@inproceedings{3501, abstract = {The Wikipedia is a collaborative encyclopedia: anyone can contribute to its articles simply by clicking on an "edit" button. The open nature of the Wikipedia has been key to its success, but has also created a challenge: how can readers develop an informed opinion on its reliability? We propose a system that computes quantitative values of trust for the text in Wikipedia articles; these trust values provide an indication of text reliability. The system uses as input the revision history of each article, as well as information about the reputation of the contributing authors, as provided by a reputation system. The trust of a word in an article is computed on the basis of the reputation of the original author of the word, as well as the reputation of all authors who edited text near the word. The algorithm computes word trust values that vary smoothly across the text; the trust values can be visualized using varying text-background colors. The algorithm ensures that all changes to an article's text are reflected in the trust values, preventing surreptitious content changes. We have implemented the proposed system, and we have used it to compute and display the trust of the text of thousands of articles of the English Wikipedia. To validate our trust-computation algorithms, we show that text labeled as low-trust has a significantly higher probability of being edited in the future than text labeled as high-trust.}, author = {Adler, B Thomas and Krishnendu Chatterjee and de Alfaro, Luca and Faella, Marco and Pye, Ian and Raman, Vishwanath}, publisher = {ACM}, title = {{Assigning trust to Wikipedia content}}, doi = {10.1145/1822258.1822293}, year = {2008}, } @inproceedings{3502, abstract = {In content-driven reputation systems for collaborative content, users gain or lose reputation according to how their contributions fare: authors of long-lived contributions gain reputation, while authors of reverted contributions lose reputation. Existing content-driven systems are prone to Sybil attacks, in which multiple identities, controlled by the same person, perform coordinated actions to increase their reputation. We show that content-driven reputation systems can be made resistant to such attacks by taking advantage of thefact that the reputation increments and decrements depend on content modifications, which are visible to all. We present an algorithm for content-driven reputation that prevents a set of identities from increasing their maximum reputation without doing any useful work. Here, work is considered useful if it causes content to evolve in a direction that is consistent with the actions of high-reputation users. We argue that the content modifications that require no effort, such as the insertion or deletion of arbitrary text, are invariably non-useful. We prove a truthfullness result for the resulting system, stating that users who wish to perform a contribution do not gain by employing complex contribution schemes, compared to simply performing the contribution at once. In particular, splitting the contribution in multiple portions, or employing the coordinated actions of multiple identities, do not yield additional reputation. Taken together, these results indicate that content-driven systems can be made robust with respect to Sybil attacks. Copyright 2008 ACM.}, author = {Krishnendu Chatterjee and de Alfaro, Luca and Pye, Ian}, pages = {33 -- 42}, publisher = {ACM}, title = {{Robust content-driven reputation}}, doi = {10.1145/1456377.1456387 }, year = {2008}, } @inproceedings{3504, abstract = {Simulation and bisimulation metrics for stochastic systems provide a quantitative gen- eralization of the classical simulation and bisimulation relations. These metrics capture the similarity of states with respect to quantitative specifications written in the quantitative μ-calculus and related probabilistic logics. We present algorithms for computing the metrics on Markov decision processes (MDPs), turn- based stochastic games, and concurrent games. For turn-based games and MDPs, we provide a polynomial-time algorithm based on linear programming for the computation of the one-step metric distance between states. The algorithm improves on the previously known exponential-time algo- rithm based on a reduction to the theory of reals. We then present PSPACE algorithms for both the decision problem and the problem of approximating the metric distance between two states, matching the best known bound for Markov chains. For the bisimulation kernel of the metric, which corresponds to probabilistic bisimulation, our algorithm works in time O(n4) for both turn-based games and MDPs; improving the previously best known O(n9 · log(n)) time algorithm for MDPs. For a concurrent game G, we show that computing the exact distance between states is at least as hard as computing the value of concurrent reachability games and the square-root-sum problem in computational geometry. We show that checking whether the metric distance is bounded by a rational r, can be accomplished via a reduction to the theory of real closed fields, involving a formula with three quantifier alternations, yielding O(|G|O(|G|5)) time complexity, improving the previously known reduction with O(|G|O(|G|7)) time complexity. These algorithms can be iterated to approximate the metrics using binary search.