We give a new model of learning motivated by smoothed analysis (Spielman and Teng, 2001). In this model, we analyze two new algorithms, for PAC-learning DNFs and agnostically learn...
Adam Tauman Kalai, Alex Samorodnitsky, Shang-Hua T...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
This paper describes the formal verification of the recently introduced Dual Transition Petri Net (DTPN) models [12], using model checking techniques. The methodology presented a...
Mauricio Varea, Bashir M. Al-Hashimi, Luis Alejand...
During the past ten years, a large number of quality models have been proposed in the literature. In general, the goal of these models is to predict a quality factor starting from...
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...