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Saturday, June 20, 2015
How to create a block for anonymous uses to enter their contact info
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How do I write an anonymous callback function as a second parameter?
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Germany beats Sweden, China ousts Cameroon at WWCup
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Argentina beats Jamaica to finish 1st in Copa America group
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HR Answers
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Paraguay, Uruguay draw 1-1 and advance to Copa quarters
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Orioles Highlight: Darren O'Day escapes bases-loaded jam in 8th, Manny Machado 2-run double in 9th in win over Blue Jays (ESPN)
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Anonymous on Twitter: "Please join #Anomymous in support of Jeremy Hammond and in protest of ...
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Brazil will appeal Neymar's Copa America suspension
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Orioles: RHP Kevin Gausman reinstated from 15-day DL; RHP Mychal Givens up from Triple-A; RHP Jason Garcia on 60-day DL (ESPN)
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Russian minister: Money not in the way of firing Capello
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Urawa Reds win J-League's first-stage title after 1-1 draw
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This Simple Trick Requires Only Your Phone Number to Hack your Email Account
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Serbia coach hopes for national unity after World Cup win
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5G Mobile Networks to Offer Speed Up To 20Gbps
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Serbia beats Brazil 2-1 in Under-20 World Cup final
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Platini has big decision in great game for FIFA throne
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3rd place: Mali gets 3 late goals, beats Senegal at U20 WCup
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Friday, June 19, 2015
Orioles Video: PH Jimmy Paredes spoils Marco Estrada's no-hit bid with bloop single in 8th in 5-4 loss to Blue Jays (ESPN)
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Brazil's Neymar banned for rest of Copa America
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Chile routs Bolivia to finish 1st in its Copa America group
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[FD] Cross-Site Request Forgery in Google Analyticator Wordpress Plugin v6.4.9.3 before rev @1183563
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[FD] IBM Domino Web Server Cross-site Scripting Vulnerability (CVE-2015-1981)
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Mexico eliminated from Copa America in 2-1 loss to Ecuador
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Orioles: Adam Jones in lineup as DH, batting 3rd Friday vs. Blue Jays; missed last 3 games with sore right shoulder (ESPN)
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Neymar banned for rest of Copa America for violent conduct
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Ravens: Jamison Hensley on the rookies who could start this season, including WR Breshad Perriman, TE Maxx Williams (ESPN)
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Ex-England, Chelsea striker Kerry Dixon jailed for assault
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Aulas ready to spend big to keep Lacazette
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Free Encryption Project to issue First SSL/TLS Certificates Next Month
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[FD] Ebay Magento Bug Bounty #12 - Cross Site Request Forgery Web Vulnerability
[FD] Ebay Magento Bug Bounty #10 - Persistent Filename Vulnerability
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ISS Daily Summary Report – 6/18/15
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[FD] Ebay Magento Bug Bounty #17 - Client Side Cross Site Scripting Web Vulnerability
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[FD] ZTE ZXV10 W300 v3.1.0c_DR0 - UI Session Delete Vulnerability
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[FD] ManageEngine SupportCenter Plus 7.90 - Multiple Vulnerabilities
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Blatter says FIFA officials should pass integrity checks
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Samsung Flaw Lets Hacker Easily Take Control of Your Galaxy Mobile Remotely
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Angry Marseille fans call for president's resignation
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Zero-Day Exploits for Stealing OS X and iOS Passwords
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The anonymous artist leaving empowering notes for women
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Brazil has history on its side in U20 World Cup final
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Tropical Storm Bill Over Texas
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M64: The Black Eye Galaxy
Thursday, June 18, 2015
[FD] Broken, Abandoned, and Forgotten Code, Part 8
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[FD] CVE-2015-4453 - Authentication bypass in OpenEMR
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Peru defeats 10-man Venezuela 1-0 on Claudio Pizarro goal
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I have a new follower on Twitter
Tina Long
Marriage is a three ring circus: engagement ring, wedding ring, and suffering.
