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1,656
Earthquake Shakes Twitter Users: Realtime Event Detection by Social Sensors
 In Proceedings of the Nineteenth International WWW Conference (WWW2010). ACM
, 2010
"... Twitter, a popular microblogging service, has received much attention recently. An important characteristic of Twitter is its realtime nature. For example, when an earthquake occurs, people make many Twitter posts (tweets) related to the earthquake, which enables detection of earthquake occurrence ..."
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Cited by 524 (4 self)
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such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center and the trajectory of the event location. We consider each Twitter user as a sensor and apply Kalman filtering and particle filtering
A Discrete Binary Version of The Particle Swarm Algorithm
 PROC. OF CONF. ON SYSTEM, MAN, AND CYBERNETICS, 4104–4109
, 1997
"... The particle swarm algorithm adjusts the trajectories of a population of “particles” through a problem space on the basis of information about each particle’s previous best performance and the best previous performance of its neighbors. Previous versions of the particle swarm have operated in contin ..."
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Cited by 339 (2 self)
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in continuous space, where trajectories are defined as changes in position on some number of dimensions. The present paper reports a reworking of the algorithm to operate on discrete binary variables. In the binary version, trajectories are changes in the probability that a coordinate will take on a zero or one
Voice puppetry
, 1999
"... Frames from a voicedriven animation, computed from a single baby picture and an adult model of facial control. Note the changes in upper facial expression. See figures 5, 6 and 7 for more examples of predicted mouth shapes. We introduce a method for predicting a control signal from another related ..."
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Cited by 298 (0 self)
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is produced by using audio to drive the model, which induces a probability distribution over the manifold of possible facial motions. We present a lineartime closedform solution for the most probable trajectory over this manifold. The output is a series of facial control parameters, suitable for driving many
Analyzing Developmental Trajectories: A Semiparametric, GroupBased Approach
 Psychological Methods
, 1999
"... A developmental trajectory describes the course of a behavior over age or time. A groupbased method for identifying distinctive groups of individual trajectories within the population and for profiling the characteristics of group members is demonstrated. Such clusters might include groups of & ..."
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Cited by 232 (14 self)
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groups of trajectories, (b) the capability to estimate the proportion of the population following each such trajectory group, (c) the capability to relate group membership probability to individual characteristics and circumstances, and (d) the capability to use the group membership probabilities
An analysis of temporaldifference learning with function approximation
 IEEE Transactions on Automatic Control
, 1997
"... We discuss the temporaldifference learning algorithm, as applied to approximating the costtogo function of an infinitehorizon discounted Markov chain. The algorithm weanalyze updates parameters of a linear function approximator online, duringasingle endless trajectory of an irreducible aperiodi ..."
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Cited by 313 (8 self)
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We discuss the temporaldifference learning algorithm, as applied to approximating the costtogo function of an infinitehorizon discounted Markov chain. The algorithm weanalyze updates parameters of a linear function approximator online, duringasingle endless trajectory of an irreducible
Tractable inference for complex stochastic processes
 In Proc. UAI
, 1998
"... The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system, these tasks typically involve the use of a belief state—a probability distribution over the state of the process at a gi ..."
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Cited by 302 (14 self)
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The monitoring and control of any dynamic system depends crucially on the ability to reason about its current status and its future trajectory. In the case of a stochastic system, these tasks typically involve the use of a belief state—a probability distribution over the state of the process at a
Probability and complex quantum trajectories
, 809
"... It is shown that in the complex trajectory representation of quantum mechanics, the Born’s Ψ ⋆ Ψ probability density can be obtained from the imaginary part of the velocity field of particles on the real axis. Extending this probability axiom to the complex plane, we first attempt to find a probabil ..."
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Cited by 4 (1 self)
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It is shown that in the complex trajectory representation of quantum mechanics, the Born’s Ψ ⋆ Ψ probability density can be obtained from the imaginary part of the velocity field of particles on the real axis. Extending this probability axiom to the complex plane, we first attempt to find a
PROBABILITY CURRENT AND TRAJECTORY REPRESENTATION
, 2000
"... A unified form for real and complex wave functions is proposed for the stationary case, and the quantum HamiltonJacobi equation is derived in the threedimensional space. The difficulties which appear in Bohm’s theory like the vanishing value of the conjugate momentum in the real wave function case ..."
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a rotation of the wave function in the complex space implies that microstates do not appear. For bound states, it is shown that some freedom subsists and gives rise to the manifestation of microstates not detected by the Schrödinger wave function. Key words: probability current, quantum Hamilton
On Learning, Representing and Generalizing a Task in a Humanoid Robot
 IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS, PART B. SPECIAL
, 2007
"... We present a programmingbydemonstration framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a series of experiments, in which a human demonstra ..."
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Cited by 239 (48 self)
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strator teaches a humanoid robot simple manipulatory tasks. A probabilitybased estimation of the relevance is suggested by first projecting the motion data onto a generic latent space using principal component analysis. The resulting signals are encoded using a mixture of Gaussian/Bernoulli distributions
Trajectory versus probability density entropy
, 2008
"... We study the problem of entropy increase of the Bernoullishift map without recourse to the concept of trajectory and we discuss whether, and under which conditions if it does, the distribution density entropy coincides with the KolmogorovSinai entropy, namely, with the trajectory entropy. ..."
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We study the problem of entropy increase of the Bernoullishift map without recourse to the concept of trajectory and we discuss whether, and under which conditions if it does, the distribution density entropy coincides with the KolmogorovSinai entropy, namely, with the trajectory entropy.
Results 1  10
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