Context-sensitive Multiple Task Learning, or csMTL, is presented as a method of inductive transfer that uses a single output neural network and additional contextual inputs for le...
Anticipation is a general concept used and applied in various domains. Many studies in the field of artificial intelligence have investigated the capacity for anticipation. In thi...
We present a novel framework for learning to interpret and generate language using only perceptual context as supervision. We demonstrate its capabilities by developing a system t...
Responsive Adaptive Display Anticipates Requests (RADAR) is a domain general system that learns to highlight an individual's preferred information displays, given the current ...
Combinatorial optimization problems naturally arise in many application areas, including logistics, manufacturing, supplychain management, and resource allocation. They often give...