pinecone/core-2020-05-10-deduplication huggingface dataset:
Modeling Features at Runtime

International audienceA feature represents a functional requirement fulfilled by a system. Since many maintenance tasks are expressed in terms of features, it is important to establish the correspondence between a feature and its implementation in source code. Traditional approaches to establish this correspondence exercise features to generate a trace of runtime events, which is then processed by post-mortem analysis. These approaches typically generate large amounts of data to analyze. Due to their static nature, these approaches do not support incremental and interactive analysis of features. We propose a radically different approach called live feature analysis, which provides a model at runtime of features. Our approach analyzes features on a running system and also makes it possible to grow feature representations by exercising different scenarios of the same feature, and identifies execution elements even to the sub-method level. We describe how live feature analysis is implemented effectively by annotating structural representations of code based on abstract syntax trees. We illustrate our live analysis with a case study where we achieve a more complete feature representation by exercising and merging variants of feature behavior and demonstrate the efficiency or our technique with benchmarks
Piecewise affine models of regulatory genetic networks: review and probabilistic interpretation

International audienceA formalism based on piecewise-affine (PWA) differential equations has been shown to be well-suited to modelling genetic regulatory networks. In this paper, we first review some results concerning the qualitative study of these models: we partition the phase space into domains bounded by the threshold hyperplanes. Inside each domain, the system is affine. To define solutions on the surfaces of discontinuity, we use the approach of Filippov, which extends the vector field to a differential inclusion. We obtain a transition graph, describing qualitatively the possible transitions of solutions between domains. In a second part of the paper, we give a new probabilistic interpretation of these transitions, by computing the proportion of the volume of the domain that crosses to one of its adjacent domains.We apply this idea to the model of the bistable switch and to parameter estimation from experimental transition probabilities
Control problems for one-dimensional fluids and reactive fluids with moving interfaces

The purpose of this paper is to expose several recent challenging control problems for mono-dimensional fluids or reactive fluids. These problems have in common the existence of a moving interface separating two spatial zones where the dynamics are rather different. All these problems are grounded on topics of engineering interest. The aim of the author is to expose the main control issues, possible solutions and to spur an interest for other future contributors. As will appear, mobile interfaces play key roles in various problems, and truly capture main phenomena at stake in the dynamics of the considered systems
Using Hamiltonians to Model Saturation in Space Vector Representations of AC Electrical Machines

An Hamiltonian formulation with complex fluxes and currents is proposed. This formulation is derived from a recent Lagrangian formulation with complex electrical quantities. The complexification process avoids the usual separation into real and imaginary parts and notably simplifies modeling issues. Simple modifications of the magnetic energy underlying standard (α,β) models yield new (α,β) models describing machines with magnetic saturation and saliency. We prove that the usual expression of the electro-mechanical torque (wedge product of fluxes and currents) is related to a rotational invariance characterizing sinusoidal machines
High-Level Modeling of Component-Based CSPs

International audienceMost of modern constraint modeling languages combine rich constraint languages with mathematical notations to tackle combinato- rial optimization problems. Our purpose is to introduce new component- oriented language constructs to manipulate hierarchical problems, for instance for modeling engineering system architectures with conditional sub-problems. To this end, an object-oriented modeling language is as- sociated with a powerful constraint language. It offers the possibility of defining conditional components to be activated at solving time, declar- ing polymorphic components whose concrete types have to be deter- mined, and overriding model elements. We illustrate the benefits of this new approach in the modeling process of a difficult embodiment design problem having several architectural alternatives
Generic meta-modelling with concepts, templates and mixin layers

