We derive generalization bounds for learning algorithms based on their robustness: the property that if a testing sample is "similar" to a training sample, then the test...
Increasingly advances in file carving, memory analysis and network forensics requires the ability to identify the underlying type of a file given only a file fragment. Work to dat...
Many popular optimization algorithms, like the Levenberg-Marquardt algorithm (LMA), use heuristic-based "controllers" that modulate the behavior of the optimizer during ...
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
An emerging trend in classrooms is the use of networked visual argumentation tools that allow students to discuss, debate, and argue with one another in a synchronous fashion about...