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An Analytical Method To Eliminate The Redundant Parameters In Robot Calibration
"... Model based error compensation of a robotic manipulator, also known as robot calibration, requires the identification of its generalized errors. These errors are found from measured data and used to predict, and compensate for, the endpoint errors as a function of configuration. However, the genera ..."
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Cited by 6 (3 self)
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, the generalized error formulation introduces redundant parameters, often nonintuitive, that may compromise the robustness of the calibration. The existing numerical methods to eliminate such errors are formulated on a casebycase basis. In this paper, the general analytical expressions and physical
Some studies in machine learning using the game of Checkers
 IBM JOURNAL OF RESEARCH AND DEVELOPMENT
, 1959
"... Two machinelearning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it will learn to play a better game of checkers than can be played by the person who wrote the program. Furthermor ..."
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Cited by 780 (0 self)
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. Furthermore, it can learn to do this in a remarkably short period of time (8 or 10 hours of machineplaying time) when given only the rules of the game, a sense of direction, and a redundant and incomplete list of parameters which are thought to have something to do with the game, but whose correct signs
The SPLASH2 programs: Characterization and methodological considerations
 INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE
, 1995
"... The SPLASH2 suite of parallel applications has recently been released to facilitate the study of centralized and distributed sharedaddressspace multiprocessors. In this context, this paper has two goals. One is to quantitatively characterize the SPLASH2 programs in terms of fundamental propertie ..."
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Cited by 1420 (12 self)
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scale with problem size and the number of processors. The other, related goal is methodological: to assist people who will use the programs in architectural evaluations to prune the space of application and machine parameters in an informed and meaningful way. For example, by characterizing the working
Redundant
"... Abstract. A robust structural damage detection method that can handle noisy frequency response function information is discussed. The inherent unstructured nature of damage detection problems is exploited by applying an implicit redundant representation (IRR) genetic algorithm. The unbraced frame st ..."
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Abstract. A robust structural damage detection method that can handle noisy frequency response function information is discussed. The inherent unstructured nature of damage detection problems is exploited by applying an implicit redundant representation (IRR) genetic algorithm. The unbraced frame
The Coverage Problem in a Wireless Sensor Network
, 2005
"... One of the fundamental issues in sensor networks is the coverage problem, which reflects how well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the service area of the sensor ne ..."
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Cited by 292 (8 self)
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network is covered by at least k sensors, where k is a given parameter. The sensing ranges of sensors can be unit disks or nonunit disks. We present polynomialtime algorithms, in terms of the number of sensors, that can be easily translated to distributed protocols. The result is a generalization
Cryptanalysis of block ciphers with overdefined systems of equations
, 2002
"... Abstract. Several recently proposed ciphers, for example Rijndael and Serpent, are built with layers of small Sboxes interconnected by linear keydependent layers. Their security relies on the fact, that the classical methods of cryptanalysis (e.g. linear or differential attacks) are based on proba ..."
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Cited by 253 (22 self)
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the sparsity of the equations and their specific structure. The XSL attack uses only relations true with probability 1, and thus the security does not have to grow exponentially in the number of rounds. XSL has a parameter P, and from our estimations is seems that P should be a constant or grow very slowly
The ContextTree Weighting Method: Basic Properties
 IEEE Trans. Inform. Theory
, 1995
"... We describe a sequential universal data compression procedure for binary tree sources that performs the "double mixture." Using a context tree, this method weights in an efficient recursive way the coding distributions corresponding to all bounded memory tree sources, and achieves a desira ..."
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Cited by 230 (18 self)
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desirable coding distribution for tree sources with an unknown model and unknown parameters. Computational and storage complexity of the proposed procedure are both linear in the source sequence length. We derive a natural upper bound on the cumulative redundancy of our method for individual sequences
Hidden Markov Model induction by Bayesian model merging
 Advances in Neural Information Processing Systems 5
, 1993
"... Abstract This paper describes a technique for learning both the number of states and the topology of Hidden Markov Models from examples. The induction process starts with the most specific model consistent with the training data and generalizes by successively merging states. Both the choice of sta ..."
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Cited by 162 (3 self)
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of states to merge and the stopping criterion are guided by the Bayesian posterior probability. We compare our algorithm with the BaumWelch method of estimating fixedsize models, and find that it can induce minimal HMMs from data in cases where fixed estimation does not converge or requires redundant
Parameter identifiability and redundancy: theoretical considerations
 PloS one
"... Abstract In this paper we outline general considerations on parameter identifiability, and introduce the notion of weak local identifiability and gradient weak local identifiability. These are based on local properties of the likelihood, in particular the rank of the Hessian matrix. We relate these ..."
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Cited by 1 (0 self)
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these to the notions of parameter identifiability and redundancy previously introduced by Rothenberg (Econometrica 39 (1971) 577591) and Catchpole and Morgan (Biometrika 84 (1997) 187196). Within certain special classes of exponential family models, gradient weak local identifiability is shown to be equivalent
A probabilistic model of redundancy in information extraction
 IN IJCAI
, 2005
"... Unsupervised Information Extraction (UIE) is the task of extracting knowledge from text without using handtagged training examples. A fundamental problem for both UIE and supervised IE is assessing the probability that extracted information is correct. In massive corpora such as the Web, the same e ..."
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Cited by 96 (19 self)
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extraction is found repeatedly in different documents. How does this redundancy impact the probability of correctness? This paper introduces a combinatorial “ballsandurns” model that computes the impact of sample size, redundancy, and corroboration from multiple distinct extraction rules on the probability
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