}, author = {Chatterjee, Krishnendu and De Alfaro, Luca and Majumdar, Ritankar and Raman, Vishwanath}, pages = {107 -- 118}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum für Informatik}, title = {{Algorithms for game metrics}}, doi = {10.4230/LIPIcs.FSTTCS.2008.1745}, volume = {2}, year = {2008}, } @article{3516, abstract = {Temporal coding is a means of representing information by the time, as opposed to the rate, at which neurons fire. Evidence of temporal coding in the hippocampus comes from place cells, whose spike times relative to theta oscillations reflect a rat's position while running along stereotyped trajectories. This arises from the backwards shift in cell firing relative to local theta oscillations (phase precession). Here we demonstrate phase precession during place-field crossings in an open-field foraging task. This produced spike sequences in each theta cycle that disambiguate the rat's trajectory through two-dimensional space and can be used to predict movement direction. Furthermore, position and movement direction were maximally predicted from firing in the early and late portions of the theta cycle, respectively. This represents the first direct evidence of a combined representation of position, trajectory and heading in the hippocampus, organized on a fine temporal scale by theta oscillations.}, author = {Huxter,John R and Senior,Timothy J and Allen, Kevin and Jozsef Csicsvari}, journal = {Nature Neuroscience}, number = {5}, pages = {587 -- 594}, publisher = {Nature Publishing Group}, title = {{Theta phase-specific codes for two-dimensional position, trajectory and heading in the hippocampus}}, doi = {10.1038/nn.2106}, volume = {11}, year = {2008}, } @article{3520, abstract = {The hippocampus is thought to be involved in episodic memory formation by reactivating traces of waking experience during sleep. Indeed, the joint firing of spatially tuned pyramidal cells encoding nearby places recur during sleep. We found that the sleep cofiring of rat CA1 pyramidal cells encoding similar places increased relative to the sleep session before exploration. This cofiring increase depended on the number of times that cells fired together with short latencies ( < 50 ms) during exploration, and was strongest between cells representing the most visited places. This is indicative of a Hebbian learning rule in which changes in firing associations between cells are determined by the number of waking coincident firing events. In contrast, cells encoding different locations reduced their cofiring in proportion to the number of times that they fired independently. Together these data indicate that reactivated patterns are shaped by both positive and negative changes in cofiring, which are determined by recent behavior.}, author = {Joseph O'Neill and Senior,Timothy J and Allen, Kevin and Huxter,John R and Jozsef Csicsvari}, journal = {Nature Neuroscience}, number = {2}, pages = {209 -- 215}, publisher = {Nature Publishing Group}, title = {{Reactivation of experience-dependent cell assembly patterns in the hippocampus}}, doi = {10.1038/nn2037}, volume = {11}, year = {2008}, } @article{3530, abstract = {In the cerebral cortex, GABAergic interneurons are often regarded as fast-spiking cells. We have identified a type of slow-spiking interneuron that offers distinct contributions to network activity. “Ivy” cells, named after their dense and fine axons innervating mostly basal and oblique pyramidal cell dendrites, are more numerous than the parvalbumin-expressing basket, bistratified, or axo-axonic cells. Ivy cells express nitric oxide synthase, neuropeptide Y, and high levels of GABA(A) receptor alpha 1 subunit; they discharge at a low frequency with wide spikes in vivo, yet are distinctively phase-locked to behaviorally relevant network rhythms including theta, gamma, and ripple oscillations. Paired recordings in vitro showed that Ivy cells receive depressing EPSPs from pyramidal cells, which in turn receive slowly rising and decaying inhibitory input from Ivy cells. In contrast to fast-spiking interneurons operating with millisecond precision, the highly abundant Ivy cells express presynaptically acting neuromodulators and regulate the excitability of pyramidal cell dendrites through slowly rising and decaying GABAergic inputs.