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Saturday, June 13, 2015
Orioles Highlight: Manny Machado with HR and 4 RBI, Nolan Reimold 2-run HR and triple in team's 6th straight win (ESPN)
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How to fix FIFA: Experts says agency needs outside reformer
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Argentina concedes late goal, draws Paraguay in Copa America
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Faeroe Islands beat Greece again in Euro 2016 qualifying
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Uruguay defeats Jamaica 1-0 to open Copa America
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Orioles: SS Everth Cabrera released; hit just .208 with 4 RBIs, 22 K's in 29 games in first season with Baltimore (ESPN)
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Ronaldo nets 3, Portugal beats Armenia 3-2 in Euro qualifier
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Ireland shreds game programs over CEO's FIFA crisis comments
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STEW on Twitter: "New York Times fund keeps donors anonymous http://t.co/M4pnO3F2ZQ (via ...
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Goalkeeper Buffon leaves Italy's squad with injured knee
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2 parties cleared for talks on taking over bankrupt Parma
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Ghana investigates top soccer official over World Cup funds
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Speculations on Anonymous Materials
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Americans held, Japan through to last 16 at Women's WCup
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The Medusa Nebula
US soccer defends Hope Solo decisions in letter to senator
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Friday, June 12, 2015
Orioles Highlight: Chris Davis with HR and 4 RBI in 11-3 rout of Yankees; 5th straight win, at .500 1st time since May 5 (ESPN)
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IT Security – Do it the hard or easy way!
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Do You also want to Hack Facebook Account of your Girlfriend?
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[FD] Yoast Wordpress SEO Plugin <= 2.1.1 Stored, Authenticated XSS
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Mexico-Bolivia ends scoreless at Copa America
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Simon scores twice in 2-0 Australia win over Nigeria
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I have a new follower on Twitter
Peter Meek
Currently a Level 4 FA Referee, Reading FC fan and loves Coldplay. These are the views of myself and myself only
Camberley
Following: 963 - Followers: 297
June 12, 2015 at 05:31PM via Twitter http://twitter.com/Ref_r_u_blind
Bale grabs winner, Wales beat Belgium 1-0 in Euro qualifying
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Wijnaldum, Narsingh score as Netherlands beats Latvia 2-0
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Swastika pattern depicted on pitch during Croatia vs. Italy
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CAF signs new marketing deal with Sportfive until 2028
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Fantasy MLB: Yankees P Michael Pineda is 3-0 with 2.56 ERA, 50 K's in 6 starts vs. Orioles; 16 K's, W in last meeting (ESPN)
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Andre Breitenreiter hired as coach of Schalke
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Defiant Warner to challenge extradition from Trinidad to US
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CAS sets target for Serbia, Albania Euro 2016 case verdicts
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I have a new follower on Twitter
Funny Photos
funniest photos from all over the world
Following: 11042 - Followers: 11998
June 12, 2015 at 10:40AM via Twitter http://twitter.com/PhotoFunKill
ISS Daily Summary Report – 6/11/15
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Franck Ribery suffers setback with ankle injury
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[FD] The token order of OpVectorTimesScalar and OpMatrixTimesScalar which generated in glslangValidator isn't consistant with SPEC
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Interpol suspends $22M FIFA project during corruption crisis
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The 2015 Earth-Orbiting Heliophysics Fleet
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Norway draws top-ranked Germany 1-1 at Women's WCup
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The Light, the Dark, and the Dusty
Thursday, June 11, 2015
Orioles Highlight: Adam Jones, Nolan Reimold and Manny Machado HR in 6-5 win over Red Sox; 1st series sweep of season (ESPN)
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Host Chile beats Ecuador 2-0 in Copa America opener
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Brazilian football confederation introduces term limits
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I keep 200+ Browser Tabs Open, and My Computer Runs Absolutely Fine. Here’s My Secret.
