Boltzmann machines are often used as building blocks in greedy learning of deep networks. However, training even a simplified model, known as restricted Boltzmann machine, can be extremely laborious: Traditional learning algorithms often converge only with the right choice of the learning rate scheduling and the scale of the initial weights. They are also sensitive to specific data representati...

We consider online routing algorithms for finding paths between the vertices of plane graphs. We show (1) there exists a routing algorithm for arbitrary triangulations that has no memory and uses no randomization, (2) no equivalent result is possible for convex subdivisions, (3) there is no competitive online routing algorithm under the Euclidean distance metric in arbitrary triangulations, and...

For any graph F and any integer r ≥ 2, the online vertex-Ramsey density of F and r, denoted m∗(F, r), is a parameter defined via a deterministic two-player Ramsey-type game (Painter vs. Builder). This parameter was introduced in a recent paper [arXiv:1103.5849 ], where it was shown that the online vertex-Ramsey density determines the threshold of a similar probabilistic one-player game (Painter...

Developing coodination among groups of agents is a big challenge in multi-agent systems. An appropriate enviroment to test new solutions is the prey-predator pursuit problem. As it is stated many times in literature, algorithms and conclusions obtained in this environment can be extended and applied to many particular problems. The first solutions for this problem proposed greedy algorithms tha...

The prey-predator pursuit problem is a generic multi-agent testbed referenced many times in literature. Algorithms and conclusions obtained in this domain can be extended and applied to many particular problems. In first place, greedy algorithms seem to do the job. But when concurrence problems arise, agent communication and coordination is needed to get a reasonable solution. It is quite popul...

This paper present two meta heuristics, reverse greedy and future aware greedy, which are variants of the greedy algorithm. Both are based on the observation that guessing the impact of future selections is useful for the current selection. While the greedy algorithm makes the best local selection given the past, future aware greedy makes the best local selection given the past and the estimate...

We introduce herein a new approach to nonparametric multi-armed bandit theory involving both the and covariate processes. Following Berry et al. (1997), we assume non-denumerable set of arms for process. The develop can be readily extended continuous-time processes by using ?-greedy randomization arm elimination instead dynamic allocation indices. It also carries out stochastic search with O(1)...

The airport transportation network structure and its performance are key factors to benefit the local area or national transportation capability and economic development. This paper presents a method based on the weighted algebraic connectivity to optimize and analyze the network. The indispensability of the weighted adjacent matrix and weighted Laplacian matrix in airport transportation networ...