Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
: The integration of different learning and adaptation techniques to overcome individual limitations and to achieve synergetic effects through the hybridization or fusion of these ...
Distributed Denial-of-Service (DDoS) attacks have emerged as a popular means of causing mass targeted service disruptions, often for extended periods of time. The relative ease an...
The increasing complexity of clinical trials has generated an enormous requirement for knowledge and information specification at all stages of the trials, including planning, doc...
Ravi D. Shankar, Susana B. Martins, Martin J. O'Co...
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...