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MA Book of Meditations
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Cavani apologizes for saying Jamaica is an African team
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Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts. (arXiv:1506.03493v1 [stat.ML])
We present a Bayesian tensor factorization model for inferring latent group structures from dynamic pairwise interaction patterns. For decades, political scientists have collected and analyzed records of the form "country $i$ took action $a$ toward country $j$ at time $t$"---known as dyadic events---in order to form and test theories of international relations. We represent these event data as a tensor of counts and develop Bayesian Poisson tensor factorization to infer a low-dimensional, interpretable representation of their salient patterns. We demonstrate that our model's predictive performance is better than that of standard non-negative tensor factorization methods. We also provide a comparison of our variational updates to their maximum likelihood counterparts. In doing so, we identify a better way to form point estimates of the latent factors than that typically used in Bayesian Poisson matrix factorization. Finally, we showcase our model as an exploratory analysis tool for political scientists. We show that the inferred latent factor matrices capture interpretable multilateral relations that both conform to and inform our knowledge of international affairs.
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Bootstrapping Skills. (arXiv:1506.03624v1 [cs.AI])
The monolithic approach to policy representation in Markov Decision Processes (MDPs) looks for a single policy that can be represented as a function from states to actions. For the monolithic approach to succeed (and this is not always possible), a complex feature representation is often necessary since the policy is a complex object that has to prescribe what actions to take all over the state space. This is especially true in large domains with complicated dynamics. It is also computationally inefficient to both learn and plan in MDPs using a complex monolithic approach. We present a different approach where we restrict the policy space to policies that can be represented as combinations of simpler, parameterized skills---a type of temporally extended action, with a simple policy representation. We introduce Learning Skills via Bootstrapping (LSB) that can use a broad family of Reinforcement Learning (RL) algorithms as a "black box" to iteratively learn parametrized skills. Initially, the learned skills are short-sighted but each iteration of the algorithm allows the skills to bootstrap off one another, improving each skill in the process. We prove that this bootstrapping process returns a near-optimal policy. Furthermore, our experiments demonstrate that LSB can solve MDPs that, given the same representational power, could not be solved by a monolithic approach. Thus, planning with learned skills results in better policies without requiring complex policy representations.
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Long-term causal effects of interventions in multiagent economic mechanisms. (arXiv:1501.02315v3 [stat.ME] UPDATED)
The effect of an intervention in an economic mechanism, for example an increase in the reserve price of an auction, is causal if the observed effect is better than the counterfactual, i.e., the effect that would be observed under no intervention. As mechanisms are populated by dynamical systems of interacting agents, their response to an intervention fluctuates until the system reaches a new equilibrium. Effects measured in the new equilibrium, the long-term causal effects, are more representative of the value of interventions. However, the statistical estimation of long-term causal effects is difficult because it has to rely, for practical reasons, on data observed before the new equilibrium is reached. Furthermore, agent actions do not only depend on the mechanism that the agents are situated in but also on the behavior of others, which complicates the causal evaluation. In this paper, we formalize this problem of estimating long-term causal effects under the potential outcomes framework of causal inference \cite{neyman1923, rubin74}. We develop an estimation method that relies on a data augmentation strategy, where agents are assumed to adopt, at each timepoint, a behavior that is latent. This allows us to leverage existing work in behavioral game theory and time-series analysis of compositional data. Our method identifies the long-term causal effects under a set of assumptions that we formulate explicitly. We illustrate our method on a dataset from a real-world behavioral experiment, and discuss open problems to stimulate future research.
