Subjects -> MATHEMATICS (Total: 1100 journals)
    - APPLIED MATHEMATICS (88 journals)
    - GEOMETRY AND TOPOLOGY (23 journals)
    - MATHEMATICS (812 journals)
    - MATHEMATICS (GENERAL) (43 journals)
    - NUMERICAL ANALYSIS (24 journals)
    - PROBABILITIES AND MATH STATISTICS (110 journals)

MATHEMATICS (812 journals)                  1 2 3 4 5 | Last

Showing 1 - 200 of 538 Journals sorted alphabetically
Abakós     Open Access   (Followers: 5)
Abhandlungen aus dem Mathematischen Seminar der Universitat Hamburg     Hybrid Journal   (Followers: 4)
Academic Voices : A Multidisciplinary Journal     Open Access   (Followers: 2)
Accounting Perspectives     Full-text available via subscription   (Followers: 7)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Mathematical Software (TOMS)     Hybrid Journal   (Followers: 6)
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 40)
Acta Applicandae Mathematicae     Hybrid Journal   (Followers: 1)
Acta Mathematica     Hybrid Journal   (Followers: 12)
Acta Mathematica Hungarica     Hybrid Journal   (Followers: 2)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5)
Acta Mathematica Sinica, English Series     Hybrid Journal   (Followers: 6)
Acta Mathematica Vietnamica     Hybrid Journal  
Acta Mathematicae Applicatae Sinica, English Series     Hybrid Journal  
Advanced Science Letters     Full-text available via subscription   (Followers: 12)
Advances in Applied Clifford Algebras     Hybrid Journal   (Followers: 4)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 6)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 10)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 23)
Advances in Decision Sciences     Open Access   (Followers: 4)
Advances in Difference Equations     Open Access   (Followers: 3)
Advances in Fixed Point Theory     Open Access   (Followers: 8)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 19)
Advances in Linear Algebra & Matrix Theory     Open Access   (Followers: 11)
Advances in Materials Science     Open Access   (Followers: 19)
Advances in Mathematical Physics     Open Access   (Followers: 8)
Advances in Mathematics     Full-text available via subscription   (Followers: 17)
Advances in Nonlinear Analysis     Open Access   (Followers: 1)
Advances in Numerical Analysis     Open Access   (Followers: 9)
Advances in Operations Research     Open Access   (Followers: 13)
Advances in Operator Theory     Hybrid Journal   (Followers: 4)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Pure and Applied Mathematics     Hybrid Journal   (Followers: 10)
Advances in Pure Mathematics     Open Access   (Followers: 11)
Advances in Science and Research (ASR)     Open Access   (Followers: 9)
Aequationes Mathematicae     Hybrid Journal   (Followers: 2)
African Journal of Educational Studies in Mathematics and Sciences     Full-text available via subscription   (Followers: 9)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 7)
Afrika Matematika     Hybrid Journal   (Followers: 3)
Air, Soil & Water Research     Open Access   (Followers: 13)
AKSIOMA Journal of Mathematics Education     Open Access   (Followers: 3)
AKSIOMATIK : Jurnal Penelitian Pendidikan dan Pembelajaran Matematika     Open Access   (Followers: 1)
Al-Jabar : Jurnal Pendidikan Matematika     Open Access   (Followers: 1)
Al-Qadisiyah Journal for Computer Science and Mathematics     Open Access   (Followers: 1)
AL-Rafidain Journal of Computer Sciences and Mathematics     Open Access   (Followers: 6)
Algebra and Logic     Hybrid Journal   (Followers: 7)
Algebra Colloquium     Hybrid Journal   (Followers: 4)
Algebra Universalis     Hybrid Journal   (Followers: 2)
Algorithmic Operations Research     Open Access   (Followers: 5)
Algorithms     Open Access   (Followers: 12)
Algorithms Research     Open Access   (Followers: 1)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 10)
American Journal of Mathematical Analysis     Open Access   (Followers: 2)
American Journal of Mathematical and Management Sciences     Hybrid Journal   (Followers: 1)
American Journal of Mathematics     Full-text available via subscription   (Followers: 7)
American Journal of Operations Research     Open Access   (Followers: 8)
American Mathematical Monthly     Full-text available via subscription   (Followers: 6)
An International Journal of Optimization and Control: Theories & Applications     Open Access   (Followers: 11)
