We consider the problems arising from using sequences of experiments to discover the causal structure among a set of variables, none of whom are known ahead of time to be an "...
Abstract The problem of generating uniform deterministic samples over the rotation group, SO(3), is fundamental to many fields, such as computational structural biology, robotics,...
Anna Yershova, Swati Jain, Steven M. LaValle, Juli...
Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
Recently, there has been much excitement in the research community over using social networks to mitigate multiple identity, or Sybil, attacks. A number of schemes have been propo...
Bimal Viswanath, Ansley Post, P. Krishna Gummadi, ...
Recent research in multi-robot exploration and mapping has focused on sampling environmental fields, which are typically modeled using the Gaussian process (GP). Existing informa...