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Vatican suspends deal with CONMEBOL amid investigation
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I've generated a matlab anonymous function. I get errors on calling it
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Safe Helpline Rectangular Web Banner - "Anonymous"
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I have a new follower on Twitter
SQL Professionals
A Microsoft SQL Server Consultancy
Minneapolis, MN
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Following: 4563 - Followers: 4711
June 11, 2015 at 06:29PM via Twitter http://twitter.com/sqlpros
[FD] XSS vulnerability Adobe Connect 9.3 (CVE-2015-0343 )
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[FD] D-Link DSP-W110 - multiple vulnerabilities
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Fabregas leads Spain's 2-1 win over Costa Rica in friendly
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[FD] Path Traversal vulnerability in Wordpress plugin se-html5-album-audio-player v1.1.0
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[FD] 6kbbs v8.0 Weak Encryption Cryptography Security Vulnerabilities
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[FD] Apache vulnerability program faulting module ntdll.dll
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Future of 2016 Centennial Copa America to be discussed
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Judge orders Chuck Blazer plea agreement unsealed
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Paraguay's Senate votes to end soccer confederation immunity
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[FD] [KIS-2015-03] Concrete5 <= 5.7.4 (Access.php) SQL Injection Vulnerability
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Anonymous on Twitter: "UK schools are using spyware to monitor students' ideology. #Anonymous ...
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[FD] [KIS-2015-02] Concrete5 <= 5.7.3.1 Multiple Reflected Cross-Site Scripting Vulnerabilities
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[FD] [KIS-2015-01] Concrete5 <= 5.7.3.1 (sendmail) Remote Code Execution Vulnerability
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Orioles: SP Miguel Gonzalez (groin) placed on 15-day DL; P Mike Wright (2.96 ERA in 4 starts) recalled from Triple-A (ESPN)
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Zimbabwe team misses flight amid payment dispute
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Paraguay's Senate votes to repeal CONMEBOL immunity
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15 arrested in fixing probe led by anti-Mafia authorities
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Bursaspor out of Europa League after appeal to CAS rejected
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Daniel Alves called up for Brazil's Copa America squad
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At Copa America, Neymar gets new chance to lead Brazil
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FIFA's top spokesman leaves job, Blatter urged to do same
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Jose Mourinho banned from driving for 6 months for speeding
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ISS Daily Summary Report – 06/10/15
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Blatter spokesman De Gregorio to leave FIFA immediately
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European lawmakers urge FIFA president Blatter to go now
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South Korea forward Kang tests positive for steroid
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NSFW illustrations of anonymous sexual encounters
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Verratti leaves Italy's squad with injured calf
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Germany, Portugal, Brazil reach quarterfinals at U20 WCup
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Lyon midfielder Clement Grenier signs new 2-year deal
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Wednesday, June 10, 2015
Brazil beats Honduras 1-0 in final warmup for Copa America
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Australia players, football federation in pay dispute
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I have a new follower on Twitter
Tony Zayas
Proud Father and Husband. Chicago sports, UFC and Iowa Hawkeye football enthusiast. Marketer, Strategist & Social media guy @Proforma
Cleveland, OH
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Following: 3720 - Followers: 5071
June 10, 2015 at 10:54PM via Twitter http://twitter.com/TonyZayas
Orioles Highlight: 3 great defensive plays lead to fourth-straight victory over Red Sox, 5-2; Wei-Yin Chen 2 ER, 5.0 IP (ESPN)
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I have a new follower on Twitter
Cordny Nederkoorn
Enthusiastic Blogger / Journalist | #softwaretesting | #SaaS | #security | #privacy | #identitymanagement
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Following: 15678 - Followers: 16686
June 10, 2015 at 09:52PM via Twitter http://twitter.com/TestingSaaS
Former Brazil star Zico wants to run for FIFA president
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On-the-Job Learning with Bayesian Decision Theory. (arXiv:1506.03140v1 [cs.AI])
How can we deploy a high-accuracy system starting with zero training examples? We consider an "on-the-job" setting, where as inputs arrive, we use crowdsourcing to resolve uncertainty where needed and output our prediction when confident. As the model improves over time, the reliance on crowdsourcing queries decreases. We cast our setting as a stochastic game based on Bayesian decision theory, which allows us to balance latency, cost, and accuracy objectives in a principled way. Computing the optimal policy is intractable, so we develop an approximation based on Monte Carlo Tree Search. We tested our approach across three datasets---named-entity recognition, sentiment classification, and image classification. On the NER task we obtained a 6--7 fold reduction in cost compared to full human annotation. We also achieve a 17% F$_1$ improvement over having a single human label the whole set, and a 28% F$_1$ improvement over online learning.
