Predicting Human Intention in Visual Observations of
... where uk and Σk are the mean and covariance of each Gaussian component, and λk are the mixing weights. The parameters of the mixture model are learned using a standard EM approach. Given the GMM model, a continuous data point x is converted to a soft discrete evidence y = [y1 , y2 , ..., yK ]T , whe ...
... where uk and Σk are the mean and covariance of each Gaussian component, and λk are the mixing weights. The parameters of the mixture model are learned using a standard EM approach. Given the GMM model, a continuous data point x is converted to a soft discrete evidence y = [y1 , y2 , ..., yK ]T , whe ...
ppt - hkust cse
... Y2=s2: people with good education and good income; Y2=s3: people with poor education and average income ...
... Y2=s2: people with good education and good income; Y2=s3: people with poor education and average income ...
Higgs doublet model
... The cutoff should not be so small. Otherwise, such a model is unlikely to be valid in the LHC physics… ...
... The cutoff should not be so small. Otherwise, such a model is unlikely to be valid in the LHC physics… ...
Information Integration Over Time in Unreliable
... one of HSMM inference, it has many distinguishing characteristics. First, not every hidden state Z(i) emits an observation; we have to deal with missing values. Moreover, some hidden states emit multiple observations (when multiple stream updates are mapped to the same Z(i)). Second, Z(i) values are ...
... one of HSMM inference, it has many distinguishing characteristics. First, not every hidden state Z(i) emits an observation; we have to deal with missing values. Moreover, some hidden states emit multiple observations (when multiple stream updates are mapped to the same Z(i)). Second, Z(i) values are ...
lift - Hong Kong University of Science and Technology
... Whether a relation should be in precondition of A, or effect of A, or not Constraints on relations can be integrated into a global optimization formula Maximum Satisfiability Problem One-class Relational Learning Testing Correctness Conciseness ...
... Whether a relation should be in precondition of A, or effect of A, or not Constraints on relations can be integrated into a global optimization formula Maximum Satisfiability Problem One-class Relational Learning Testing Correctness Conciseness ...
A Probabilistic Analysis for the Range Assignment - IIT-CNR
... In [14], Ramanathan and Rosales-Hain considered the problem of minimizing the maximum of node transmitting ranges while achieving connectedness. They also considered the stronger requirement of bi-connectivity. They present centralized topology control algorithms that provide the optimal solution fo ...
... In [14], Ramanathan and Rosales-Hain considered the problem of minimizing the maximum of node transmitting ranges while achieving connectedness. They also considered the stronger requirement of bi-connectivity. They present centralized topology control algorithms that provide the optimal solution fo ...
Traffic demands
... Local policies for path selection (which to use?) Local policies for route propagation (who to tell?) Policies configured by the AS’s network operator ...
... Local policies for path selection (which to use?) Local policies for route propagation (who to tell?) Policies configured by the AS’s network operator ...
Identifying and Overcoming Common Data Mining Mistakes
... one nontrivial level. If only one dominant level appears, the variable is highly likely to be useless in any model since a large portion of the observations cannot be differentiated with respect to this variable. However, in the case of modeling rare events, it is still possible that an infrequently ...
... one nontrivial level. If only one dominant level appears, the variable is highly likely to be useless in any model since a large portion of the observations cannot be differentiated with respect to this variable. However, in the case of modeling rare events, it is still possible that an infrequently ...
presentation source
... – 98% of all traffic (bytes) associated with a set of egress links – 95-99% of traffic consistent with an OSPF simulator Disambiguating outbound traffic – 67% of traffic associated with a single ingress link – 33% of traffic split across multiple ingress (typically, same city!) Inbound and trans ...
... – 98% of all traffic (bytes) associated with a set of egress links – 95-99% of traffic consistent with an OSPF simulator Disambiguating outbound traffic – 67% of traffic associated with a single ingress link – 33% of traffic split across multiple ingress (typically, same city!) Inbound and trans ...
![OC-2 Wind-driven Ocean Circulation [text KKC, pp.80-85]](http://s1.studyres.com/store/data/008502887_1-6ef66b62825062dfd75ea5af20713ce0-300x300.png)
Computer simulation
A computer simulation is a simulation, run on a single computer, or a network of computers, to reproduce behavior of a system. The simulation uses an abstract model (a computer model, or a computational model) to simulate the system. Computer simulations have become a useful part of mathematical modeling of many natural systems in physics (computational physics), astrophysics, climatology, chemistry and biology, human systems in economics, psychology, social science, and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.Computer simulations vary from computer programs that run a few minutes to network-based groups of computers running for hours to ongoing simulations that run for days. The scale of events being simulated by computer simulations has far exceeded anything possible (or perhaps even imaginable) using traditional paper-and-pencil mathematical modeling. Over 10 years ago, a desert-battle simulation of one force invading another involved the modeling of 66,239 tanks, trucks and other vehicles on simulated terrain around Kuwait, using multiple supercomputers in the DoD High Performance Computer Modernization ProgramOther examples include a 1-billion-atom model of material deformation; a 2.64-million-atom model of the complex maker of protein in all organisms, a ribosome, in 2005;a complete simulation of the life cycle of Mycoplasma genitalium in 2012; and the Blue Brain project at EPFL (Switzerland), begun in May 2005 to create the first computer simulation of the entire human brain, right down to the molecular level.Because of the computational cost of simulation, computer experiments are used to perform inference such as uncertainty quantification.