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We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solutio ...
Mainstream surrogate approaches for multi-objective problems build one approximation for each objective. Mono-surrogate approaches instead aim at characterizing the Pareto front with a single model. Such an approach has been recently introduced using a mix ...
Linearizability is a key design methodology for reasoning about implementations of concurrent abstract data types in both shared memory and message passing systems. It provides the illusion that operations execute sequentially and fault-free, despite the a ...
In this paper, we study the problem of optimizing (fine-tuning) the design parameters of large-scale traffic control systems that are composed of distinct and mutually interacting modules. This problem usually requires a considerable amount of human effort ...
Institute of Electrical and Electronics Engineers2011
In many real-life optimization problems involving multiple agents, the rewards are not necessarily known exactly in advance, but rather depend on sources of exogenous uncertainty. For instance, delivery companies might have to coordinate to choose who shou ...
This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and ...
We study averaging algorithms in time-varying networks, and means tomeasure their performance. We present sufficient conditions on these algorithms, which ensure they lead to computation at each node, of the global average of measurements provided by each ...
We propose a new trust region based optimization algorithm for solving unconstrained nonlinear problems whose second derivatives matrix is singular at a local solution. We give a theoretical characterization of the singularity in this context and we propos ...
We present an extension of a classical data management subproblem, the page migration. The problem is investigated in dynamic networks, where costs of communication between different nodes may change with time. We construct asymptotically optimal online al ...
Econometric models play an important role in transportation analysis. Estimating more and more complex models becomes problematic. The associated log-likelihood function is highly nonlinear and non concave and the comlexity of the model requires constraint ...