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Teaching Machines to Read and Comprehend. (arXiv:1506.03340v1 [cs.CL])
Teaching machines to read natural language documents remains an elusive challenge. Machine reading systems can be tested on their ability to answer questions posed on the contents of documents that they have seen, but until now large scale training and test datasets have been missing for this type of evaluation. In this work we define a new methodology that resolves this bottleneck and provides large scale supervised reading comprehension data. This allows us to develop a class of attention based deep neural networks that learn to read real documents and answer complex questions with minimal prior knowledge of language structure.
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Contextual Bandits with Global Constraints and Objective. (arXiv:1506.03374v1 [cs.LG])
We consider the contextual version of a multi-armed bandit problem with global convex constraints and concave objective function. In each round, the outcome of pulling an arm is a context-dependent vector, and the global constraints require the average of these vectors to lie in a certain convex set. The objective is a concave function of this average vector. The learning agent competes with an arbitrary set of context-dependent policies. This problem is a common generalization of problems considered by Badanidiyuru et al. (2014) and Agrawal and Devanur (2014), with important applications. We give computationally efficient algorithms with near-optimal regret, generalizing the approach of Agarwal et al. (2014) for the non-constrained version of the problem. For the special case of budget constraints our regret bounds match those of Badanidiyuru et al. (2014), answering their main open question of obtaining a computationally efficient algorithm.
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On the Prior Sensitivity of Thompson Sampling. (arXiv:1506.03378v1 [cs.LG])
The empirically successful Thompson Sampling algorithm for stochastic bandits has drawn much interest in understanding its theoretical properties. One important benefit of the algorithm is that it allows domain knowledge to be conveniently encoded as a prior distribution to balance exploration and exploitation more effectively. While it is generally believed that the algorithm's regret is low (high) when the prior is good (bad), little is known about the exact dependence. In this paper, we fully characterize the algorithm's worst-case dependence of regret on the choice of prior, focusing on a special yet representative case. These results also provide insights into the general sensitivity of the algorithm to the choice of priors. In particular, with $p$ being the prior probability mass of the true reward-generating model, we prove $O(\sqrt{T/p})$ and $O(\sqrt{(1-p)T})$ regret upper bounds for the bad- and good-prior cases, respectively, as well as \emph{matching} lower bounds. Our proofs rely on the discovery of a fundamental property of Thompson Sampling and make heavy use of martingale theory, both of which appear novel in the literature, to the best of our knowledge.
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The Online Discovery Problem and Its Application to Lifelong Reinforcement Learning. (arXiv:1506.03379v1 [cs.LG])
Transferring knowledge across a sequence of related tasks is an important challenge in reinforcement learning. Despite much encouraging empirical evidence that shows benefits of transfer, there has been very little theoretical analysis. In this paper, we study a class of lifelong reinforcement-learning problems: the agent solves a sequence of tasks modeled as finite Markov decision processes (MDPs), each of which is from a finite set of MDPs with the same state/action spaces and different transition/reward functions. Inspired by the need for cross-task exploration in lifelong learning, we formulate a novel online discovery problem and give an optimal learning algorithm to solve it. Such results allow us to develop a new lifelong reinforcement-learning algorithm, whose overall sample complexity in a sequence of tasks is much smaller than that of single-task learning, with high probability, even if the sequence of tasks is generated by an adversary. Benefits of the algorithm are demonstrated in a simulated problem.
