Results 1 - 10 of 3,625

Randomized kinodynamic planning

by Steven M. Lavalle, James J. Kuffner, Jr. - THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2001; 20; 378 , 2001
"... This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based ..."
Abstract - Cited by 626 (35 self) - Add to MetaCart
dynamical models and avoiding obstacles in the robot’s environment. The authors consider generic systems that express the nonlinear dynamics of a robot in terms of the robot’s high-dimensional configuration space. Kinodynamic planning is treated as a motion-planning problem in a higher dimensional state

Gradient-based learning applied to document recognition

by Yann Lecun, Léon Bottou, Yoshua Bengio, Patrick Haffner - Proceedings of the IEEE , 1998
"... Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify hi ..."
Abstract - Cited by 1533 (84 self) - Add to MetaCart
high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed

Eigentaste: A Constant Time Collaborative Filtering Algorithm

by Ken Goldberg, Theresa Roeder, Dhruv Gupta, Chris Perkins , 2000
"... Eigentaste is a collaborative filtering algorithm that uses universal queries to elicit real-valued user ratings on a common set of items and applies principal component analysis (PCA) to the resulting dense subset of the ratings matrix. PCA facilitates dimensionality reduction for offline clusterin ..."
Abstract - Cited by 378 (6 self) - Add to MetaCart
Eigentaste is a collaborative filtering algorithm that uses universal queries to elicit real-valued user ratings on a common set of items and applies principal component analysis (PCA) to the resulting dense subset of the ratings matrix. PCA facilitates dimensionality reduction for offline

Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function

by Garrett M. Morris, David S. Goodsell, Robert S. Halliday, Ruth Huey, William E. Hart, Richard K. Belew, Arthur J. Olson - J. Comput. Chem , 1998
"... ABSTRACT: A novel and robust automated docking method that predicts the bound conformations of flexible ligands to macromolecular targets has been developed and tested, in combination with a new scoring function that estimates the free energy change upon binding. Interestingly, this method applies a ..."
Abstract - Cited by 380 (4 self) - Add to MetaCart
algorithm, and compare their performance in dockings of seven protein�ligand test systems having known three-dimensional structure. We show that both the traditional and Lamarckian genetic algorithms can handle ligands with more degrees of freedom than the simulated annealing method used in earlier versions

Model selection and accounting for model uncertainty in graphical models using Occam's window

by David Madigan, Adrian E. Raftery , 1993
"... We consider the problem of model selection and accounting for model uncertainty in high-dimensional contingency tables, motivated by expert system applications. The approach most used currently is a stepwise strategy guided by tests based on approximate asymptotic P-values leading to the selection o ..."
Abstract - Cited by 370 (47 self) - Add to MetaCart
We consider the problem of model selection and accounting for model uncertainty in high-dimensional contingency tables, motivated by expert system applications. The approach most used currently is a stepwise strategy guided by tests based on approximate asymptotic P-values leading to the selection

Incorporating Contextual Information in Recommender Systems Using a Multidimensional Approach

by Gediminas Adomavicius, Ramesh Sankaranarayanan, Shahana Sen, Alexander Tuzhilin - ACM Transactions on Information Systems , 2005
"... The paper presents a multidimensional (MD) approach to recommender systems that can provide recommendations based on additional contextual information besides the typical information on users and items used in most of the current recommender systems. This approach supports multiple dimensions, exten ..."
Abstract - Cited by 236 (9 self) - Add to MetaCart
approach outperforms the standard two-dimensional approach and uses the MD approach in those situations and the standard two-dimensional approach elsewhere. Finally, the paper presents a pilot empirical study of the combined approach, using a multidimensional movie recommender system that was developed

Two dimensional gauge theories revisited

by Edward Witten, Olden Lane - J. Geom. Phys , 1992
"... Two dimensional quantum Yang-Mills theory is reexamined using a non-abelian version of the Duistermaat-Heckman integration formula to carry out the functional integral. This makes it possible to explain properties of the theory that are inaccessible to standard methods and to obtain general expressi ..."
Abstract - Cited by 200 (3 self) - Add to MetaCart
Two dimensional quantum Yang-Mills theory is reexamined using a non-abelian version of the Duistermaat-Heckman integration formula to carry out the functional integral. This makes it possible to explain properties of the theory that are inaccessible to standard methods and to obtain general

Lost in quantization: Improving particular object retrieval in large scale image databases

by James Philbin, Michael Isard, Josef Sivic, Andrew Zisserman - In CVPR , 2008
"... The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local regions of images are characterized using high-dimensional descriptors which are then mapped to “visual words ” selected ..."
Abstract - Cited by 253 (8 self) - Add to MetaCart
The state of the art in visual object retrieval from large databases is achieved by systems that are inspired by text retrieval. A key component of these approaches is that local regions of images are characterized using high-dimensional descriptors which are then mapped to “visual words ” selected

Real-time visual tracking of complex structures

by Tom Drummond, Roberto Cipolla - IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE , 2002
"... This paper presents a novel framework for three-dimensional model-based tracking. Graphical rendering technology is combined with constrained active contour tracking to create a robust wire-frame tracking system. It operates in real time at video frame rate (25 Hz) on standard hardware. It is based ..."
Abstract - Cited by 226 (7 self) - Add to MetaCart
This paper presents a novel framework for three-dimensional model-based tracking. Graphical rendering technology is combined with constrained active contour tracking to create a robust wire-frame tracking system. It operates in real time at video frame rate (25 Hz) on standard hardware

Relaxation to equilibrium for two dimensional disordered Ising systems in the Griffiths phase

by F. Cesi, C. Maes, F. Martinelli , 1997
"... We consider Glauber--type dynamics for two dimensional disordered magnets of Ising type. We prove that, if in equilibrium the disorder--averaged influence of the boundary condition is sufficiently small, then the corresponding Glauber dynamics is ergodic with probability one and the disorder-average ..."
Abstract - Cited by 11 (6 self) - Add to MetaCart
model. For this model we also rigorously prove the existence of a dynamical phase transition when J crosses the critical value J c for the standard two dimensional Ising model.
Results 1 - 10 of 3,625