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Omid Askarisichani
University of California, Santa Barbara
2Publications
Publications 2
Newest
#1Omid Askarisichani (UCSB: University of California, Santa Barbara)
#2Jacqueline Ng Lane (Harvard University)
Last.Brian Uzzi (NU: Northwestern University)H-Index: 34
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Polarization affects many forms of social organization. A key issue focuses on which affective relationships are prone to change and how their change relates to performance. In this study, we analyze a financial institutional over a two-year period that employed 66 day traders, focusing on links between changes in affective relations and trading performance. Traders’ affective relations were inferred from their IMs (>2 million messages) and trading performance was measured from profit and loss s...
#2Omid Askarisichani (UCSB: University of California, Santa Barbara)
Last.Ambuj K. Singh (UCSB: University of California, Santa Barbara)H-Index: 33
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In many real-world big data applications, the data distribution is not homogeneous over entire data, but instead varies across groups/clusters of data samples. Although a model’s predictive performance remains vital, there is also a need to learn succinct sets of features that evolve and capture smooth variations in data distribution. These small sets of features not only lead to high prediction accuracy, but also discover the important underlying processes. We investigate this challenging probl...
#1Victor AmelkinH-Index: 3
Last.Ambuj K. SinghH-Index: 33
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Today, many complex tasks are assigned to teams, rather than individuals. One reason for teaming up is expansion of the skill coverage of each individual to the joint team skill set. However, numerous empirical studies of human groups suggest that the performance of equally skilled teams can widely differ. Two natural question arise: What are the factors defining team performance? and How can we best predict the performance of a given team on a specific task? While the team members’ task-related...
#1Omid AskariSichani (Sharif University of Technology)H-Index: 2
#2Mahdi Jalili (Sharif University of Technology)H-Index: 23
A small number of informed agents can control opinion formation in complex networks.To infuence the society, we affect the nodes with small degrees are connected to hubs.Small in-degree with large out-degree provides efficient influence and propagation.Informed agents are more infuential in disassortative networks than assortative ones.The proposed method is more effective than using high centrality in opinion formation. Control of collective behavior is one of the most desirable goals in many a...
#1Omid AskariSichani (Sharif University of Technology)H-Index: 2
#2Mahdi Jalili (Sharif University of Technology)H-Index: 23
Purpose: Large-scale optimization tasks have many applications in science and engineering. There are many algorithms to perform such optimization tasks. In this manuscript, we aim at using consensus in multi-agent systems as a tool for solving large-scale optimization tasks. Method: The model is based on consensus of opinions among agents interacting over a complex networked structure. For each optimization task, a number of agents are considered, each with an opinion value. These agents interac...
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