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We show aging of Glauber-type dynamics on the random energy model, inthe sense that we obtain the annealed scaling limits of the clock process and of theage process. The latter encodes the Gibbs weight of the configuration occupied by thedynamics. Both lim ...
We propose a method for accurate and temporally consistent surface classification in the presence of noisy, irregularly sampled measurements, and apply it to the estimation of snow coverage over time. The input imagery is extremely challenging, with large ...
Symmetric submodular functions are an important family of submodular functions capturing many interesting cases including cut functions of graphs and hypergraphs. In this work, we identify submodular maximization problems for which one can get a better app ...
In the biometrics community, face and speaker recognition are mature fields in which several systems have been proposed over the past twenty years. While existing systems perform well under controlled recording conditions, mismatch caused by the use of dif ...
We present a conditional random field approach to tracking-by-detection in which we model pairwise factors linking pairs of detections and their hidden labels, as well as higher order potentials defined in terms of label costs. To the contrary of previous ...
With widening interests in using model organisms for reverse genetic approaches and biomimmetic micro-robotics, motility phenotyping of the nematode Caenorhabditis elegans is expanding across a growing array of locomotive environments. One ongoing bottlene ...
State-of-the-art phoneme sequence recognition systems are based on hybrid hidden Markov model/artificial neural networks (HMM/ANN) framework. In this framework, the local classifier, ANN, is typically trained using Viterbi expectation-maximization algorith ...
We address the task of identifying people appearing in TV shows. The target persons are all people whose identity is said or written, like the journalists and the well known people, as politicians, athletes, celebrities, etc. In our approach, overlaid name ...
Max-stable processes are the natural analogues of the generalized extreme-value distribution when modelling extreme events in space and time. Under suitable conditions, these processes are asymptotically justified models for maxima of independent replicati ...
Max-stable processes arise as the only possible nontrivial limits for maxima of affinely normalized identically distributed stochastic processes, and thus form an important class of models for the extreme values of spatial processes. Until recently, infere ...