}, author = {Fuentealba,Pablo and Begum,Rahima and Capogna,Marco and Jinno,Shozo and Marton,Laszlo F and Jozsef Csicsvari and Thomson,Alex and Somogyi, Péter and Klausberger,Thomas}, journal = {Neuron}, number = {6}, pages = {917 -- 929}, publisher = {Elsevier}, title = {{Ivy cells: A population of nitric-oxide-producing, slow-spiking GABAergic neurons and their involvement in hippocampal network activity}}, doi = {10.1016/j.neuron.2008.01.034}, volume = {57}, year = {2008}, } @article{3534, author = {Dupret, David and Pleydell-Bouverie, Barty and Jozsef Csicsvari}, journal = {PNAS}, number = {47}, pages = {18079 -- 18080}, publisher = {National Academy of Sciences}, title = {{Inhibitory interneurons and network oscillations}}, doi = {10.1073/pnas.0810064105}, volume = {105}, year = {2008}, } @article{3537, abstract = {Hippocampal place cells that fire together within the same cycle of theta oscillations represent the sequence of positions (movement trajectory) that a rat traverses on a linear track. Furthermore, it has been suggested that the encoding of these and other types of temporal memory sequences is organized by gamma oscillations nested within theta oscillations. Here, we examined whether gamma-related firing of place cells permits such discrete temporal coding. We found that gamma-modulated CA1 pyramidal cells separated into two classes on the basis of gamma firing phases during waking theta periods. These groups also differed in terms of their spike waveforms, firing rates, and burst firing tendency. During gamma oscillations one group's firing became restricted to theta phases associated with the highest gamma power. Consequently, on the linear track, cells in this group often failed to fire early in theta-phase precession (as the rat entered the place field) if gamma oscillations were present. The second group fired throughout the theta cycle during gamma oscillations, and maintained gamma-modulated firing at different stages of theta-phase precession. Our results suggest that the two different pyramidal cell classes may support different types of population codes within a theta cycle: one in which spike sequences representing movement trajectories occur across subsequent gamma cycles nested within each theta cycle, and another in which firing in synchronized gamma discharges without temporal sequences encode a representation of location. We propose that gamma oscillations during theta-phase precession organize the mnemonic recall of population patterns representing places and movement paths.}, author = {Senior,Timothy J and Huxter,John R and Allen, Kevin and Joseph O'Neill and Jozsef Csicsvari}, journal = {Journal of Neuroscience}, number = {9}, pages = {2274 -- 2286}, publisher = {Society for Neuroscience}, title = {{Gamma oscillatory firing reveals distinct populations of pyramidal cells in the CA1 region of the hippocampus}}, doi = {10.1523/JNEUROSCI.4669-07.2008}, volume = {28}, year = {2008}, } @article{3544, abstract = {In the subthalamic nucleus (STN) of Parkinson's disease (PD) patients, a pronounced synchronization of oscillatory activity at beta frequencies (15-30 Hz) accompanies movement difficulties. Abnormal beta oscillations and motor symptoms are concomitantly and acutely suppressed by dopaminergic therapies, suggesting that these inappropriate rhythms might also emerge acutely from disrupted dopamine transmission. The neural basis of these abnormal beta oscillations is unclear, and how they might compromise information processing, or how they arise, is unknown. Using a 6-hydroxydopamine-lesioned rodent model of PD, we demonstrate that beta oscillations are inappropriately exaggerated, compared with controls, in a brain-state-dependent manner after chronic dopamine loss. Exaggerated beta oscillations are expressed at the levels of single neurons and small neuronal ensembles, and are focally present and spatially distributed within STN. They are also expressed in synchronous population activities, as evinced by oscillatory local field potentials, in STN and cortex. Excessively synchronized beta oscillations reduce the information coding capacity of STN neuronal ensembles, which may contribute to parkinsonian motor impairment. Acute disruption of dopamine transmission in control animals with antagonists of D-1/D-2 receptors did not exaggerate STN or cortical beta oscillations. Moreover, beta oscillations were not exaggerated until several days after 6-hydroxydopamine injections. Thus, contrary to predictions, abnormally amplified beta oscillations in cortico-STN circuits do not result simply from an acute absence of dopamine receptor stimulation, but are instead delayed sequelae of chronic dopamine depletion. Targeting the plastic processes underlying the delayed emergence of pathological beta oscillations after continuing dopaminergic dysfunction may offer considerable therapeutic promise.