Houston
Following: 1233 - Followers: 232
June 18, 2015 at 09:03PM via Twitter http://twitter.com/TinaLlong
Emergence of synchrony in an Adaptive Interaction Model. (arXiv:1506.05573v1 [cs.HC])
In a Human-Computer Interaction context, we aim to elaborate an adaptive and generic interaction model in two different use cases: Embodied Conversational Agents and Creative Musical Agents for musical improvisation. To reach this goal, we'll try to use the concepts of adaptation and synchronization to enhance the interactive abilities of our agents and guide the development of our interaction model, and will try to make synchrony emerge from non-verbal dimensions of interaction.
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A hybrid algorithm for Bayesian network structure learning with application to multi-label learning. (arXiv:1506.05692v1 [stat.ML])
We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges. The algorithm is based on divide-and-conquer constraint-based subroutines to learn the local structure around a target variable. We conduct two series of experimental comparisons of H2PC against Max-Min Hill-Climbing (MMHC), which is currently the most powerful state-of-the-art algorithm for Bayesian network structure learning. First, we use eight well-known Bayesian network benchmarks with various data sizes to assess the quality of the learned structure returned by the algorithms. Our extensive experiments show that H2PC outperforms MMHC in terms of goodness of fit to new data and quality of the network structure with respect to the true dependence structure of the data. Second, we investigate H2PC's ability to solve the multi-label learning problem. We provide theoretical results to characterize and identify graphically the so-called minimal label powersets that appear as irreducible factors in the joint distribution under the faithfulness condition. The multi-label learning problem is then decomposed into a series of multi-class classification problems, where each multi-class variable encodes a label powerset. H2PC is shown to compare favorably to MMHC in terms of global classification accuracy over ten multi-label data sets covering different application domains. Overall, our experiments support the conclusions that local structural learning with H2PC in the form of local neighborhood induction is a theoretically well-motivated and empirically effective learning framework that is well suited to multi-label learning. The source code (in R) of H2PC as well as all data sets used for the empirical tests are publicly available.
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FastMMD: Ensemble of Circular Discrepancy for Efficient Two-Sample Test. (arXiv:1405.2664v2 [cs.AI] UPDATED)
The maximum mean discrepancy (MMD) is a recently proposed test statistic for two-sample test. Its quadratic time complexity, however, greatly hampers its availability to large-scale applications. To accelerate the MMD calculation, in this study we propose an efficient method called FastMMD. The core idea of FastMMD is to equivalently transform the MMD with shift-invariant kernels into the amplitude expectation of a linear combination of sinusoid components based on Bochner's theorem and Fourier transform (Rahimi & Recht, 2007). Taking advantage of sampling of Fourier transform, FastMMD decreases the time complexity for MMD calculation from $O(N^2 d)$ to $O(L N d)$, where $N$ and $d$ are the size and dimension of the sample set, respectively. Here $L$ is the number of basis functions for approximating kernels which determines the approximation accuracy. For kernels that are spherically invariant, the computation can be further accelerated to $O(L N \log d)$ by using the Fastfood technique (Le et al., 2013). The uniform convergence of our method has also been theoretically proved in both unbiased and biased estimates. We have further provided a geometric explanation for our method, namely ensemble of circular discrepancy, which facilitates us to understand the insight of MMD, and is hopeful to help arouse more extensive metrics for assessing two-sample test. Experimental results substantiate that FastMMD is with similar accuracy as exact MMD, while with faster computation speed and lower variance than the existing MMD approximation methods.
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Multi-Context Models for Reasoning under Partial Knowledge: Generative Process and Inference Grammar. (arXiv:1412.4271v2 [cs.AI] UPDATED)
Arriving at the complete probabilistic knowledge of a domain, i.e., learning how all variables interact, is indeed a demanding task. In reality, settings often arise for which an individual merely possesses partial knowledge of the domain, and yet, is expected to give adequate answers to a variety of posed queries. That is, although precise answers to some queries, in principle, cannot be achieved, a range of plausible answers is attainable for each query given the available partial knowledge. In this paper, we propose the Multi-Context Model (MCM), a new graphical model to represent the state of partial knowledge as to a domain. MCM is a middle ground between Probabilistic Logic, Bayesian Logic, and Probabilistic Graphical Models. For this model we discuss: (i) the dynamics of constructing a contradiction-free MCM, i.e., to form partial beliefs regarding a domain in a gradual and probabilistically consistent way, and (ii) how to perform inference, i.e., to evaluate a probability of interest involving some variables of the domain.