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-16145-2_2Proceedings of 13th International Conference, MODELS 2010, Oslo, Norway, October 3-8, 2010.Meta-modelling is a key technique in Model Driven Engineering, where it is used for language engineering and domain modelling. However, mainstream approaches like the OMG’s Meta-Object Facility provide little support for abstraction, modularity, reusability and extendibility of (meta-)models, behaviours and transformations.
In order to alleviate this weakness, we bring three elements of generic programming into meta-modelling: concepts, templates and mixin layers. Concepts permit an additional typing for models, enabling the definition of behaviours and transformations independently of meta-models, making specifications reusable. Templates use concepts to express requirements on their generic parameters, and are applicable to models and meta-models. Finally, we define functional layers by means of meta-model mixins which can extend other meta-models.
As a proof of concept we also report on MetaDepth, a multi-level meta-modelling framework that implements these ideas.Work sponsored by the Spanish Ministry of Science, project TIN2008-02081 and mobility grants JC2009-00015 and PR2009-0019, and by the  R&D programme of the Community of Madrid, project S2009/TIC-165
On Learning Algorithms for Nash Equilibria

Can learning algorithms find a Nash equilibrium? This is a natural question for several reasons. Learning algorithms resemble the behavior of players in many naturally arising games, and thus results on the convergence or non-convergence properties of such dynamics may inform our understanding of the applicability of Nash equilibria as a plausible solution concept in some settings. A second reason for asking this question is in the hope of being able to prove an impossibility result, not dependent on complexity assumptions, for computing Nash equilibria via a restricted class of reasonable algorithms. In this work, we begin to answer this question by considering the dynamics of the standard multiplicative weights update learning algorithms (which are known to converge to a Nash equilibrium for zero-sum games). We revisit a 3×3 game defined by Shapley [10] in the 1950s in order to establish that fictitious play does not converge in general games. For this simple game, we show via a potential function argument that in a variety of settings the multiplicative updates algorithm impressively fails to find the unique Nash equilibrium, in that the cumulative distributions of players produced by learning dynamics actually drift away from the equilibrium.Third International Symposium, SAGT 2010, Athens, Greece, October 18-20, 2010. Proceeding
A Direct Reduction from k-Player to 2-Player Approximate Nash
  Equilibrium

We present a direct reduction from k-player games to 2-player games that
preserves approximate Nash equilibrium. Previously, the computational
equivalence of computing approximate Nash equilibrium in k-player and 2-player
games was established via an indirect reduction. This included a sequence of
works defining the complexity class PPAD, identifying complete problems for
this class, showing that computing approximate Nash equilibrium for k-player
games is in PPAD, and reducing a PPAD-complete problem to computing approximate
Nash equilibrium for 2-player games. Our direct reduction makes no use of the
concept of PPAD, thus eliminating some of the difficulties involved in
following the known indirect reduction.Comment: 21 page
Bottleneck Routing Games with Low Price of Anarchy

We study {\em bottleneck routing games} where the social cost is determined
by the worst congestion on any edge in the network. In the literature,
bottleneck games assume player utility costs determined by the worst congested
edge in their paths. However, the Nash equilibria of such games are inefficient
since the price of anarchy can be very high and proportional to the size of the
network. In order to obtain smaller price of anarchy we introduce {\em
exponential bottleneck games} where the utility costs of the players are
exponential functions of their congestions. We find that exponential bottleneck
games are very efficient and give a poly-log bound on the price of anarchy:
$O(\log L \cdot \log |E|)$, where $L$ is the largest path length in the
players' strategy sets and $E$ is the set of edges in the graph. By adjusting
the exponential utility costs with a logarithm we obtain games whose player
costs are almost identical to those in regular bottleneck games, and at the
same time have the good price of anarchy of exponential games.Comment: 12 page
Single Parameter Combinatorial Auctions with Partially Public Valuations