Anadol University Journal of Science and Technology B : Theoritical Sciences     Open Access  
Analele Universitatii Ovidius Constanta - Seria Matematica     Open Access  
Analysis and Applications     Hybrid Journal   (Followers: 1)
Analysis and Mathematical Physics     Hybrid Journal   (Followers: 6)
Analysis Mathematica     Full-text available via subscription  
Analysis. International mathematical journal of analysis and its applications     Hybrid Journal   (Followers: 5)
Anargya : Jurnal Ilmiah Pendidikan Matematika     Open Access   (Followers: 7)
Annales Mathematicae Silesianae     Open Access   (Followers: 2)
Annales mathématiques du Québec     Hybrid Journal   (Followers: 4)
Annales Universitatis Mariae Curie-Sklodowska, sectio A – Mathematica     Open Access   (Followers: 1)
Annales Universitatis Paedagogicae Cracoviensis. Studia Mathematica     Open Access  
Annali di Matematica Pura ed Applicata     Hybrid Journal   (Followers: 1)
Annals of Combinatorics     Hybrid Journal   (Followers: 4)
Annals of Data Science     Hybrid Journal   (Followers: 13)
Annals of Discrete Mathematics     Full-text available via subscription   (Followers: 8)
Annals of Functional Analysis     Hybrid Journal   (Followers: 4)
Annals of Mathematics     Full-text available via subscription   (Followers: 2)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 14)
Annals of PDE     Hybrid Journal  
Annals of Pure and Applied Logic     Open Access   (Followers: 4)
Annals of the Alexandru Ioan Cuza University - Mathematics     Open Access  
Annals of the Institute of Statistical Mathematics     Hybrid Journal   (Followers: 1)
Annals of West University of Timisoara - Mathematics     Open Access  
Annals of West University of Timisoara - Mathematics and Computer Science     Open Access   (Followers: 2)
Annuaire du Collège de France     Open Access   (Followers: 6)
ANZIAM Journal     Open Access   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applications of Mathematics     Hybrid Journal   (Followers: 3)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 14)
Applied Mathematics     Open Access   (Followers: 4)
Applied Mathematics     Open Access   (Followers: 8)
Applied Mathematics & Optimization     Hybrid Journal   (Followers: 10)
Applied Mathematics - A Journal of Chinese Universities     Hybrid Journal   (Followers: 1)
Applied Mathematics and Nonlinear Sciences     Open Access  
Applied Mathematics Letters     Full-text available via subscription   (Followers: 4)
Applied Mathematics Research eXpress     Hybrid Journal   (Followers: 1)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 6)
Arab Journal of Mathematical Sciences     Open Access   (Followers: 4)
Arabian Journal of Mathematics     Open Access   (Followers: 2)
Archive for Mathematical Logic     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 6)
Archive of Numerical Software     Open Access  
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
Armenian Journal of Mathematics     Open Access   (Followers: 1)
Arnold Mathematical Journal     Hybrid Journal   (Followers: 1)
Artificial Satellites     Open Access   (Followers: 24)
Asia-Pacific Journal of Operational Research     Hybrid Journal   (Followers: 3)
Asian Journal of Algebra     Open Access   (Followers: 1)
Asian Research Journal of Mathematics     Open Access   (Followers: 1)
Asian-European Journal of Mathematics     Hybrid Journal   (Followers: 3)
Australian Mathematics Teacher, The     Full-text available via subscription   (Followers: 7)
Australian Primary Mathematics Classroom     Full-text available via subscription   (Followers: 5)
Australian Senior Mathematics Journal     Full-text available via subscription   (Followers: 2)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Axioms     Open Access   (Followers: 1)
Baltic International Yearbook of Cognition, Logic and Communication     Open Access   (Followers: 2)
Banach Journal of Mathematical Analysis     Hybrid Journal   (Followers: 2)
Basin Research     Hybrid Journal   (Followers: 5)
BIBECHANA     Open Access   (Followers: 2)
Biomath     Open Access  
BIT Numerical Mathematics     Hybrid Journal   (Followers: 1)
Boletim Cearense de Educação e História da Matemática     Open Access  
Boletim de Educação Matemática     Open Access  
