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Jump to navigationJump to search- 14:44, 3 April 2011 diff hist -239 m Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Used as a Classifier
- 14:43, 3 April 2011 diff hist -1,406 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Hypothesis Test
- 14:43, 3 April 2011 diff hist -534 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Estimation
- 14:43, 3 April 2011 diff hist -239 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Used as a Classifier
- 14:42, 3 April 2011 diff hist -1,406 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Hypothesis Test
- 14:42, 3 April 2011 diff hist -541 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Estimation Methods
- 14:42, 3 April 2011 diff hist -485 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Model Desprition
- 14:42, 3 April 2011 diff hist -583 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Summary
- 14:39, 3 April 2011 diff hist +3,252 N Several methods are used in this paper Created page with 'This paper proposed a discrete temporal model family that is capable of modeling network evolution, while maintaining the flexibility of ERGMs. It also proposed such models to bu…' current
- 14:37, 3 April 2011 diff hist +2,769 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Model Desprition
- 14:33, 3 April 2011 diff hist +58 Steve Hanneke and Eric Xing, Discrete Temporal Models of Social Networks →Summary
- 13:27, 3 April 2011 diff hist +494 N Proposed a discrete temporal model family that is capable of modeling network evolution, while maintaining the flexibility of ERGMs. It also proposed such models to build upon ERGMs as much as possible. Created page with 'This paper proposed to obtain a general model family, which can be used to predict the evolution of network and keep the flexibility of ERGM models at the same time. The mathema…' current
- 13:14, 3 April 2011 diff hist +127 United States 108th Senate, having n = 100 actors. current
- 13:10, 3 April 2011 diff hist +2 United States 108th Senate, having n = 100 actors.
- 13:09, 3 April 2011 diff hist +6 United States 108th Senate, having n = 100 actors.
- 13:08, 3 April 2011 diff hist +1 United States 108th Senate, having n = 100 actors.
- 13:08, 3 April 2011 diff hist +54 N United States 108th Senate, having n = 100 actors. Created page with 'Dataset: United States 108th Senate #Nodes(Actor): 100'
- 13:04, 3 April 2011 diff hist -1,567 Vladimir Ouzienko, Prediction of Attributes and Links in Temporal Social Networks →Brief Description of the tERGM Model Methods
- 13:00, 3 April 2011 diff hist -1,567 Predict the attributes and links in Temporal Social Network. →Brief Description of the tERGM Model Methods current
- 13:00, 3 April 2011 diff hist +1,565 N New model named Temporal Exponential Random Graphical Model(tERGM) Created page with '== '''Brief Description of the tERGM Model Methods''' == This novel Model comes from htERGM Model. However, it has some difference with the htERGM Model in the following aspects:…' current