While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...
The rising awareness of the challenges of preserving information over the long term has led to a wealth of initiatives developing economic models, methods, tools, systems, guideli...
The detection of laughter in conversational interaction presents an important challenge in meeting understanding, important primarily because laughter is predictive of the emotion...
We analyze the performance of protocols for load balancing in distributed systems based on no-regret algorithms from online learning theory. These protocols treat load balancing a...
Constraining and input biasing are frequently used techniques in functional verification methodologies based on randomized simulation generation. Constraints confine the simulatio...
Jun Yuan, Kurt Shultz, Carl Pixley, Hillel Miller,...