Boletín de la Sociedad Matemática Mexicana     Hybrid Journal  
Bollettino dell'Unione Matematica Italiana     Full-text available via subscription   (Followers: 2)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 18)
Bruno Pini Mathematical Analysis Seminar     Open Access  
Buletinul Academiei de Stiinte a Republicii Moldova. Matematica     Open Access   (Followers: 13)
Bulletin des Sciences Mathamatiques     Full-text available via subscription   (Followers: 4)
Bulletin of Dnipropetrovsk University. Series : Communications in Mathematical Modeling and Differential Equations Theory     Open Access   (Followers: 3)
Bulletin of Mathematical Sciences     Open Access   (Followers: 1)
Bulletin of Symbolic Logic     Full-text available via subscription   (Followers: 2)
Bulletin of the Australian Mathematical Society     Full-text available via subscription   (Followers: 2)
Bulletin of the Brazilian Mathematical Society, New Series     Hybrid Journal  
Bulletin of the Iranian Mathematical Society     Hybrid Journal  
Bulletin of the London Mathematical Society     Hybrid Journal   (Followers: 3)
Bulletin of the Malaysian Mathematical Sciences Society     Hybrid Journal  
Cadernos do IME : Série Matemática     Open Access   (Followers: 1)
Calculus of Variations and Partial Differential Equations     Hybrid Journal  
Canadian Journal of Mathematics / Journal canadien de mathématiques     Hybrid Journal  
Canadian Journal of Science, Mathematics and Technology Education     Hybrid Journal   (Followers: 22)
Canadian Mathematical Bulletin     Hybrid Journal  
Carpathian Mathematical Publications     Open Access   (Followers: 1)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 3)
CHANCE     Hybrid Journal   (Followers: 5)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals : X     Open Access  
ChemSusChem     Hybrid Journal   (Followers: 8)
Chinese Annals of Mathematics, Series B     Hybrid Journal  
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chinese Journal of Mathematics     Open Access  
Ciencia     Open Access   (Followers: 1)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CODEE Journal     Open Access   (Followers: 3)
Cogent Mathematics     Open Access   (Followers: 2)
Cognitive Computation     Hybrid Journal   (Followers: 3)
Collectanea Mathematica     Hybrid Journal  
College Mathematics Journal     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 15)
Commentarii Mathematici Helvetici     Hybrid Journal  
Communications in Advanced Mathematical Sciences     Open Access  
Communications in Combinatorics and Optimization     Open Access  
Communications in Contemporary Mathematics     Hybrid Journal  
Communications in Mathematical Physics     Hybrid Journal   (Followers: 4)
Communications On Pure & Applied Mathematics     Hybrid Journal   (Followers: 4)
Complex Analysis and its Synergies     Open Access   (Followers: 3)
Complex Variables and Elliptic Equations: An International Journal     Hybrid Journal  
Composite Materials Series     Full-text available via subscription   (Followers: 9)
Compositio Mathematica     Full-text available via subscription  
Comptes Rendus Mathematique     Full-text available via subscription  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 4)
Computational and Mathematical Methods     Hybrid Journal  
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 9)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Optimization and Applications     Hybrid Journal   (Followers: 9)
Computers & Mathematics with Applications     Full-text available via subscription   (Followers: 11)
Concrete Operators     Open Access   (Followers: 4)
Confluentes Mathematici     Hybrid Journal  
Contributions to Discrete Mathematics     Open Access   (Followers: 2)
Contributions to Game Theory and Management     Open Access  
COSMOS     Hybrid Journal  
Cryptography and Communications     Hybrid Journal   (Followers: 13)
Cuadernos de Investigación y Formación en Educación Matemática     Open Access  
Cubo. A Mathematical Journal     Open Access  
Current Research in Biostatistics     Open Access   (Followers: 8)
Czechoslovak Mathematical Journal     Hybrid Journal   (Followers: 1)
Daya Matematis : Jurnal Inovasi Pendidikan Matematika     Open Access   (Followers: 2)
Demographic Research     Open Access   (Followers: 15)
Demonstratio Mathematica     Open Access  