}, author = {Mallet,Nicolas and Pogosyan,Alek and Sharott,Andrew and Jozsef Csicsvari and Bolam, John Paul and Brown,Peter and Magill,Peter J}, journal = {Journal of Neuroscience}, number = {18}, pages = {4795 -- 4806}, publisher = {Society for Neuroscience}, title = {{Disrupted dopamine transmission and the emergence of exaggerated beta oscillations in subthalamic nucleus and cerebral cortex}}, doi = {10.1523/JNEUROSCI.0123-08.2008}, volume = {28}, year = {2008}, } @inbook{3577, author = {Biasotti, Silvia and Attali, Dominique and Boissonnat, Jean-Daniel and Herbert Edelsbrunner and Elber, Gershon and Mortara, Michela and Sanniti di Baja, Gabriella and Spagnuolo, Michela and Tanase, Mirela and Veltkam, Remco}, booktitle = {Shape Analysis and Structuring}, pages = {145 -- 183}, publisher = {Springer}, title = {{Skeletal structures}}, doi = {10.1007/978-3-540-33265-7_5}, year = {2008}, } @article{3591, abstract = {The controlled internalization of membrane receptors and lipids is crucial for cells to control signaling pathways and interact with their environment. During clathrin-mediated endocytosis, membrane constituents are transported via endocytic vesicles into early endosomes, from which they are further distributed within the cell. The small guanosine triphosphatase (GTPase) Rab5 is both required and sufficient for the formation of these early endosomes and can be used to experimentally address endocytic processes. Recent evidence shows that endocytic turnover of E-cadherin regulates the migration of mesendodermal cells during zebrafish gastrulation by modulating their adhesive interactions with neighboring cells. This in turn leads to effective and synchronized movement within the embryo. In this review, we discuss techniques to manipulate E-cadherin endocytosis by morpholino-mediated knockdown of rab5 during zebrafish gastrulation. We describe the use of antibodies specifically directed against zebrafish E-cadherin to detect its intracellular localization and of in situ hybridization and primary cell culture to reveal patterns of cell migration and adhesion, respectively}, author = {Ulrich, Florian and Heisenberg, Carl-Philipp J}, journal = {Methods in Molecular Biology}, pages = {371 -- 387}, publisher = {Springer}, title = {{Probing E-cadherin endocytosis by morpholino-mediated Rab5 knock-down in zebrafish.}}, doi = {10.1007/978-1-59745-178-9_27}, volume = {440}, year = {2008}, } @inproceedings{3599, abstract = {In this paper, adaptive formation control and bio-inspired optimization are jointly addressed for a cluster-based satellite wireless sensor network in which there are multiple satellites flying in formation (MSFF) in the presence of unknown disturbances. The full nonlinear dynamics model describing the relative positioning of the MSFF system is used to develop an adaptive formation controller. First, the original nonlinear system is transformed into a linear controllable system with aperturbation term by invoking the input-output feedback linearization technique. Second, by using the integral feedback design scheme, the adaptive formation controller is presented for improving the steady-state performance of the MSFF system in the presence of unknown disturbances. Third, as a currently popular bio-inspired algorithm, PSO (particle swarm optimizer) is employed to minimize the total energy consumption under the required quality of service by jointly optimizing the transmission power and rate for each satellite. Simulation results are provided to demonstrate the effectiveness of the adaptive formation controller and the PSO-based optimization for saving the total communication energy.}, author = {Yang, Erfu and Erdogan, Ahmet T and Arslan, Tughrul and Nicholas Barton}, pages = {432 -- 439}, publisher = {IEEE}, title = {{Adaptive formation control and bio-inspired optimization of a cluster-based satellite wireless sensor network }}, doi = {10.1109/AHS.2008.60}, year = {2008}, } @inproceedings{3600, abstract = {Scalability is one of the most important issues for optimization algorithms used in wireless sensor networks (WSNs) since there are often many parameters to be optimized at the same time. In this case it is very hard to ensure that an optimization algorithm can be smoothly scaled up from a low-dimensional optimization problem to the one with a high dimensionality. This paper addresses the scalability issue of a novel optimization algorithm inspired by the Shifting Balance Theory (SBT) of evolution in population genetics. Toward this end, a cluster-based WSN is employed in this paper as a benchmark to perform a comparative study. The total energy consumption is minimized under the required quality of service by jointly optimizing the transmission power and rate for each sensor node. The results obtained by the SBT-based algorithm are compared with the Metropolis algorithm (MA) and currently popular particle swarm optimizer (PSO) to assess the scaling performance of the three algorithms against the same WSN optimization problem.