on the ordering of decision variables in the graph. Although a function requires, in the worst case, a graph of size exponential in the number of arguments, many of the functions encountered in typical applications have a more reasonable representation. Our algorithms have time complexity proportional

behind the wheel without interfering with his driving. In this paper I have developed a system that can monitor the alertness of drivers in order to prevent people from falling asleep at the wheel. The other main aim of this algorithm is to have efficient performance on low quality webcam and without

-state approach, two-way signaling message exchanges, receiver-based resource reservation, and being independent from all other related components in a QOS support architecture, such as flow-specification, admission control, scheduling algorithm, and routing. As stated in the article, “RSVP is primarily a vehicle

important because efficiency demands operating points on or close to the boundary of the set of admissible states and controls. In this review, we focus on model predictive control of constrained systems, both linear and nonlinear and discuss only briefly model predictive control of unconstrained nonlinear

We introduce a compact graph-theoretic representation for multi-party game theory. Our main result is a provably correct and efficient algorithm for computing approximate Nash equilibria in one-stage games represented by trees or sparse graphs.

is not admissible and the search algorithms are not optimal. In this paper we address this problem. We formulate a new admissible heuristic for planning, use it to guide an ida search, and empirically evaluate the resulting optimal planner over a number of domains. The main contribution is the idea underlying

regression models and present an efficient algorithm, that is especially suitable for high dimensional problems, which can also be applied to generalized linear models to solve the corresponding convex optimization problem. The group lasso estimator for logistic regression is shown to be statistically

The two dominant schemes for rule-learning, C4.5 and RIPPER, both operate in two stages. First they induce an initial rule set and then they refine it using a rather complex optimization stage that discards (C4.5) or adjusts (RIPPER) individual rules to make them work better together. In contrast

, the network must offer a service which can provide deterministic guarantees for the maximum delay ofpackets from all connections, referred to as bounded delay service. The admission control functions in a network with a bounded delay service must have available schedulability conditions that detect violations

-to-one correspondence between semantic labels and semantic classes, a minimum probability of error annotation and retrieval are feasible with algorithms that are 1) conceptually simple, 2) computationally efficient, and 3) do not require prior semantic segmentation of training images. In particular, images