@inproceedings{2891,
abstract = {Quantitative automata are nondeterministic finite automata with edge weights. They value a
run by some function from the sequence of visited weights to the reals, and value a word by its
minimal/maximal run. They generalize boolean automata, and have gained much attention in
recent years. Unfortunately, important automaton classes, such as sum, discounted-sum, and
limit-average automata, cannot be determinized. Yet, the quantitative setting provides the potential
of approximate determinization. We define approximate determinization with respect to
a distance function, and investigate this potential.
We show that sum automata cannot be determinized approximately with respect to any
distance function. However, restricting to nonnegative weights allows for approximate determinization
with respect to some distance functions.
Discounted-sum automata allow for approximate determinization, as the influence of a word’s
suffix is decaying. However, the naive approach, of unfolding the automaton computations up
to a sufficient level, is shown to be doubly exponential in the discount factor. We provide an
alternative construction that is singly exponential in the discount factor, in the precision, and
in the number of states. We prove matching lower bounds, showing exponential dependency on
each of these three parameters.
Average and limit-average automata are shown to prohibit approximate determinization with
respect to any distance function, and this is the case even for two weights, 0 and 1.},
author = {Boker, Udi and Henzinger, Thomas A},
booktitle = {Leibniz International Proceedings in Informatics},
location = {Hyderabad, India},
pages = {362 -- 373},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik},
title = {{Approximate determinization of quantitative automata}},
doi = {10.4230/LIPIcs.FSTTCS.2012.362},
volume = {18},
year = {2012},
}
@article{2902,
abstract = {We present an algorithm for simplifying linear cartographic objects and results obtained with a computer program implementing this algorithm. },
author = {Edelsbrunner, Herbert and Musin, Oleg and Ukhalov, Alexey and Yakimova, Olga and Alexeev, Vladislav and Bogaevskaya, Victoriya and Gorohov, Andrey and Preobrazhenskaya, Margarita},
journal = {Modeling and Analysis of Information Systems},
number = {6},
pages = {152 -- 160},
publisher = {Technische Universität Darmstadt},
title = {{Fractal and computational geometry for generalizing cartographic objects}},
volume = {19},
year = {2012},
}
@inproceedings{2903,
abstract = {In order to enjoy a digital version of the Jordan Curve Theorem, it is common to use the closed topology for the foreground and the open topology for the background of a 2-dimensional binary image. In this paper, we introduce a single topology that enjoys this theorem for all thresholds decomposing a real-valued image into foreground and background. This topology is easy to construct and it generalizes to n-dimensional images.},
author = {Edelsbrunner, Herbert and Symonova, Olga},
location = {New Brunswick, NJ, USA },
pages = {41 -- 48},
publisher = {IEEE},
title = {{The adaptive topology of a digital image}},
doi = {10.1109/ISVD.2012.11},
year = {2012},
}
@article{2904,
abstract = {Generalized van der Corput sequences are onedimensional, infinite sequences in the unit interval. They are generated from permutations in integer base b and are the building blocks of the multi-dimensional Halton sequences. Motivated by recent progress of Atanassov on the uniform distribution behavior of Halton sequences, we study, among others, permutations of the form P(i) = ai (mod b) for coprime integers a and b. We show that multipliers a that either divide b - 1 or b + 1 generate van der Corput sequences with weak distribution properties. We give explicit lower bounds for the asymptotic distribution behavior of these sequences and relate them to sequences generated from the identity permutation in smaller bases, which are, due to Faure, the weakest distributed generalized van der Corput sequences.},
author = {Pausinger, Florian},
issn = {2118-8572},
journal = {Journal de Theorie des Nombres des Bordeaux},
number = {3},
pages = {729 -- 749},
publisher = {Universite de Bordeaux},
title = {{Weak multipliers for generalized van der Corput sequences}},
doi = {10.5802/jtnb.819},
volume = {24},
year = {2012},
}
@article{2912,
author = {Edelsbrunner, Herbert and Strelkova, Nataliya},
journal = { Uspekhi Mat. Nauk},
number = {6},
pages = {203 -- 204},
publisher = {Moscow Mathematical Society },
title = {{Configuration space for shortest networks }},
doi = {10.4213/rm9503},
volume = {67},
year = {2012},
}
@inproceedings{2915,
