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Preference Parameters And Behavioral Heterogeneity: An Experimental Approach In The Health And Retirement Study

by Robert B. Barsky, F. Thomas Juster, Miles S. Kimball, Matthew D. Shapiro , 1997
"... This paper reports measures of preference parameters relating to risk tolerance, time preference, and intertemporal substitution. These measures are based on survey responses to hypothetical situations constructed using an economic theorist's concept of the underlying parameters. The individual ..."
Abstract - Cited by 524 (12 self) - Add to MetaCart
This paper reports measures of preference parameters relating to risk tolerance, time preference, and intertemporal substitution. These measures are based on survey responses to hypothetical situations constructed using an economic theorist's concept of the underlying parameters

Flexible camera calibration by viewing a plane from unknown orientations

by Zhengyou Zhang , 1999
"... We propose a flexible new technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion is modeled ..."
Abstract - Cited by 512 (7 self) - Add to MetaCart
We propose a flexible new technique to easily calibrate a camera. It only requires the camera to observe a planar pattern shown at a few (at least two) different orientations. Either the camera or the planar pattern can be freely moved. The motion need not be known. Radial lens distortion

A Mathematical Introduction to Robotic Manipulation

by Richard M. Murray, Zexiang Li, S. Shankar Sastry , 1994
"... ..."
Abstract - Cited by 1002 (53 self) - Add to MetaCart
Abstract not found

The Coordination of Arm Movements: An Experimentally Confirmed Mathematical Model

by Tamar Flash, Neville Hogans - Journal of neuroscience , 1985
"... This paper presents studies of the coordination of volun-tary human arm movements. A mathematical model is for-mulated which is shown to predict both the qualitative fea-tures and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematic ..."
Abstract - Cited by 663 (18 self) - Add to MetaCart
This paper presents studies of the coordination of volun-tary human arm movements. A mathematical model is for-mulated which is shown to predict both the qualitative fea-tures and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled

Robust Monte Carlo Localization for Mobile Robots

by Sebastian Thrun, Dieter Fox, Wolfram Burgard, Frank Dellaert , 2001
"... Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples), whi ..."
Abstract - Cited by 826 (88 self) - Add to MetaCart
Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples

Good Error-Correcting Codes based on Very Sparse Matrices

by David J.C. MacKay , 1999
"... We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay--Neal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties. The ..."
Abstract - Cited by 741 (23 self) - Add to MetaCart
We study two families of error-correcting codes defined in terms of very sparse matrices. "MN" (MacKay--Neal) codes are recently invented, and "Gallager codes" were first investigated in 1962, but appear to have been largely forgotten, in spite of their excellent properties

Solving multiclass learning problems via error-correcting output codes

by Thomas G. Dietterich, Ghulum Bakiri - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH , 1995
"... Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass l ..."
Abstract - Cited by 730 (8 self) - Add to MetaCart
Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k>2values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hx i;f(x i)i. Existing approaches to multiclass

A Probabilistic Approach to Concurrent Mapping and Localization for Mobile Robots

by Sebastian Thrun, Wolfram Burgard, Dieter Fox, Henry Hexmoor, Maja Mataric - Machine Learning , 1998
"... . This paper addresses the problem of building large-scale geometric maps of indoor environments with mobile robots. It poses the map building problem as a constrained, probabilistic maximum-likelihood estimation problem. It then devises a practical algorithm for generating the most likely map from ..."
Abstract - Cited by 487 (47 self) - Add to MetaCart
data, alog with the most likely path taken by the robot. Experimental results in cyclic environments of size up to 80 by 25 meter illustrate the appropriateness of the approach. Keywords: Bayes rule, expectation maximization, mobile robots, navigation, localization, mapping, maximum likelihood

Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces

by Lydia Kavraki, Petr Svestka, Jean-claude Latombe, Mark Overmars - IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION , 1996
"... A new motion planning method for robots in static workspaces is presented. This method proceeds in two phases: a learning phase and a query phase. In the learning phase, a probabilistic roadmap is constructed and stored as a graph whose nodes correspond to collision-free configurations and whose edg ..."
Abstract - Cited by 1276 (124 self) - Add to MetaCart
nodes. The method is general and easy to implement. It can be applied to virtually any type of holonomic robot. It requires selecting certain parameters (e.g., the duration of the learning phase) whose values depend on the scene, that is the robot and its workspace. But these values turn out

Loopy Belief Propagation for Approximate Inference: An Empirical Study

by Kevin P. Murphy, Yair Weiss, Michael I. Jordan - In Proceedings of Uncertainty in AI , 1999
"... Recently, researchers have demonstrated that "loopy belief propagation" --- the use of Pearl's polytree algorithm in a Bayesian network with loops --- can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performa ..."
Abstract - Cited by 680 (18 self) - Add to MetaCart
Recently, researchers have demonstrated that "loopy belief propagation" --- the use of Pearl's polytree algorithm in a Bayesian network with loops --- can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon
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