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Minimizing Regret in Dynamic Decision Problems. (arXiv:1502.00152v2 [cs.AI] UPDATED)
The menu-dependent nature of regret-minimization creates subtleties when it is applied to dynamic decision problems. Firstly, it is not clear whether \emph{forgone opportunities} should be included in the \emph{menu}, with respect to which regrets are computed, at different points of the decision problem. If forgone opportunities are included, however, we can characterize when a form of dynamic consistency is guaranteed. Secondly, more subtleties arise when sophistication is used to deal with dynamic inconsistency. In the full version of this paper, we examine, axiomatically and by common examples, the implications of different menu definitions for sophisticated, regret-minimizing agents.
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Exact Hybrid Covariance Thresholding for Joint Graphical Lasso. (arXiv:1503.02128v2 [cs.LG] UPDATED)
This paper considers the problem of estimating multiple related Gaussian graphical models from a $p$-dimensional dataset consisting of different classes. Our work is based upon the formulation of this problem as group graphical lasso. This paper proposes a novel hybrid covariance thresholding algorithm that can effectively identify zero entries in the precision matrices and split a large joint graphical lasso problem into small subproblems. Our hybrid covariance thresholding method is superior to existing uniform thresholding methods in that our method can split the precision matrix of each individual class using different partition schemes and thus split group graphical lasso into much smaller subproblems, each of which can be solved very fast. In addition, this paper establishes necessary and sufficient conditions for our hybrid covariance thresholding algorithm. The superior performance of our thresholding method is thoroughly analyzed and illustrated by a few experiments on simulated data and real gene expression data.
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Learning Scale-Free Networks by Dynamic Node-Specific Degree Prior. (arXiv:1503.02129v3 [cs.LG] UPDATED)
Learning the network structure underlying data is an important problem in machine learning. This paper introduces a novel prior to study the inference of scale-free networks, which are widely used to model social and biological networks. The prior not only favors a desirable global node degree distribution, but also takes into consideration the relative strength of all the possible edges adjacent to the same node and the estimated degree of each individual node.
To fulfill this, ranking is incorporated into the prior, which makes the problem challenging to solve. We employ an ADMM (alternating direction method of multipliers) framework to solve the Gaussian Graphical model regularized by this prior. Our experiments on both synthetic and real data show that our prior not only yields a scale-free network, but also produces many more correctly predicted edges than the others such as the scale-free inducing prior, the hub-inducing prior and the $l_1$ norm.
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A New Fundamental Evidence of Non-Classical Structure in the Combination of Natural Concepts. (arXiv:1505.04981v2 [cs.AI] UPDATED)
We recently performed cognitive experiments on conjunctions and negations of two concepts with the aim of investigating the combination problem of concepts. Our experiments confirmed the deviations (conceptual vagueness, underextension, overextension, etc.) from the rules of classical (fuzzy) logic and probability theory observed by several scholars in concept theory, while our data were successfully modeled in a quantum-theoretic framework developed by ourselves. In this paper, we isolate a new, very stable and systematic pattern of violation of classicality that occurs in concept combinations. In addition, the strength and regularity of this non-classical effect leads us to believe that it occurs at a more fundamental level than the deviations observed up to now. It is our opinion that we have identified a deep non-classical mechanism determining not only how concepts are combined but, rather, how they are formed. We show that this effect can be faithfully modeled in a two-sector Fock space structure, and that it can be exactly explained by assuming that human thought is the supersposition of two processes, a 'logical reasoning', guided by 'logic', and a 'conceptual reasoning' guided by 'emergence', and that the latter generally prevails over the former. All these findings provide a new fundamental support to our quantum-theoretic approach to human cognition.