}, author = {Yang, Erfu and Nicholas Barton and Arslan, Tughrul and Erdogan, Ahmet T}, pages = {249 -- 260}, publisher = {Springer}, title = {{ Scalability of a novel shifting balance theory-based optimization algorithm: A comparative study on a cluster-based wireless sensor network}}, doi = {10.1007/978-3-540-85857-7_22}, volume = {5216}, year = {2008}, } @article{3605, abstract = {Many animals and plants show a correlation between the traits of the individuals in the mating pair, implying assortative mating. Given the ubiquity of assortative mating in nature, why and how it has evolved remain open questions. Here we attempt to answer these questions in those cases where the trait under assortment is the same in males and females. We consider the most favorable scenario for assortment to evolve, where the same trait is under assortment and viability selection. We find conditions for assortment to evolve using a multilocus formalism in a haploid population. Our results show how epistasis in fitness between the loci that control the focal trait is crucial for assortment to evolve. We then assume specific forms of assortment in haploids and diploids and study the limiting cases of selective and nonselective mating. We find that selection for increased assortment is weak and that where increased assortment is costly, it does not invade.}, author = {De Cara, Maria A and Nicholas Barton and Kirkpatrick, Mark}, journal = {American Naturalist}, number = {5}, pages = {580 -- 596}, publisher = {University of Chicago Press}, title = {{A model for the evolution of assortative mating}}, doi = {10.1086/587062}, volume = {171}, year = {2008}, } @article{3606, abstract = {Explicit formulae are given for the effects of a barrier to gene flow on random fluctuations in allele frequency; these formulae can also be seen as generating functions for the distribution of coalescence times. The formulae are derived using a continuous diffusion approximation, which is accurate over all but very small spatial scales. The continuous approximation is confirmed by comparison with the exact solution to the stepping stone model. In both one and two spatial dimensions, the variance of fluctuations in allele frequencies increases near the barrier; when the barrier is very strong, the variance doubles. However, the effect on fluctuations close to the barrier is much greater when the population is spread over two spatial dimensions than when it occupies a linear, one-dimensional habitat: barriers of strength comparable with the dispersal range (B≈σ) can have an appreciable effect in two dimensions, whereas only barriers with strength comparable with the characteristic scale (B\! \approx\! L \equals \sigma \sol \sqrt {2 \mu}\hskip2) are significant in one dimension (μ is the rate of mutation or long-range dispersal). Thus, in a two-dimensional population, barriers to gene flow can be detected through their effect on the spatial pattern of genetic marker alleles.}, author = {Nicholas Barton}, journal = {Genetical Research}, number = {1}, pages = {139 -- 149}, publisher = {Cambridge University Press}, title = {{The effect of a barrier to gene flow on patterns of geographic variation}}, doi = {10.1017/S0016672307009081}, volume = {90}, year = {2008}, } @inproceedings{3694, abstract = {Distributed Denial of Service (DDoS) attacks are today the most destabilizing factor in the global internet and there is a strong need for sophisticated solutions. We introduce a formal statistical framework and derive a Bayes optimal packet classifier from it. Our proposed practical algorithm "Adaptive History-Based IP Filtering" (AHIF) mitigates DDoS attacks near the victim and outperforms existing methods by at least 32% in terms of collateral damage. Furthermore, it adjusts to the strength of an ongoing attack and ensures availability of the attacked server. In contrast to other adaptive solutions, firewall rulesets used to resist an attack can be precalculated before an attack takes place. This ensures an immediate response in a DDoS emergency. For evaluation, simulated DDoS attacks and two real-world user traffic datasets are used.