We consider the problem of designing truthful auctions, when the bidders'
valuations have a public and a private component. In particular, we consider
combinatorial auctions where the valuation of an agent $i$ for a set $S$ of
items can be expressed as $v_if(S)$, where $v_i$ is a private single parameter
of the agent, and the function $f$ is publicly known. Our motivation behind
studying this problem is two-fold: (a) Such valuation functions arise naturally
in the case of ad-slots in broadcast media such as Television and Radio. For an
ad shown in a set $S$ of ad-slots, $f(S)$ is, say, the number of {\em unique}
viewers reached by the ad, and $v_i$ is the valuation per-unique-viewer. (b)
From a theoretical point of view, this factorization of the valuation function
simplifies the bidding language, and renders the combinatorial auction more
amenable to better approximation factors. We present a general technique, based
on maximal-in-range mechanisms, that converts any $\alpha$-approximation
non-truthful algorithm ($\alpha \leq 1$) for this problem into
$\Omega(\frac{\alpha}{\log{n}})$ and $\Omega(\alpha)$-approximate truthful
mechanisms which run in polynomial time and quasi-polynomial time,
respectively
Braess's Paradox for Flows Over Time

We study the properties of Braess's paradox in the context of the model of
congestion games with flow over time introduced by Koch and Skutella. We
compare them to the well known properties of Braess's paradox for Wardrop's
model of games with static flows. We show that there are networks which do not
admit Braess's paradox in Wardrop's model, but which admit it in the model with
flow over time. Moreover, there is a topology that admits a much more severe
Braess's ratio for this model. Further, despite its symmetry for games with
static flow, we show that Braess's paradox is not symmetric for flows over
time. We illustrate that there are network topologies which exhibit Braess's
paradox, but for which the transpose does not. Finally, we conjecture a
necessary and sufficient condition of existence of Braess's paradox in a
network, and prove the condition of existence of the paradox either in the
network or in its transpose.Comment: 19 pages, 6 figures, an extended version of paper accepted for SAGT
  201
Truthful Fair Division

We address the problem of fair division, or cake cutting, with the goal of
finding truthful mechanisms. In the case of a general measure space ("cake")
and non-atomic, additive individual preference measures - or utilities - we
show that there exists a truthful "mechanism" which ensures that each of the k
players gets at least 1/k of the cake. This mechanism also minimizes risk for
truthful players. Furthermore, in the case where there exist at least two
different measures we present a different truthful mechanism which ensures that
each of the players gets more than 1/k of the cake.
  We then turn our attention to partitions of indivisible goods with bounded
utilities and a large number of goods. Here we provide similar mechanisms, but
with slightly weaker guarantees. These guarantees converge to those obtained in
the non-atomic case as the number of goods goes to infinity.Comment: 10 page
2-Player Nash and Nonsymmetric Bargaining Games: Algorithms and
  Structural Properties

The solution to a Nash or a nonsymmetric bargaining game is obtained by
maximizing a concave function over a convex set, i.e., it is the solution to a
convex program. We show that each 2-player game whose convex program has linear
constraints, admits a rational solution and such a solution can be found in
polynomial time using only an LP solver. If in addition, the game is succinct,
i.e., the coefficients in its convex program are ``small'', then its solution
can be found in strongly polynomial time. We also give a non-succinct linear
game whose solution can be found in strongly polynomial time
Nash equilibria in Fisher market

Much work has been done on the computation of market equilibria. However due
to strategic play by buyers, it is not clear whether these are actually
observed in the market. Motivated by the observation that a buyer may derive a
better payoff by feigning a different utility function and thereby manipulating
the Fisher market equilibrium, we formulate the {\em Fisher market game} in
which buyers strategize by posing different utility functions. We show that
existence of a {\em conflict-free allocation} is a necessary condition for the
Nash equilibria (NE) and also sufficient for the symmetric NE in this game.
There are many NE with very different payoffs, and the Fisher equilibrium
payoff is captured at a symmetric NE. We provide a complete polyhedral
characterization of all the NE for the two-buyer market game. Surprisingly, all
the NE of this game turn out to be symmetric and the corresponding payoffs
constitute a piecewise linear concave curve. We also study the correlated
equilibria of this game and show that third-party mediation does not help to
achieve a better payoff than NE payoffs
Mixing Time and Stationary Expected Social Welfare of Logit Dynamics