        1 2 3 4 5 | Last

Similar Journals
Journal Cover
Annals of Mathematics and Artificial Intelligence
Journal Prestige (SJR): 0.413
Citation Impact (citeScore): 1
Number of Followers: 14  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-7470 - ISSN (Online) 1012-2443
Published by Springer-Verlag Homepage  [2626 journals]
  • Correction to: Log A G : An algebraic non-monotonic logic for reasoning
           with graded propositions
    • Abstract: Due to an oversight by the Publisher during the typesetting stage, an uncorrected version of the paper was published.
      PubDate: 2020-08-02
       
  • Leveraging cluster backbones for improving MAP inference in statistical
           relational models
    • Abstract: Abstract A wide range of important problems in machine learning, expert system, social network analysis, bioinformatics and information theory can be formulated as a maximum a-posteriori (MAP) inference problem on statistical relational models. While off-the-shelf inference algorithms that are based on local search and message-passing may provide adequate solutions in some situations, they frequently give poor results when faced with models that possess high-density networks. Unfortunately, these situations always occur in models of real-world applications. As such, accurate and scalable maximum a-posteriori (MAP) inference on such models often remains a key challenge. In this paper, we first introduce a novel family of extended factor graphs that are parameterized by a smoothing parameter χ ∈ [0,1]. Applying belief propagation (BP) message-passing to this family formulates a new family of W eighted S urvey P ropagation algorithms (WSP-χ) applicable to relational domains. Unlike off-the-shelf inference algorithms, WSP-χ detects the “backbone” ground atoms in a solution cluster that involve potentially optimal MAP solutions: the cluster backbone atoms are not only portions of the optimal solutions, but they also can be exploited for scaling MAP inference by iteratively fixing them to reduce the complex parts until the network is simplified into one that can be solved accurately using any conventional MAP inference method. We also propose a lazy variant of this WSP-χ family of algorithms. Our experiments on several real-world problems show the efficiency of WSP-χ and its lazy variants over existing prominent MAP inference solvers such as MaxWalkSAT, RockIt, IPP, SP-Y and WCSP.
      PubDate: 2020-08-01
       
  • On biased random walks, corrupted intervals, and learning under
           adversarial design
    • Abstract: Abstract We tackle some fundamental problems in probability theory on corrupted random processes on the integer line. We analyze when a biased random walk is expected to reach its bottommost point and when intervals of integer points can be detected under a natural model of noise. We apply these results to problems in learning thresholds and intervals under a new model for learning under adversarial design.
      PubDate: 2020-08-01
       
  • Characterization Of sampling patterns for low-tt-rank tensor retrieval
    • Abstract: Abstract In this paper, we analyze the fundamental conditions for low-rank tensor completion given the separation or tensor-train (TT) rank, i.e., ranks of TT unfoldings. We exploit the algebraic structure of the TT decomposition to obtain the deterministic necessary and sufficient conditions on the locations of the samples to ensure finite completability. Specifically, we propose an algebraic geometric analysis on the TT manifold that can incorporate the whole rank vector simultaneously in contrast to the existing approach based on the Grassmannian manifold that can only incorporate one rank component. Our proposed technique characterizes the algebraic independence of a set of polynomials defined based on the sampling pattern and the TT decomposition, which is instrumental to obtaining the deterministic condition on the sampling pattern for finite completability. In addition, based on the proposed analysis, assuming that the entries of the tensor are sampled independently with probability p, we derive a lower bound on the sampling probability p, or equivalently, the number of sampled entries that ensures finite completability with high probability. Moreover, we also provide the deterministic and probabilistic conditions for unique completability.
      PubDate: 2020-08-01
       
  • Derivation and analysis of parallel-in-time neural ordinary differential
           equations
    • Abstract: Abstract The introduction in 2015 of Residual Neural Networks (RNN) and ResNET allowed for outstanding improvements of the performance of learning algorithms for evolution problems containing a “large” number of layers. Continuous-depth RNN-like models called Neural Ordinary Differential Equations (NODE) were then introduced in 2019. The latter have a constant memory cost, and avoid the a priori specification of the number of hidden layers. In this paper, we derive and analyze a parallel (-in-parameter and time) version of the NODE, which potentially allows for a more efficient implementation than a standard/naive parallelization of NODEs with respect to the parameters only. We expect this approach to be relevant whenever we have access to a very large number of processors, or when we are dealing with high dimensional ODE systems. Moreover, when using implicit ODE solvers, solutions to linear systems with up to cubic complexity are then required for solving nonlinear systems using for instance Newton’s algorithm; as the proposed approach allows to reduce the overall number of time-steps thanks to an iterative increase of the accuracy order of the ODE system solvers, it then reduces the number of linear systems to solve, hence benefiting from a scaling effect.
      PubDate: 2020-07-25
       
