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An empirical study on the effects of spatial discretization error in a stereo vision system

K. L. Chan, A. K. Forrest
1990 Procedings of the British Machine Vision Conference 1990  
We derive an empirical relationship between the uncertainty volume of triangulation at the vergence point of convergent stereo viewing and the average triangulation error in such a set-up.  ...  The size of this polyhedral volume is then the uncertainty volume within which the triangulated 3D point lies.  ...  We derive an empirical relationship between the uncertainty volume of triangulation at the vergence point of convergent stereo viewing and the average triangulation error in such a set-up.  ... 
doi:10.5244/c.4.48 dblp:conf/bmvc/ChanF90 fatcat:fylnu3otxbeyfodqukky4sku7u

Unraveling the Role of Shared Vision and Trust in Constructive Conflict Management of Family Firms. An Empirical Study From a Mixed Methods Approach

Cristina Alvarado-Alvarez, Immaculada Armadans, María José Parada, M. Teresa Anguera
2021 Frontiers in Psychology  
We study the relationship between shared vision and trust that intervene in the adoption of constructive conflict management.  ...  Family firms are a unique setting to study constructive conflict management due to the influence of family ties of the owning family imprinting a sense of common purpose and shared destiny, and high levels  ...  Further studies may investigate the potential of conflict management as a tool for balancing work and family in the context of family firms (Lu et al., 2012) .  ... 
doi:10.3389/fpsyg.2021.629730 fatcat:ktuzwk4zmvbzlpnucmq7i5anie

Predictive modeling in a polyhedral optimization space

Eunjung Park, Louis-Noel Pouche, John Cavazos, Albert Cohen, P. Sadayappan
2011 International Symposium on Code Generation and Optimization (CGO 2011)  
We allow for a minimal empirical search on the target machine, discovering on average 83% of the search space optimal combinations in at most 5 runs.  ...  But since the number of polyhedral optimization alternatives can be enormous, it is often impractical to iterate over a significant fraction of the entire space of polyhedral transformed variants.  ...  National Science Foundation through award 0926688, the Defense Advanced Research Projects Agency through AFRL Contract FA8650-09-C-7915, the DARPA Computer Science Study Group (CSSG) and NSF Career award  ... 
doi:10.1109/cgo.2011.5764680 dblp:conf/cgo/ParkPCCS11 fatcat:4jf4y3zuwza37bpdp6je5yyrkm

Optimizing Dynamic Resource Allocation

Lucas W. Krakow, Louis Rabiet, Yun Zou, Guillaume Iooss, Edwin K.P. Chong, Sanjay Rajopadhye
2014 Procedia Computer Science  
We present a formulation, solution method, and program acceleration techniques for two dynamic control scenarios, both with the common goal of optimizing resource allocations.  ...  A novel aspect is included in the second scenario: dynamically allocating the computational resources in an online fashion which is made possible through constant aspect ratio tiling (CART).  ...  Through the non-myopic management of the computational resources, Section 4, energy and time expended for the tracking execution can be reduced in an optimal manner.  ... 
doi:10.1016/j.procs.2014.05.115 fatcat:xe42jy2q4jg5raeokutw75jhuq

Predictive Modeling in a Polyhedral Optimization Space

Eunjung Park, John Cavazos, Louis-Noël Pouchet, Cédric Bastoul, Albert Cohen, P. Sadayappan
2013 International journal of parallel programming  
We allow for a minimal empirical search on the target machine, discovering on average 83% of the search space optimal combinations in at most 5 runs.  ...  But since the number of polyhedral optimization alternatives can be enormous, it is often impractical to iterate over a significant fraction of the entire space of polyhedral transformed variants.  ...  National Science Foundation through award 0926688, the Defense Advanced Research Projects Agency through AFRL Contract FA8650-09-C-7915, the DARPA Computer Science Study Group (CSSG) and NSF Career award  ... 
doi:10.1007/s10766-013-0241-1 fatcat:x3slz5gqlfdzzhu3jnlyfetjhy

Switchable Scheduling for Runtime Adaptation of Optimization [chapter]

Lénaïc Bagnères, Cédric Bastoul
2014 Lecture Notes in Computer Science  
Finding the best optimization for every context at compile time is clearly out of reach.  ...  The recent shift to multicore architectures for desktop and embedded systems as well as the emergence of cloud computing is raising the problem of the impact of the execution context on performance.  ...  For this purpose we rely on a dedicated version generation phase and on an extensive empirical study of the version behavior.  ... 
doi:10.1007/978-3-319-09873-9_19 fatcat:2plmmzbkbnewvixyvf5olfjdie

Iterative Optimization in the Polyhedral Model: Part I, One-Dimensional Time

Louis-Noel Pouchet, Cedric Bastoul, Albert Cohen, Nicolas Vasilache
2007 International Symposium on Code Generation and Optimization (CGO'07)  
This method is based on an upstream characterization, as opposed to state-of-the-art downstream filtering approaches.  ...  Our results demonstrate orders of magnitude improvements in the size of the search space and in the convergence speed of a dedicated iterative optimization heuristic.  ...  We defer the application of these approaches to a further study, dedicating this paper to the study of the mathematical properties of our model, in an attempt to pruning the search space without loosing  ... 
doi:10.1109/cgo.2007.21 dblp:conf/cgo/PouchetBCV07 fatcat:tjuvrrggvfd2pgpjqixp2kgalu

Generalization Bounds in the Predict-then-Optimize Framework [article]