We study "logit dynamics" [Blume, Games and Economic Behavior, 1993] for
strategic games. This dynamics works as follows: at every stage of the game a
player is selected uniformly at random and she plays according to a "noisy"
best-response where the noise level is tuned by a parameter $\beta$. Such a
dynamics defines a family of ergodic Markov chains, indexed by $\beta$, over
the set of strategy profiles. We believe that the stationary distribution of
these Markov chains gives a meaningful description of the long-term behavior
for systems whose agents are not completely rational.
  Our aim is twofold: On the one hand, we are interested in evaluating the
performance of the game at equilibrium, i.e. the expected social welfare when
the strategy profiles are random according to the stationary distribution. On
the other hand, we want to estimate how long it takes, for a system starting at
an arbitrary profile and running the logit dynamics, to get close to its
stationary distribution; i.e., the "mixing time" of the chain.
  In this paper we study the stationary expected social welfare for the
3-player CK game, for 2-player coordination games, and for two simple
$n$-player games. For all these games, we also give almost tight upper and
lower bounds on the mixing time of logit dynamics. Our results show two
different behaviors: in some games the mixing time depends exponentially on
$\beta$, while for other games it can be upper bounded by a function
independent of $\beta$.Comment: 28 page
The zero exemplar distance problem

Given two genomes with duplicate genes, \textsc{Zero Exemplar Distance} is
the problem of deciding whether the two genomes can be reduced to the same
genome without duplicate genes by deleting all but one copy of each gene in
each genome. Blin, Fertin, Sikora, and Vialette recently proved that
\textsc{Zero Exemplar Distance} for monochromosomal genomes is NP-hard even if
each gene appears at most two times in each genome, thereby settling an
important open question on genome rearrangement in the exemplar model. In this
paper, we give a very simple alternative proof of this result. We also study
the problem \textsc{Zero Exemplar Distance} for multichromosomal genomes
without gene order, and prove the analogous result that it is also NP-hard even
if each gene appears at most two times in each genome. For the positive
direction, we show that both variants of \textsc{Zero Exemplar Distance} admit
polynomial-time algorithms if each gene appears exactly once in one genome and
at least once in the other genome. In addition, we present a polynomial-time
algorithm for the related problem \textsc{Exemplar Longest Common Subsequence}
in the special case that each mandatory symbol appears exactly once in one
input sequence and at least once in the other input sequence. This answers an
open question of Bonizzoni et al. We also show that \textsc{Zero Exemplar
Distance} for multichromosomal genomes without gene order is fixed-parameter
tractable if the parameter is the maximum number of chromosomes in each genome.Comment: Strengthened and reorganize
Real-time image segmentation on a GPU

Trabajo presentado a la Conference for Young Scientists on Facing the Multicore Challenge celebrada en Alemania de 17 al 19 de marzo de 2010.Efficient segmentation of color images is important for many applications in computer vision. Non-parametric solutions are required in situations where little or no prior knowledge about the data is available. In this paper, we present a novel parallel image segmentation algorithm which segments images in real-time in a non-parametric way. The algorithm ﬁnds the equilibrium states of a Potts model in the superparamagnetic phase of the system. Our method maps perfectly onto the Graphics Processing Unit (GPU) architecture and has been implemented using the framework NVIDIA Compute Unified Device Architecture (CUDA). For images of 256 × 320 pixels we obtained a frame rate of 30 Hz that demonstrates the applicability of the algorithm to video-processing tasks in real-time.This work was supported by the project 'Perception, action & cognition through learning of object-action complexes.' (4915). The work has received support from the German Ministry for Education and Research (BMBF) via the Bernstein Center for Computational Neuroscience (BCCN) G ottingen and the EU Project PACO-PLUS. B.D. also acknowledges support from Spanish Ministry for Science and Innovation via a Ramon y Cajal\ud
fellowship.Peer Reviewe
Improved Scalability By Using Hardware-Aware Thread Affinities