  • Digitized rotations of 12 neighbors on the triangular grid
    • Abstract: Abstract There are various geometric transformations, e.g., translations, rotations, which are always bijections in the Euclidean space. Their digital counterpart, i.e., their digitized variants are defined on discrete grids, since most of our pictures are digital nowadays. Usually, these digital versions of the transformations have different properties than the original continuous variants have. Rotations are bijective on the Euclidean plane, but in many cases they are not injective and not surjective on digital grids. Since these transformations play an important role in image processing and in image manipulation, it is important to discover their properties. Neighborhood motion maps are tools to analyze digital transformations, e.g., rotations by local bijectivity point of view. In this paper we show digitized rotations of a pixel and its 12-neighbors on the triangular grid. In particular, different rotation centers are considered with respect to the corresponding main pixel, e.g. edge midpoints and corner points. Angles of all locally bijective and non-bijective rotations are described in details. It is also shown that the triangular grid shows better performance in some cases than the square grid regarding the number of lost pixels in the neighborhood motion map.
      PubDate: 2020-07-22
       
  • Mutual conditional independence and its applications to model selection in
           Markov networks
    • Abstract: Abstract The fundamental concepts underlying Markov networks are the conditional independence and the set of rules called Markov properties that translate conditional independence constraints into graphs. We introduce the concept of mutual conditional independence in an independent set of a Markov network, and we prove its equivalence to the Markov properties under certain regularity conditions. This extends the notion of similarity between separation in graph and conditional independence in probability to similarity between the mutual separation in graph and the mutual conditional independence in probability. Model selection in graphical models remains a challenging task due to the large search space. We show that mutual conditional independence property can be exploited to reduce the search space. We present a new forward model selection algorithm for graphical log-linear models using mutual conditional independence. We illustrate our algorithm with a real data set example. We show that for sparse models the size of the search space can be reduced from \(\mathcal {O} (n^{3})\) to \(\mathcal {O}(n^{2})\) using our proposed forward selection method rather than the classical forward selection method. We also envision that this property can be leveraged for model selection and inference in different types of graphical models.
      PubDate: 2020-07-21
       
  • On a hypergraph probabilistic graphical model
    • Abstract: Abstract We propose a directed acyclic hypergraph framework for a probabilistic graphical model that we call Bayesian hypergraphs. The space of directed acyclic hypergraphs is much larger than the space of chain graphs. Hence Bayesian hypergraphs can model much finer factorizations than Bayesian networks or LWF chain graphs and provide simpler and more computationally efficient procedures for factorizations and interventions. Bayesian hypergraphs also allow a modeler to represent causal patterns of interaction such as Noisy-OR graphically (without additional annotations). We introduce global, local and pairwise Markov properties of Bayesian hypergraphs and prove under which conditions they are equivalent. We also extend the causal interpretation of LWF chain graphs to Bayesian hypergraphs and provide corresponding formulas and a graphical criterion for intervention.
      PubDate: 2020-07-10
       
  • Learning under p -tampering poisoning attacks
    • Abstract: Abstract Recently, Mahloujifar and Mahmoody (Theory of Cryptography Conference’17) studied attacks against learning algorithms using a special case of Valiant’s malicious noise, called p-tampering, in which the adversary gets to change any training example with independent probability p but is limited to only choose ‘adversarial’ examples with correct labels. They obtained p-tampering attacks that increase the error probability in the so called ‘targeted’ poisoning model in which the adversary’s goal is to increase the loss of the trained hypothesis over a particular test example. At the heart of their attack was an efficient algorithm to bias the expected value of any bounded real-output function through p-tampering. In this work, we present new biasing attacks for increasing the expected value of bounded real-valued functions. Our improved biasing attacks, directly imply improved p-tampering attacks against learners in the targeted poisoning model. As a bonus, our attacks come with considerably simpler analysis. We also study the possibility of PAC learning under p-tampering attacks in the non-targeted (aka indiscriminate) setting where the adversary’s goal is to increase the risk of the generated hypothesis (for a random test example). We show that PAC learning is possible under p-tampering poisoning attacks essentially whenever it is possible in the realizable setting without the attacks. We further show that PAC learning under ‘no-mistake’ adversarial noise is not possible, if the adversary could choose the (still limited to only p fraction of) tampered examples that she substitutes with adversarially chosen ones. Our formal model for such ‘bounded-budget’ tampering attackers is inspired by the notions of adaptive corruption in cryptography.
      PubDate: 2020-07-01
       
