@misc{5396,
abstract = {We consider the problem of inference in agraphical model with binary variables. While in theory it is arguably preferable to compute marginal probabilities, in practice researchers often use MAP inference due to the availability of efficient discrete optimization algorithms. We bridge the gap between the two approaches by introducing the Discrete Marginals technique in which approximate marginals are obtained by minimizing an objective function with unary and pair-wise terms over a discretized domain. This allows the use of techniques originally devel-oped for MAP-MRF inference and learning. We explore two ways to set up the objective function - by discretizing the Bethe free energy and by learning it from training data. Experimental results show that for certain types of graphs a learned function can out-perform the Bethe approximation. We also establish a link between the Bethe free energy and submodular functions.},
author = {Korc, Filip and Kolmogorov, Vladimir and Lampert, Christoph},
issn = {2664-1690},
pages = {13},
publisher = {IST Austria},
title = {{Approximating marginals using discrete energy minimization}},
doi = {10.15479/AT:IST-2012-0003},
year = {2012},
}
@inbook{5745,
author = {Gupta, Ashutosh},
booktitle = {Automated Technology for Verification and Analysis},
isbn = {9783642333859},
issn = {0302-9743},
location = {Thiruvananthapuram, Kerala, India},
pages = {107--121},
publisher = {Springer Berlin Heidelberg},
title = {{Improved Single Pass Algorithms for Resolution Proof Reduction}},
doi = {10.1007/978-3-642-33386-6_10},
volume = {7561},
year = {2012},
}
@article{3249,
abstract = {Boolean notions of correctness are formalized by preorders on systems. Quantitative measures of correctness can be formalized by real-valued distance functions between systems, where the distance between implementation and specification provides a measure of "fit" or "desirability". We extend the simulation preorder to the quantitative setting by making each player of a simulation game pay a certain price for her choices. We use the resulting games with quantitative objectives to define three different simulation distances. The correctness distance measures how much the specification must be changed in order to be satisfied by the implementation. The coverage distance measures how much the implementation restricts the degrees of freedom offered by the specification. The robustness distance measures how much a system can deviate from the implementation description without violating the specification. We consider these distances for safety as well as liveness specifications. The distances can be computed in polynomial time for safety specifications, and for liveness specifications given by weak fairness constraints. We show that the distance functions satisfy the triangle inequality, that the distance between two systems does not increase under parallel composition with a third system, and that the distance between two systems can be bounded from above and below by distances between abstractions of the two systems. These properties suggest that our simulation distances provide an appropriate basis for a quantitative theory of discrete systems. We also demonstrate how the robustness distance can be used to measure how many transmission errors are tolerated by error correcting codes.},
author = {Cerny, Pavol and Henzinger, Thomas A and Radhakrishna, Arjun},
journal = {Theoretical Computer Science},
number = {1},
pages = {21 -- 35},
publisher = {Elsevier},
title = {{Simulation distances}},
doi = {10.1016/j.tcs.2011.08.002},
volume = {413},
year = {2012},
}
@article{2950,
abstract = {Contractile actomyosin rings drive various fundamental morphogenetic processes ranging from cytokinesis to wound healing. Actomyosin rings are generally thought to function by circumferential contraction. Here, we show that the spreading of the enveloping cell layer (EVL) over the yolk cell during zebrafish gastrulation is driven by a contractile actomyosin ring. In contrast to previous suggestions, we find that this ring functions not only by circumferential contraction but also by a flow-friction mechanism. This generates a pulling force through resistance against retrograde actomyosin flow. EVL spreading proceeds normally in situations where circumferential contraction is unproductive, indicating that the flow-friction mechanism is sufficient. Thus, actomyosin rings can function in epithelial morphogenesis through a combination of cable-constriction and flow-friction mechanisms.},
author = {Behrndt, Martin and Salbreux, Guillaume and Campinho, Pedro and Hauschild, Robert and Oswald, Felix and Roensch, Julia and Grill, Stephan and Heisenberg, Carl-Philipp J},
journal = {Science},
number = {6104},
pages = {257 -- 260},
publisher = {American Association for the Advancement of Science},
title = {{Forces driving epithelial spreading in zebrafish gastrulation}},
doi = {10.1126/science.1224143},
volume = {338},
year = {2012},
}
@misc{5377,
abstract = {Two-player games on graphs are central in many problems in formal verification and program analysis such as synthesis and verification of open systems. In this work we consider solving recursive game graphs (or pushdown game graphs) that can model the control flow of sequential programs with recursion. While pushdown games have been studied before with qualitative objectives, such as reachability and ω-regular objectives, in this work we study for the first time such games with the most well-studied quantitative objective, namely, mean-payoff objectives. In pushdown games two types of strategies are relevant: (1) global strategies, that depend on the entire global history; and (2) modular strategies, that have only local memory and thus do not depend on the context of invocation, but only on the history of the current invocation of the module. Our main results are as follows: (1) One-player pushdown games with mean-payoff objectives under global strategies are decidable in polynomial time. (2) Two- player pushdown games with mean-payoff objectives under global strategies are undecidable. (3) One-player pushdown games with mean-payoff objectives under modular strategies are NP- hard. (4) Two-player pushdown games with mean-payoff objectives under modular strategies can be solved in NP (i.e., both one-player and two-player pushdown games with mean-payoff objectives under modular strategies are NP-complete). We also establish the optimal strategy complexity showing that global strategies for mean-payoff objectives require infinite memory even in one-player pushdown games; and memoryless modular strategies are sufficient in two- player pushdown games. Finally we also show that all the problems have the same complexity if the stack boundedness condition is added, where along with the mean-payoff objective the player must also ensure that the stack height is bounded.},
author = {Chatterjee, Krishnendu and Velner, Yaron},
issn = {2664-1690},
pages = {33},
publisher = {IST Austria},
title = {{Mean-payoff pushdown games}},
doi = {10.15479/AT:IST-2012-0002},
year = {2012},
}