Moving from a broad introduction to the core problems, such as the unpre-dictability of AI outcomes or the dificulty in explaining AI decisions, this book arrives at more complex questions of ownership and …

Most of the information about the future is unpredictable, but not quite everything. The predictions you can make are often far removed from the original question you were trying to answer. A few …

we formulate the unpredictable evolution as a new matrix completion problem and propose an effective method with much smaller observed entries than conventional ones;

“The ultimate vision for the digital twin is to create, test and build our equipment in a virtual environment. Only when we get it to where it performs to our requirements do we physically manufacture it. – John …

In this work, we introduce, for the first time, chaotic learning, a novel multiscale topological paradigm that enables accurate predictions from chaotic systems. We show that seemingly random and …

2 Motivation ed scheduling policy for handling unpredictable, bursty request rates. To meet the SLO of the requests while maximizing the accuracy of the responses, we motivate the use of SuperNets …

We show how one can use machine learning models to leverage information on comparable products from the past together with experts’ forecasts to improve forecasting accuracy.