  • The price to pay for forgoing normalization in fair division of
           indivisible goods
    • Abstract: Abstract We study the complexity of fair division of indivisible goods and consider settings where agents can have nonzero utility for the empty bundle. This is a deviation from a common normalization assumption in the literature, and we show that this inconspicuous change can lead to an increase in complexity: In particular, while an allocation maximizing social welfare by the Nash product is known to be easy to detect in the normalized setting whenever there are as many agents as there are resources, without normalization it can no longer be found in polynomial time, unless P = NP. The same statement also holds for egalitarian social welfare. Moreover, we show that it is NP-complete to decide whether there is an allocation whose Nash product social welfare is above a certain threshold if the number of resources is a multiple of the number of agents. Finally, we consider elitist social welfare and prove that the increase in expressive power by allowing negative coefficients again yields NP-completeness.
      PubDate: 2020-07-01
       
  • Statistical learning based on Markovian data maximal deviation
           inequalities and learning rates
    • Abstract: Abstract In statistical learning theory, numerous works established non-asymptotic bounds assessing the generalization capacity of empirical risk minimizers under a large variety of complexity assumptions for the class of decision rules over which optimization is performed, by means of sharp control of uniform deviation of i.i.d. averages from their expectation, while fully ignoring the possible dependence across training data in general. It is the purpose of this paper to show that similar results can be obtained when statistical learning is based on a data sequence drawn from a (Harris positive) Markov chain X, through the running example of estimation of minimum volume sets (MV-sets) related to X’s stationary distribution, an unsupervised statistical learning approach to anomaly/novelty detection. Based on novel maximal deviation inequalities we establish, using the regenerative method, learning rate bounds that depend not only on the complexity of the class of candidate sets but also on the ergodicity rate of the chain X, expressed in terms of tail conditions for the length of the regenerative cycles. In particular, this approach fully tailored to Markovian data permits to interpret the rate bound results obtained in frequentist terms, in contrast to alternative coupling techniques based on mixing conditions: the larger the expected number of cycles over a trajectory of finite length, the more accurate the MV-set estimates. Beyond the theoretical analysis, this phenomenon is supported by illustrative numerical experiments.
      PubDate: 2020-07-01
       
  • Privacy stochastic games in distributed constraint reasoning
    • Abstract: Abstract In this work, we approach the issue of privacy in distributed constraint reasoning by studying how agents compromise solution quality for preserving privacy, using utility and game theory. We propose a utilitarian definition of privacy in the context of distributed constraint reasoning, detail its different implications, and present a model and solvers, as well as their properties. We then show how important steps in a distributed constraint optimization with privacy requirements can be modeled as a planning problem, and more specifically as a stochastic game. We present experiments validating the interest of our approach, according to several criteria.
      PubDate: 2020-07-01
       
  • Energy allocation and payment: a game-theoretic approach
    • Abstract: Abstract Nowadays, energy represents the most important resource; however, we need to face several energy-related rising issues, one main concern is how energy is consumed. In particular, how we can stimulate consumers on a specific behaviour. In this work, we present a model facing energy allocation and payment. Thus, we start with the explanation of the first step of our work concerning a mechanism design approach for energy allocation among consumers. More in details, we go deep into the formal description of the energy model and users’ consumption profiles. We aim to select the optimal consumption profile for every user avoiding consumption peaks when the total required energy could exceed the energy production. The mechanism will be able to drive users in shifting energy consumptions in different hours of the day. The next step concerns a payment estimation problem which involves a community of users and an energy distributor (or producer). Our aim is to compute payments for every user in the community according to the single user’s consumption, the community’s consumption and the available energy. By computing community-dependent energy bills, our model stimulates a users’ virtuous behaviour, so that everyone approaches the production threshold as close as possible. Our payment function distributes incentives if the consumption is lower than the produced energy and penalties when the consumption exceeds the resources threshold, satisfying efficiency and fairness properties both from the community (efficiency as an economic equilibrium among sellers and buyers) and the single user (fairness as an economic measure of energy good-behaving) points of view.
      PubDate: 2020-07-01
       
  • Optimal probability aggregation based on generalized brier scoring
    • Abstract: Abstract In this paper we combine the theory of probability aggregation with results of machine learning theory concerning the optimality of predictions under expert advice. In probability aggregation theory several characterization results for linear aggregation exist. However, in linear aggregation weights are not fixed, but free parameters. We show how fixing such weights by success-based scores, a generalization of Brier scoring, allows for transferring the mentioned optimality results to the case of probability aggregation.
      PubDate: 2020-07-01
       