The complexity of an efficient thread management steadily rises with the number of processor cores and heterogeneities in the design of system architectures, e.g., the topologies of execution units and the memory architecture. In this paper, we show that using information about the system topology combined with a hardware-aware thread management is worthwhile. We present such a hardware-aware approach that utilizes thread affinity to automatically steer the mapping of threads to cores and experimentally analyze its performance. Our experiments show that we can achieve significantly better scalability and runtime stability compared to the ordinary dispatching of threads provided by the operating system
Computational Algorithm for Some Problems with Variable Geometrical Structure

International audienceThe work is devoted to the computational algorithm for a problem of plant growth. The plant is represented as a system of connected intervals corresponding to branches. We compute the concentration distributions inside the branches. The originality of the problem is that the geometry of the plant is not a priori given. It evolves in time depending on the concentrations of plant hormones found as a solution of the problem. New branches appear in the process of plant growth. The algorithm is adapted to an arbitrary plant structure and an arbitrary number of branches
Magically Constraining the Inverse Method Using Dynamic Polarity Assignment

International audienceGiven a logic program that is terminating and mode-correct in an idealized Prolog interpreter (i.e., in a top-down logic programming engine), a bottom-up logic programming engine can be used to compute exactly the same set of answers as the top-down engine for a given mode-correct query by rewriting the program and the query using the Magic Sets Transformation (MST). In previous work, we have shown that focusing can logically characterize the standard notion of bottom-up logic programming if atomic formulas are statically given a certain polarity assignment. In an analogous manner, dynamically assigning polarities can characterize the effect of MST without needing to transform the program or the query. This gives us a new proof of the completeness of MST in purely logical terms, by using the general completeness theorem for focusing. As the dynamic assignment is done in a general logic, the essence of MST can potentially be generalized to larger fragments of logic
Characterising Probabilistic Processes Logically

In this paper we work on (bi)simulation semantics of processes that exhibit
both nondeterministic and probabilistic behaviour. We propose a probabilistic
extension of the modal mu-calculus and show how to derive characteristic
formulae for various simulation-like preorders over finite-state processes
without divergence. In addition, we show that even without the fixpoint
operators this probabilistic mu-calculus can be used to characterise these
behavioural relations in the sense that two states are equivalent if and only
if they satisfy the same set of formulae.Comment: 18 page
Variable compression in ProbLog

acceptance rate: 38%In order to compute the probability of a query, ProbLog represents the proofs of the query as disjunctions of conjunctions, for which a Reduced Ordered Binary Decision Diagram (ROBDD) is computed. The paper identifies patterns of Boolean variables that occur in Boolean formulae, namely AND-clusters and OR-clusters. Our method compresses the variables in these clusters and thus reduces the size of ROBDDs without affecting the probability.

We give a polynomial algorithm that detects AND-clusters in disjunctive normal form (DNF) Boolean formulae, or OR-clusters in conjunctive normal form (CNF) Boolean formulae.

We do an experimental evaluation of the effects of AND-cluster compression for a real application of ProbLog. With our prototype implementation we have a significant improvement in performance (up to 87%) for the generation of ROBDDs. Moreover, compressing AND-clusters of Boolean variables in the DNFs makes it feasible to deal with ProbLog queries that give rise to larger DNFs.status: publishe
Ordered weighted average based fuzzy rough sets

Traditionally, membership to the fuzzy-rough lower, resp. upper approximation is determined by looking only at the worst, resp. best performing object. Consequently, when applied to data analysis problems, these approximations are sensitive to noisy and/or outlying samples. In this paper, we advocate a mitigated approach, in which membership to the lower and upper approximation is determined by means of an aggregation process using ordered weighted average operators. In comparison to the previously introduced vaguely quantified rough set model, which is based on a similar rationale, our proposal has the advantage that the approximations are monotonous w.r.t. the used fuzzy indiscernibility relation. Initial experiments involving a feature selection application confirm the potential of the OWA-based model