author = {Kroemer, Oliver and Lampert, Christoph and Peters, Jan},
publisher = {Deutsches Zentrum für Luft und Raumfahrt},
title = {{Multi-modal learning for dynamic tactile sensing}},
year = {2012},
}
@unpublished{2928,
abstract = { This paper addresses the problem of approximate MAP-MRF inference in general graphical models. Following [36], we consider a family of linear programming relaxations of the problem where each relaxation is specified by a set of nested pairs of factors for which the marginalization constraint needs to be enforced. We develop a generalization of the TRW-S algorithm [9] for this problem, where we use a decomposition into junction chains, monotonic w.r.t. some ordering on the nodes. This generalizes the monotonic chains in [9] in a natural way. We also show how to deal with nested factors in an efficient way. Experiments show an improvement over min-sum diffusion, MPLP and subgradient ascent algorithms on a number of computer vision and natural language processing problems. },
author = {Kolmogorov, Vladimir and Schoenemann, Thomas},
booktitle = {arXiv},
pages = {16},
publisher = {ArXiv},
title = {{Generalized sequential tree-reweighted message passing}},
year = {2012},
}
@inproceedings{2930,
abstract = {In this paper we investigate k-submodular functions. This natural family of discrete functions includes submodular and bisubmodular functions as the special cases k = 1 and k = 2 respectively.
In particular we generalize the known Min-Max-Theorem for submodular and bisubmodular functions. This theorem asserts that the minimum of the (bi)submodular function can be found by solving a maximization problem over a (bi)submodular polyhedron. We define a k-submodular polyhedron, prove a Min-Max-Theorem for k-submodular functions, and give a greedy algorithm to construct the vertices of the polyhedron.
},
author = {Huber, Anna and Kolmogorov, Vladimir},
location = {Athens, Greece},
pages = {451 -- 462},
publisher = {Springer},
title = {{Towards minimizing k-submodular functions}},
doi = {10.1007/978-3-642-32147-4_40},
volume = {7422},
year = {2012},
}
@article{2931,
abstract = {In this paper, we present a new approach for establishing correspondences between sparse image features related by an unknown nonrigid mapping and corrupted by clutter and occlusion, such as points extracted from images of different instances of the same object category. We formulate this matching task as an energy minimization problem by defining an elaborate objective function of the appearance and the spatial arrangement of the features. Optimization of this energy is an instance of graph matching, which is in general an NP-hard problem. We describe a novel graph matching optimization technique, which we refer to as dual decomposition (DD), and demonstrate on a variety of examples that this method outperforms existing graph matching algorithms. In the majority of our examples, DD is able to find the global minimum within a minute. The ability to globally optimize the objective allows us to accurately learn the parameters of our matching model from training examples. We show on several matching tasks that our learned model yields results superior to those of state-of-the-art methods.
},
author = {Torresani, Lorenzo and Kolmogorov, Vladimir and Rother, Carsten},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
number = {2},
pages = {259 -- 271},
publisher = {IEEE},
title = {{A dual decomposition approach to feature correspondence}},
doi = {10.1109/TPAMI.2012.105},
volume = {35},
year = {2012},
}
@inproceedings{2916,
abstract = {The classical (boolean) notion of refinement for behavioral interfaces of system components is the alternating refinement preorder. In this paper, we define a quantitative measure for interfaces, called interface simulation distance. It makes the alternating refinement preorder quantitative by, intu- itively, tolerating errors (while counting them) in the alternating simulation game. We show that the interface simulation distance satisfies the triangle inequality, that the distance between two interfaces does not increase under parallel composition with a third interface, and that the distance between two interfaces can be bounded from above and below by distances between abstractions of the two interfaces. We illustrate the framework, and the properties of the distances under composition of interfaces, with two case studies.},
author = {Cerny, Pavol and Chmelik, Martin and Henzinger, Thomas A and Radhakrishna, Arjun},
booktitle = {Electronic Proceedings in Theoretical Computer Science},
location = {Napoli, Italy},
pages = {29 -- 42},
publisher = {EPTCS},
title = {{Interface Simulation Distances}},
doi = {10.4204/EPTCS.96.3},
volume = {96},
year = {2012},
}