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Fox's Van Susteren hits media for 'anonymous trash talkers'
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Orioles Video: Manny Machado's 1st-inning HR is all the offense in 2-1 loss to Phillies; Bud Norris 5 H, 2 ER in 6.0 IP (ESPN)
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Liberia soccer chief announces run for FIFA presidency
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Neymar in danger of missing Copa America quarterfinals
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Liberia FA head Bility announces run for FIFA presidency
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Argentines wanted in FIFA probe turn themselves in
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Swiss champion Basel hires Urs Fischer as coach
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ISS Daily Summary Report – 6/17/2015
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Greece: Olympiakos chairman released on bail
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Belgium weighs compensation claim for losing World Cup bid
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Marseille signs France U21 midifielder Nkoudou
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Anonymous Claims Responsibility for Cyber Attack on Canadian Government Websites
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M45: The Pleiades Star Cluster
Wednesday, June 17, 2015
Neymar sent off as Colombia beats Brazil 1-0 in Copa America
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Fulham assistant Miller is new Newcastle coach in A-League
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Colombia beats Brazil 1-0 in Copa America
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Orioles Highlight: Chris Parmelee homers for 3rd time in 2 games as Baltimore makes it 3 straight wins over Philadelphia (ESPN)
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SNA-based reasoning for multiagent team composition. (arXiv:1506.05154v1 [cs.MA])
The social network analysis (SNA), branch of complex systems can be used in the construction of multiagent systems. This paper proposes a study of how social network analysis can assist in modeling multiagent systems, while addressing similarities and differences between the two theories. We built a prototype of multi-agent systems for resolution of tasks through the formation of teams of agents that are formed on the basis of the social network established between agents. Agents make use of performance indicators to assess when should change their social network to maximize the participation in teams
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SAT-based Analysis of Large Real-world Feature Models is Easy. (arXiv:1506.05198v1 [cs.SE])
Modern conflict-driven clause-learning (CDCL) Boolean SAT solvers provide efficient automatic analysis of real-world feature models (FM) of systems ranging from cars to operating systems. It is well-known that solver-based analysis of real-world FMs scale very well even though SAT instances obtained from such FMs are large, and the corresponding analysis problems are known to be NP-complete. To better understand why SAT solvers are so effective, we systematically studied many syntactic and semantic characteristics of a representative set of large real-world FMs. We discovered that a key reason why large real-world FMs are easy-to-analyze is that the vast majority of the variables in these models are unrestricted, i.e., the models are satisfiable for both true and false assignments to such variables under the current partial assignment. Given this discovery and our understanding of CDCL SAT solvers, we show that solvers can easily find satisfying assignments for such models without too many backtracks relative to the model size, explaining why solvers scale so well. Further analysis showed that the presence of unrestricted variables in these real-world models can be attributed to their high-degree of variability. Additionally, we experimented with a series of well-known non-backtracking simplifications that are particularly effective in solving FMs. The remaining variables/clauses after simplifications, called the core, are so few that they are easily solved even with backtracking, further strengthening our conclusions.
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Why Bother With Syntax?. (arXiv:1506.05282v1 [cs.AI])
This short note discusses the role of syntax vs. semantics and the interplay between logic, philosophy, and language in computer science and game theory.
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Early Predictions of Movie Success: the Who, What, and When of Profitability. (arXiv:1506.05382v1 [cs.AI])
This paper proposes a decision support system to aid movie investment decisions at the early stage of movie productions. The system predicts the success of a movie based on its profitability by leveraging historical data from various sources. Using social network analysis and text mining techniques, the system automatically extracts several groups of features, including "who" are on the cast, "what" a movie is about, "when" a movie will be released, as well as "hybrid" features that match "who" with "what", and "when" with "what". Our experiments with movies during an 11-year period showcase the system's decent performance in predicting movie success. Moreover, experiment results also suggest that different groups of features, including novel features we proposed, all contribute to the prediction.