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Fast Online Clustering with Randomized Skeleton Sets. (arXiv:1506.03425v1 [cs.AI])
We present a new fast online clustering algorithm that reliably recovers arbitrary-shaped data clusters in high throughout data streams. Unlike the existing state-of-the-art online clustering methods based on k-means or k-medoid, it does not make any restrictive generative assumptions. In addition, in contrast to existing nonparametric clustering techniques such as DBScan or DenStream, it gives provable theoretical guarantees. To achieve fast clustering, we propose to represent each cluster by a skeleton set which is updated continuously as new data is seen. A skeleton set consists of weighted samples from the data where weights encode local densities. The size of each skeleton set is adapted according to the cluster geometry. The proposed technique automatically detects the number of clusters and is robust to outliers. The algorithm works for the infinite data stream where more than one pass over the data is not feasible. We provide theoretical guarantees on the quality of the clustering and also demonstrate its advantage over the existing state-of-the-art on several datasets.
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Dynamic Consistency of Conditional Simple Temporal Networks via Mean Payoff Games: a Singly-Exponential Time DC-Checking. (arXiv:1505.00828v3 [cs.DS] UPDATED)
Conditional Simple Temporal Network (CSTN) is a constraint-based graph-formalism for conditional temporal planning. It offers a more flexible formalism than the equivalent CSTP model of Tsamardinos, Vidal and Pollack, from which it was derived mainly as a sound formalization. Three notions of consistency arise for CSTNs and CSTPs: weak, strong, and dynamic. Dynamic consistency is the most interesting notion, but it is also the most challenging and it was conjectured to be hard to assess. Tsamardinos, Vidal and Pollack gave a doubly-exponential time algorithm for deciding whether a CSTN is dynamically-consistent and to produce, in the positive case, a dynamic execution strategy of exponential size. In the present work we offer a proof that deciding whether a CSTN is dynamically-consistent is coNP-hard and provide the first singly-exponential time algorithm for this problem, also producing a dynamic execution strategy whenever the input CSTN is dynamically-consistent. The algorithm is based on a novel connection with Mean Payoff Games, a family of two-player combinatorial games on graphs well known for having applications in model-checking and formal verification. The presentation of such connection is mediated by the Hyper Temporal Network model, a tractable generalization of Simple Temporal Networks whose consistency checking is equivalent to determining Mean Payoff Games. In order to analyze the algorithm we introduce a refined notion of dynamic-consistency, named \epsilon-dynamic-consistency, and present a sharp lower bounding analysis on the critical value of the reaction time \hat{\varepsilon} where the CSTN transits from being, to not being, dynamically-consistent. The proof technique introduced in this analysis of \hat{\varepsilon} is applicable more in general when dealing with linear difference constraints which include strict inequalities.
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Orioles: A red-hot bullpen (3 R last 18.1 IP) looks to stop Red Sox 4th straight time in Baltimore, 7 ET ESPN/WatchESPN (ESPN)
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Orioles: A red-hot bullpen (3 R last 18.1 IP) looks to stop Red Sox 4th straight time in Baltimore, 7 ET ESPN/WatchESPN (ESPN)
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Red Sox: Rick Porcello looks to build on last outing (8 IP, 2 R, 0 BBs vs. Twins) at Orioles; 7 pm ET on ESPN/WatchESPN (ESPN)
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MLB: Orioles look to make it 4 wins in a row at home against the Red Sox (David Ortiz benched); 7 pm ET ESPN/WatchESPN (ESPN)
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PicResize.com (@picresize) favorited one of your Tweets!
