demonstrates effective use of unlabeled data.

Consistency of spectral clustering

by Ulrike von Luxburg, Mikhail Belkin, Olivier Bousquet , 2004
"... Consistency is a key property of statistical algorithms, when the data is drawn from some underlying probability distribution. Surprisingly, despite decades of work, little is known about consistency of most clustering algorithms. In this paper we investigate consistency of a popular family of spe ..."
Abstract - Cited by 572 (15 self) - Add to MetaCart
Consistency is a key property of statistical algorithms, when the data is drawn from some underlying probability distribution. Surprisingly, despite decades of work, little is known about consistency of most clustering algorithms. In this paper we investigate consistency of a popular family

Globally Consistent Range Scan Alignment for Environment Mapping

by F. Lu, E. Milios - AUTONOMOUS ROBOTS , 1997
"... A robot exploring an unknown environmentmay need to build a world model from sensor measurements. In order to integrate all the frames of sensor data, it is essential to align the data properly. An incremental approach has been typically used in the past, in which each local frame of data is alig ..."
Abstract - Cited by 531 (8 self) - Add to MetaCart
A robot exploring an unknown environmentmay need to build a world model from sensor measurements. In order to integrate all the frames of sensor data, it is essential to align the data properly. An incremental approach has been typically used in the past, in which each local frame of data

On Model Selection Consistency of Lasso

by Peng Zhao, Bin Yu , 2006
"... Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such models, but usually involves a computationally heavy combinatorial search. Lasso (Tibshirani, 1996) is now being used ..."
Abstract - Cited by 477 (20 self) - Add to MetaCart
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such models, but usually involves a computationally heavy combinatorial search. Lasso (Tibshirani, 1996) is now being

Incorporating non-local information into information extraction systems by Gibbs sampling

by Jenny Rose Finkel, Trond Grenager, Christopher Manning - IN ACL , 2005
"... Most current statistical natural language processing models use only local features so as to permit dynamic programming in inference, but this makes them unable to fully account for the long distance structure that is prevalent in language use. We show how to solve this dilemma with Gibbs sampling, ..."
Abstract - Cited by 730 (25 self) - Add to MetaCart
, a simple Monte Carlo method used to perform approximate inference in factored probabilistic models. By using simulated annealing in place of Viterbi decoding in sequence models such as HMMs, CMMs, and CRFs, it is possible to incorporate non-local structure while preserving tractable inference. We

Consistent hashing and random trees: Distributed caching protocols for relieving hot spots on the World Wide Web

by David Karger, Eric Lehman, Tom Leighton, Matthew Levine, Daniel Lewin, Rina Panigrahy - IN PROC. 29TH ACM SYMPOSIUM ON THEORY OF COMPUTING (STOC , 1997
"... We describe a family of caching protocols for distrib-uted networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, where delays caused by hot spots can be severe, and ..."
Abstract - Cited by 699 (10 self) - Add to MetaCart
, and where it is not feasible for every server to have complete information about the current state of the entire network. The protocols are easy to implement using existing network protocols such as TCP/IP, and require very little overhead. The protocols work with local control, make efficient use

Local grayvalue invariants for image retrieval

by Cordelia Schmid, Roger Mohr - IEEE Transactions on Pattern Analysis and Machine Intelligence , 1997
"... Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows for efficie ..."
Abstract - Cited by 548 (27 self) - Add to MetaCart
Abstract—This paper addresses the problem of retrieving images from large image databases. The method is based on local grayvalue invariants which are computed at automatically detected interest points. A voting algorithm and semilocal constraints make retrieval possible. Indexing allows

A PERFORMANCE EVALUATION OF LOCAL DESCRIPTORS

by Krystian Mikolajczyk, Cordelia Schmid , 2005
"... In this paper we compare the performance of descriptors computed for local interest regions, as for example extracted by the Harris-Affine detector [32]. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how their perfo ..."
Abstract - Cited by 1783 (51 self) - Add to MetaCart
In this paper we compare the performance of descriptors computed for local interest regions, as for example extracted by the Harris-Affine detector [32]. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how

Recognizing human actions: A local SVM approach

by Christian Schüldt, Ivan Laptev, Barbara Caputo - In ICPR , 2004
"... Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space-ti ..."
Abstract - Cited by 758 (20 self) - Add to MetaCart
Local space-time features capture local events in video and can be adapted to the size, the frequency and the velocity of moving patterns. In this paper we demonstrate how such features can be used for recognizing complex motion patterns. We construct video representations in terms of local space

The information bottleneck method

by Naftali Tishby, Fernando C. Pereira, William Bialek , 1999
"... We define the relevant information in a signal x ∈ X as being the information that this signal provides about another signal y ∈ Y. Examples include the information that face images provide about the names of the people portrayed, or the information that speech sounds provide about the words spoken. ..."
Abstract - Cited by 540 (35 self) - Add to MetaCart
consistent equations for the coding rules X → ˜ X and ˜ X → Y. Solutions to these equations can be found by a convergent re–estimation method that generalizes the Blahut–Arimoto algorithm. Our variational principle provides a surprisingly rich framework for discussing a variety of problems in signal
Results 1 - 10 of 178,067