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Hybrid Algorithm for Multi-Objective Optimization by Greedy Hypervolume Maximization. (arXiv:1506.05424v1 [cs.NE])
This paper introduces a high-performance hybrid algorithm, called Hybrid Hypervolume Maximization Algorithm (H2MA), for multi-objective optimization that alternates between exploring the decision space and exploiting the already obtained non-dominated solutions. The proposal is centered on maximizing the hypervolume indicator, thus converting the multi-objective problem into a single-objective one. The exploitation employs gradient-based methods, but considering a single candidate efficient solution at a time, to overcome limitations associated with population-based approaches and also to allow an easy control of the number of solutions provided. There is an interchange between two steps. The first step is a deterministic local exploration, endowed with an automatic procedure to detect stagnation. When stagnation is detected, the search is switched to a second step characterized by a stochastic global exploration using an evolutionary algorithm. Using five ZDT benchmarks with 30 variables, the performance of the new algorithm is compared to state-of-the-art algorithms for multi-objective optimization, more specifically NSGA-II, SPEA2, and SMS-EMOA. The solutions found by the H2MA guide to higher hypervolume and smaller distance to the true Pareto frontier with significantly less function evaluations, even when the gradient is estimated numerically. Furthermore, although only continuous decision spaces have been considered here, discrete decision spaces could also have been treated, replacing gradient-based search by hill-climbing. Finally, a thorough explanation is provided to support the expressive gain in performance that was achieved.
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Fair assignment of indivisible objects under ordinal preferences. (arXiv:1312.6546v4 [cs.GT] UPDATED)
We consider the discrete assignment problem in which agents express ordinal preferences over objects and these objects are allocated to the agents in a fair manner. We use the stochastic dominance relation between fractional or randomized allocations to systematically define varying notions of proportionality and envy-freeness for discrete assignments. The computational complexity of checking whether a fair assignment exists is studied for these fairness notions. We also characterize the conditions under which a fair assignment is guaranteed to exist. For a number of fairness concepts, polynomial-time algorithms are presented to check whether a fair assignment exists. Our algorithmic results also extend to the case of unequal entitlements of agents. Our NP-hardness result, which holds for several variants of envy-freeness, answers an open question posed by Bouveret, Endriss, and Lang (ECAI 2010). We also propose fairness concepts that always suggest a non-empty set of assignments with meaningful fairness properties. Among these concepts, optimal proportionality and optimal weak proportionality appear to be desirable fairness concepts.
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Swiss champion Basel agrees to end coach Sousa's contract
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[FD] [CVE-2015-4553]Dedecms variable coverage leads to getshell
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Re: [FD] Announcing NorthSec 2015 - Montreal, May 21-24
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Vidal appears in court; gets 4 month driving ban after DUI
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ECHR Finds Website Liable for Anonymous User Comments
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Leicester fires 3 players over sex tape in Thailand
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New Zealand sets England victory target of 350 in 4th ODI
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Arsenal's Jack Wilshere fined over parade outburst
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Arsenal's Jack Wilshere fined over parade outburst
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FIFA prosecutor ready to act as World Cup bids probe widens
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Anonymous on Twitter: "Don't abuse government power, don't censor the web, and don't arrest ...
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Moenchengladbach signs striker Drmic from Leverkusen
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ISS Daily Summary Report – 06/16/15
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PFF President suspended over financial embezzlement, report
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Sounders finish with 7 men in US Open Cup
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Swiss bank named in FIFA indictment opens investigation
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Asian confederation general secretary quits amid probe
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Brazil to meet Serbia in Under-20 World Cup final
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Capello on the brink with Russian football in crisis
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Serbia advances to under-20 World Cup final vs Brazil
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Pavel Kaderabek moves to Hoffenheim from Sparta Prague
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I have a new follower on Twitter
Ways to Stay Fit
It's the little things that you do each day that add up to being healthy and fit.
Following: 457 - Followers: 278
June 17, 2015 at 06:25AM via Twitter http://twitter.com/WaystoStayFitt
Swiss AG: 53 possible money-laundering cases in FIFA probe
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Chelsea opens EPL defense against Swansea, Man U hosts Spurs
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Brazil builds confidence with U20 World Cup semifinal win
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Brazil beats Senegal 5-0 to reach U20 WCup final
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Asian powers unconvincing in World Cup qualifying
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