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Wood scores late to give US a 2-1 win over Germany
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Former Brazil star Zico running for FIFA president
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Wood's 87th-minute goal lifts US to 2-1 win at Germany
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[FD] Authentication Bypass in Pandora FMS
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[FD] Remote file upload vulnerability in aviary-image-editor-add-on-for-gravity-forms v3.0beta Wordpress plugin
"; • echo $result; • echo "
"; • ?>
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Trinidad AG: Gov't feared ex-FIFA VP Warner a flight risk
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Argentine willing to be extradited to US in FIFA case
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[FD] This POODLE Bites: Exploiting The SSL 3.0 Fallback
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NPR Journalist, Citing Anonymous 'List'
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Beasley on US roster for CONCACAF Gold Cup
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I have a new follower on Twitter
John Sonmez
Want to know the best way to increase your salary or hourly rate? http://t.co/5hjINCbt04
Tampa, FL
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Following: 16103 - Followers: 23098
June 10, 2015 at 03:26PM via Twitter http://twitter.com/jsonmez
Swansea signs Ghana forward Andre Ayew
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Williams, Diskerud, Agudelo start for US against Germany
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Swiss attorney general seizes evidence from FIFA offices
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Fantasy MLB: Red Sox 2B Dustin Pedroia 15-for-32 (.469 BA) in his career against Orioles SP Wei-Yin Chen (ESPN)
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ISS Daily Summary Report – 06/09/15
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Self Organizing Maps Whose Topologies Can Be Learned With Adaptive Binary Search Trees Using Conditional Rotations. (arXiv:1506.02750v1 [cs.NE])
Numerous variants of Self-Organizing Maps (SOMs) have been proposed in the literature, including those which also possess an underlying structure, and in some cases, this structure itself can be defined by the user Although the concepts of growing the SOM and updating it have been studied, the whole issue of using a self-organizing Adaptive Data Structure (ADS) to further enhance the properties of the underlying SOM, has been unexplored. In an earlier work, we impose an arbitrary, user-defined, tree-like topology onto the codebooks, which consequently enforced a neighborhood phenomenon and the so-called tree-based Bubble of Activity. In this paper, we consider how the underlying tree itself can be rendered dynamic and adaptively transformed. To do this, we present methods by which a SOM with an underlying Binary Search Tree (BST) structure can be adaptively re-structured using Conditional Rotations (CONROT). These rotations on the nodes of the tree are local, can be done in constant time, and performed so as to decrease the Weighted Path Length (WPL) of the entire tree. In doing this, we introduce the pioneering concept referred to as Neural Promotion, where neurons gain prominence in the Neural Network (NN) as their significance increases. We are not aware of any research which deals with the issue of Neural Promotion. The advantages of such a scheme is that the user need not be aware of any of the topological peculiarities of the stochastic data distribution. Rather, the algorithm, referred to as the TTOSOM with Conditional Rotations (TTOCONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution, and additionally, the neighborhood properties of the neurons suit the best BST that represents the data. These properties have been confirmed by our experimental results on a variety of data sets.
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Swiss Justice Dept: 1 of 7 arrested in FIFA case seeks bail
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Messi, Neymar try not to be upstaged at Copa America
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US, Mali, Serbia, Senegal advance to U20 quarterfinals
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Report: Lazio president Lotito investigated for extortion
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FIFA postpones start of 2026 World Cup bidding amid turmoil
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Mali stuns Ghana, Serbia beats Hungary in U20 playoffs
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UEFA chief Platini meets with French President Hollande
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Newcastle releases Carver, set to announce new manager
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Grandma J's Thanks Anonymous Vandal After 'Busiest Week' Ever
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BBC News Magazine on Twitter: "Overeaters Anonymous is just one of many groups to follow ...
from Google Alert - anonymous https://www.google.com/url?rct=j&sa=t&url=https://twitter.com/BBCNewsMagazine/status/608277428306345984/photo/1&ct=ga&cd=CAIyGjgxMzAxNTQ0ZWE3M2NhMmQ6Y29tOmVuOlVT&usg=AFQjCNE9B9-P_vhKgK3x-zt0Bmcn5zFueQ
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[FD] Heroku Bug Bounty #2 - (API) Re Auth Session Bypass Vulnerability
Source: Gmail -> IFTTT-> Blogger
[FD] Heroku Bug Bounty #2 - (API) Re Auth Session Bypass Vulnerability
Source: Gmail -> IFTTT-> Blogger