Results 1 - 10 of 324

Locality-constrained linear coding for image classification

by Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas Huang, Yihong Gong - IN: IEEE CONFERENCE ON COMPUTER VISION AND PATTERN CLASSIFICATOIN , 2010
"... The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC util ..."
Abstract - Cited by 443 (20 self) - Add to MetaCart
utilizes the locality constraints to project each descriptor into its local-coordinate system, and the projected coordinates are integrated by max pooling to generate the final representation. With linear classifier, the proposed approach performs remarkably better than the traditional nonlinear SPM

Efficient Simulation from the Multivariate Normal and Student-t Distributions Subject to Linear Constraints and the Evaluation of Constraint Probabilities

by John Geweke , 1991
"... The construction and implementation of a Gibbs sampler for efficient simulation from the truncated multivariate normal and Student-t distributions is described. It is shown how the accuracy and convergence of integrals based on the Gibbs sample may be constructed, and how an estimate of the probabil ..."
Abstract - Cited by 211 (10 self) - Add to MetaCart
The construction and implementation of a Gibbs sampler for efficient simulation from the truncated multivariate normal and Student-t distributions is described. It is shown how the accuracy and convergence of integrals based on the Gibbs sample may be constructed, and how an estimate

Improving Backtrack Search for Solving the TCSP

by Lin Xu, Berthe Y. Choueiry , 2003
"... In this paper, we address the task of finding the minimal network of a Temporal Constraint Satisfaction Problem (TCSP). We report the integration of three approaches to improve the performance of the exponential-time backtrack search (BT-TCSP) proposed by Dechter et al. [6] for this purpose. The fir ..."
Abstract - Cited by 7 (4 self) - Add to MetaCart
In this paper, we address the task of finding the minimal network of a Temporal Constraint Satisfaction Problem (TCSP). We report the integration of three approaches to improve the performance of the exponential-time backtrack search (BT-TCSP) proposed by Dechter et al. [6] for this purpose

Cache-oblivious data structures for orthogonal range searching

by Pankaj K. Agarwal, Lars Arge, Andrew Danner, Bryan Holland-Minkley - IN PROC. ACM SYMPOSIUM ON COMPUTATIONAL GEOMETRY , 2003
"... We develop cache-oblivious data structures for orthogonal range searching, the problem of finding all T points in a set of N points in Rd lying in a query hyper-rectangle. Cacheoblivious data structures are designed to be efficient in arbitrary memory hierarchies. We describe a dynamic linear-size ..."
Abstract - Cited by 20 (5 self) - Add to MetaCart
We develop cache-oblivious data structures for orthogonal range searching, the problem of finding all T points in a set of N points in Rd lying in a query hyper-rectangle. Cacheoblivious data structures are designed to be efficient in arbitrary memory hierarchies. We describe a dynamic linear

doi:10.1093/amrx/abq003 Nonlinearly Constrained Optimization Using Heuristic Penalty Methods and Asynchronous Parallel Generating Set Search

by Joshua D. Griffin, Tamara G. Kolda , 2009
"... Many optimization problems are characterized by expensive objective and/or constraint function evaluations paired with a lack of derivative information. Direct search methods such as generating set search (GSS) are well understood and efficient for derivative-free optimization of unconstrained and l ..."
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Many optimization problems are characterized by expensive objective and/or constraint function evaluations paired with a lack of derivative information. Direct search methods such as generating set search (GSS) are well understood and efficient for derivative-free optimization of unconstrained

Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An

by Zvika Ben-haim, Yonina C. Eldar
"... Abstract — We consider minimum variance estimation within the sparse linear Gaussian model (SLGM). A sparse vector is to be estimated from a linearly transformed version embedded in Gaussian noise. Our analysis is based on the theory of reproducing kernel Hilbert spaces (RKHS). After a characterizat ..."
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Abstract — We consider minimum variance estimation within the sparse linear Gaussian model (SLGM). A sparse vector is to be estimated from a linearly transformed version embedded in Gaussian noise. Our analysis is based on the theory of reproducing kernel Hilbert spaces (RKHS). After a

Multi-loop Position Analysis via Iterated Linear Programming

by unknown authors
"... Abstract — This paper presents a numerical method able to isolate all configurations that an arbitrary loop linkage can adopt, within given ranges for its degrees of freedom. The procedure is general, in the sense that it can be applied to single or multiple intermingled loops of arbitrary topology. ..."
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. It is also complete, meaning that all possible solutions get accurately bounded, irrespectively of whether the analyzed linkage is rigid or mobile. The problem is tackled by formulating a system of linear, parabolic, and hyperbolic equations, which is here solved by a new strategy exploiting its structure

Multi-loop Position Analysis via Iterated Linear Programming

by unknown authors
"... Abstract — This paper presents a numerical method able to isolate all configurations that an arbitrary loop linkage can adopt, within given ranges for its degrees of freedom. The procedure is general, in the sense that it can be applied to single or multiple intermingled loops of arbitrary topology, ..."
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, and complete, in the sense that all possible solutions get accurately bounded, irrespectively of whether the analyzed linkage is rigid or mobile. The problem is tackled by formulating a system of linear, parabolic, and hyperbolic equations, which is here solved by a new strategy exploiting its structure

Decidability of the Reachability for a Family of Linear Vector Fields

by Ting Gan, Mingshuai Chen, Liyun Dai, Bican Xia
"... Abstract. The reachability problem is one of the most important issues in the verification of hybrid systems. Computing the reachable sets of dif-ferential equations is difficult, although computing the reachable sets of finite state machines is well developed. Hence, it is not surprising that the r ..."
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functions, which has been proved in [21,22] due to Strzebonski. In this paper, we propose another decision procedure, which is more efficient when all constraints are open sets. The experimental results indicate the efficiency of our approach, even better than existing approaches based on approximation

Automatic Enumeration of (Related-key) Differential and Linear Characteristics with Predefined Properties and Its Applications

by Ling Song
"... Abstract. In this paper, we investigate the Mixed-integer Linear Programming (MILP) modelling of the differential and linear behavior of a wide rang of block ciphers. The differential and linear behavior of the transformations involved in a block cipher can be described by a set P ⊆ {0, 1}n ⊆ Rn. We ..."
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lower bounds of the number of differentially or linearly active S-boxes; and the new method is more efficient which is able to obtain characteristic enjoying higher probability or covering more rounds of a cipher with less computational effort.
Results 1 - 10 of 324