}, author = {Goldstein,Markus and Christoph Lampert and Reif,Matthias and Stahl,Armin and Breuel,Thomas M}, pages = {174 -- 179}, publisher = {IEEE}, title = {{Bayes optimal DDoS mitigation by adaptive history-based IP filtering}}, doi = {10.1109/ICN.2008.64}, year = {2008}, } @inproceedings{3698, abstract = {Kernel canonical correlation analysis (KCCA) is a dimensionality reduction technique for paired data. By finding directions that maximize correlation, KCCA learns representations that are more closely tied to the underlying semantics of the data rather than noise. However, meaningful directions are not only those that have high correlation to another modality, but also those that capture the manifold structure of the data. We propose a method that is simultaneously able to find highly correlated directions that are also located on high variance directions along the data manifold. This is achieved by the use of semi-supervised Laplacian regularization of KCCA. We show experimentally that Laplacian regularized training improves class separation over KCCA with only Tikhonov regularization, while causing no degradation in the correlation between modalities. We propose a model selection criterion based on the Hilbert-Schmidt norm of the semi-supervised Laplacian regularized cross-covariance operator, which we compute in closed form.}, author = {Blaschko,Matthew B and Christoph Lampert and Gretton,Arthur}, number = {Part 1}, pages = {133 -- 145}, publisher = {Springer}, title = {{Semi-supervised Laplacian regularization of kernel canonical correlation analysis}}, doi = {10.1007/978-3-540-87479-9_27}, volume = {5211}, year = {2008}, } @inproceedings{3700, abstract = {We propose a new method to partition an unlabeled dataset, called Discriminative Context Partitioning (DCP). It is motivated by the idea of splitting the dataset based only on how well the resulting parts can be separated from a context class of disjoint data points. This is in contrast to typical clustering techniques like K-means that are based on a generative model by implicitly or explicitly searching for modes in the distribution of samples. The discriminative criterion in DCP avoids the problems that density based methods have when the a priori assumption of multimodality is violated, when the number of samples becomes small in relation to the dimensionality of the feature space, or if the cluster sizes are strongly unbalanced. We formulate DCP&amp;amp;amp;amp;amp;amp;amp;amp;lsquo;s separation property as a large-margin criterion, and show how the resulting optimization problem can be solved efficiently. Experiments on the MNIST and USPS datasets of handwritten digits and on a subset of the Caltech256 dataset show that, given a suitable context, DCP can achieve good results even in situation where density-based clustering techniques fail.}, author = {Christoph Lampert}, pages = {1 -- 8}, publisher = {IEEE}, title = {{Partitioning of image datasets using discriminative context information}}, doi = {10.1109/CVPR.2008.4587448}, year = {2008}, } @inproceedings{3705, abstract = {Sliding window classifiers are among the most successful and widely applied techniques for object localization. However, training is typically done in a way that is not specific to the localization task. First a binary classifier is trained using a sample of positive and negative examples, and this classifier is subsequently applied to multiple regions within test images. We propose instead to treat object localization in a principled way by posing it as a problem of predicting structured data: we model the problem not as binary classification, but as the prediction of the bounding box of objects located in images. The use of a joint-kernel framework allows us to formulate the training procedure as a generalization of an SVM, which can be solved efficiently. We further improve computational efficiency by using a branch-and-bound strategy for localization during both training and testing. Experimental evaluation on the PASCAL VOC and TU Darmstadt datasets show that the structured training procedure improves pe rformance over binary training as well as the best previously published scores.}, author = {Blaschko,Matthew B and Christoph Lampert}, pages = {2 -- 15}, publisher = {Springer}, title = {{Learning to localize objects with structured output regression}}, doi = {10.1007/978-3-540-88682-2_2}, volume = {5302}, year = {2008}, } @inproceedings{3706, abstract = {We present a new technique for structured prediction that works in a hybrid generative/discriminative way, using a one-class support vector machine to model the joint probability of (input, output)-pairs in a joint reproducing kernel Hilbert space. Compared to discriminative techniques, like conditional random fields or structured output SVMs?, the proposed method has the advantage that its training time depends only on the number of training examples, not on the size of the label space. Due to its generative aspect, it is also very tolerant against ambiguous, incomplete or incorrect labels. Experiments on realistic data show that our method works efficiently and robustly in situations that discriminative techniques have problems with or that are computationally infeasible for them.}, author = {Christoph Lampert and Blaschko,Matthew B}, pages = {1 -- 4}, publisher = {Curran Associates, Inc.}, title = {{Joint kernel support estimation for structured prediction}}, year = {2008}, }