Othman El Balghiti, Adam N. Elmachtoub, Paul Grigas, Ambuj Tewari
2022 arXiv   pre-print
The predict-then-optimize framework is fundamental in many practical settings: predict the unknown parameters of an optimization problem, and then solve the problem using the predicted values of the parameters  ...  We first derive bounds based on the Natarajan dimension that, in the case of a polyhedral feasible region, scale at most logarithmically in the number of extreme points, but, in the case of a general convex  ...  AE acknowledges the support of NSF via grant CMMI-1763000. PG acknowledges the support of NSF Awards CCF-1755705 and CMMI-1762744.  ... 
arXiv:1905.11488v3 fatcat:kqe7qpgxsjes5gxpfatd5az3ta

A practical automatic polyhedral parallelizer and locality optimizer

Uday Bondhugula, Albert Hartono, J. Ramanujam, P. Sadayappan
2008 SIGPLAN notices  
The system also enables the easy use of powerful empirical/iterative optimization for general arbitrarily nested loop sequences.  ...  We present the design and implementation of an automatic polyhedral source-to-source transformation framework that can optimize regular programs (sequences of possibly imperfectly nested loops) for parallelism  ...  We wish to acknowledge Martin Griebl and team (FMI, Universität Passau, Germany) for the LooPo infrastructure. We thank the reviewers of the submission for detailed comments.  ... 
doi:10.1145/1379022.1375595 fatcat:mx5tqjwvdzfelgf4j7rrwb7ojm

A practical automatic polyhedral parallelizer and locality optimizer

Uday Bondhugula, Albert Hartono, J. Ramanujam, P. Sadayappan
2008 Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation - PLDI '08  
The system also enables the easy use of powerful empirical/iterative optimization for general arbitrarily nested loop sequences.  ...  We present the design and implementation of an automatic polyhedral source-to-source transformation framework that can optimize regular programs (sequences of possibly imperfectly nested loops) for parallelism  ...  We wish to acknowledge Martin Griebl and team (FMI, Universität Passau, Germany) for the LooPo infrastructure. We thank the reviewers of the submission for detailed comments.  ... 
doi:10.1145/1375581.1375595 dblp:conf/pldi/BondhugulaHRS08 fatcat:oxeykavud5fqffeswz3o7k5ote

Optimization-Based and Machine-Learning Methods for Conjoint Analysis: Estimation and Question Design [chapter]

Olivier Toubia, Theodoros Evgeniou, John Hauser
2007 Conjoint Measurement  
This chapter reviews recent developments in the application of optimization methods and machine learning to the estimation of conjoint-analysis partworths and to the adaptation of conjoint-analysis questions  ...  We demonstrate that, while the proposed methods are relatively new, they show considerable potential to improve the accuracy of conjoint-analysis partworths and to improve the predictive ability of conjoint-analysis  ...  Bootstrapping methods like crossvalidation (reviewed in a later section), for example, offer a practical and effective way of searching for this optimal value of γ , which is an issue extensively studied  ... 
doi:10.1007/978-3-540-71404-0_12 fatcat:bahbj4gcqnfafmf57vs7dbizr4

Application of Optimization Algorithms in Clusters

Ruby Srivastava
2021 Frontiers in Chemistry  
The potential energy surfaces (PES) are explored to find several minima with an ultimate goal of locating the global minima (GM) for the clusters.  ...  Various model or empirical potentials (EPs) as Lennard–Jones (LJ), Born–Mayer, Gupta, Sutton–Chen, and Murrell–Mottram potentials are used to describe the bonding in different type of clusters.  ...  In one of the Agpdpt alloys study, both empirical investigation and the theoretical analysis has given strong evidence that these nanoparticles are composed by an AgPd alloy core with Pt atoms lied on  ... 
doi:10.3389/fchem.2021.637286 pmid:33777900 pmcid:PMC7994592 fatcat:b2jjjx4alfbh5cfqzsvxvtwabi

Iterative optimization in the polyhedral model

Louis-Noël Pouchet, Cédric Bastoul, Albert Cohen, John Cavazos
2008 Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation - PLDI '08  
Thus, we introduce the use of a genetic algorithm with specialized operators that leverage the polyhedral representation of program dependences.  ...  We first propose a feedback-driven iterative heuristic tailored to the search space properties of the polyhedral model.  ...  Acknowledgments Uday+Ram+Saday for fruitful talks and Cornero/Rohou for the traviata board  ... 
doi:10.1145/1375581.1375594 dblp:conf/pldi/PouchetBCC08 fatcat:p6z3qjhxl5cx7jwjvlu7cabgie

Iterative optimization in the polyhedral model

Louis-Noël Pouchet, Cédric Bastoul, Albert Cohen, John Cavazos
2008 SIGPLAN notices  
Thus, we introduce the use of a genetic algorithm with specialized operators that leverage the polyhedral representation of program dependences.  ...  We first propose a feedback-driven iterative heuristic tailored to the search space properties of the polyhedral model.  ...  Acknowledgments Uday+Ram+Saday for fruitful talks and Cornero/Rohou for the traviata board  ... 
doi:10.1145/1379022.1375594 fatcat:2g6qs7a4qzbixmf7mz3mw5gke4

Combined Iterative and Model-driven Optimization in an Automatic Parallelization Framework

Louis-Noel Pouchet, Uday Bondhugula, Cedric Bastoul, Albert Cohen, J. Ramanujam, P. Sadayappan
2010 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis  
Today's multi-core era places significant demands on an optimizing compiler, which must parallelize programs, exploit memory hierarchy, and leverage the ever-increasing SIMD capabilities of modern processors  ...  We have developed a completely automatic framework in which we focus the empirical search on the set of valid possibilities to perform fusion/code motion, and rely on model-based mechanisms to perform  ...  It was also partly supported by the European Commission through the FP6 project SARC id. 027648.  ... 
doi:10.1109/sc.2010.14 dblp:conf/sc/PouchetBBCRS10 fatcat:wtvly4ercbai3lo6t7ry4f7tee
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