  • L o g A G : An algebraic Non-Monotonic logic for reasoning with graded
           propositions
    • Abstract: Abstract We present LogAG, a weighted algebraic non-monotonic logic for reasoning with graded beliefs. LogAG is algebraic in that it is a language of only terms, some of which denote propositions and may be associated with ordered grades. The grades could be taken to represent a wide variety of phenomena including preference degrees, priority levels, trust ranks, and uncertainty measures. Reasoning in LogAG is non-monotonic and may give rise to contradictions. Belief revision is, hence, an integral part of reasoning and is guided by the grades. This yields a quite expressive language providing an interesting alternative to the currently existing approaches to non-monotonicity. We show how LogAG can be utilised for modelling resource-bounded reasoning; simulating inconclusive reasoning with circular, liar-like sentences; and reasoning about information arriving over a chain of sources each with a different degree of trust. While there certainly are accounts in the literature for each of these issues, we are not aware of any single framework that accounts for them all like LogAG does. We also show how LogAG captures a wide variety of non-monotonic logical formalisms. As such, LogAG is a unifying framework for non-monotonicity which is flexible enough to admit a wide array of potential uses.
      PubDate: 2020-06-20
       
  • Festschrift in honor of Oliviero Stock—— Preface
    • PubDate: 2020-06-01
       
  • Dual embeddings and metrics for word and relational similarity
    • Abstract: Abstract Word embedding models excel in measuring word similarity and completing analogies. Word embeddings based on different notions of context trade off strengths in one area for weaknesses in another. Linear bag-of-words contexts, such as in word2vec, can capture topical similarity better, while dependency-based word embeddings better encode functional similarity. By combining these two word embeddings using different metrics, we show how the best aspects of both approaches can be captured. We show state-of-the-art performance on standard word and relational similarity benchmarks.
      PubDate: 2020-06-01
       
  • Non-terminating processes in the situation calculus
    • Abstract: Abstract By their very design, many robot control programs are non-terminating. This paper describes a situation calculus approach to expressing and proving properties of non-terminating programs expressed in Golog, a high level logic programming language for modeling and implementing dynamical systems. Because in this approach actions and programs are represented in classical (second-order) logic, it is natural to express and prove properties of Golog programs, including non-terminating ones, in the very same logic. This approach to program proofs has the advantage of logical uniformity and the availability of classical proof theory.
      PubDate: 2020-06-01
       
  • “All the world’s a stage”: incongruity humour revisited
    • Abstract: Abstract Eighteenth and nineteenth century philosophers took interest in humour and, in particular, humorous incongruities. Humour was not necessarily their main interest; however, observations on humour could support their more general philosophical theories. Spontaneous and unintentional humour such as anecdotes, witty remarks and absurd events were the styles of humour that they analysed and made part of their theories. Prepared humour such as verbal jokes were rarely included in their observations, likely dismissed as too vulgar and not requiring intellectual effort. Humour, as analysed by several eighteenth and nineteenth century philosophers, was seen as part of daily life or life simulated on stage. In the twentieth century, Freud emphasized a possible ‘relief’ function of ‘prepared’ humour such as jokes. Additionally, linguists began developing theories to analyse jokes. A joke has a particular structure that is constructed with the aim of achieving a humorous effect. This structure makes jokes suitable for linguistic analysis. In the present-day humour research, jokes have become a main topic of research. This linguistically oriented joke research neglects many other forms of humour: spontaneous humour, non-verbal humour, physical humour, and many forms of unintentional humour that appear in real life. We want to survey and re-evaluate the contributions to the humour research of these eighteenth, nineteenth and early twentieth century philosophers and clarify that their more general contributions to the humour research have been neglected in favour of the very restricted form of prepared humour and linguistically expressed and analysed humour as it appears in jokes. We hope that the views expressed in this paper will help to steer the humour research away from joke research and help to integrate humour in the design of human-computer interfaces and smart environments. That is, rather than considering only verbal jokes, we should aim at generating smart environments that understand, facilitate or create humour that goes beyond jokes.
      PubDate: 2020-06-01
       
  • Foreword to special issue for ISAIM 2018
    • PubDate: 2020-05-12
       
 
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