pinecone/core-2020-05-10-deduplication huggingface dataset:
Concentration and confidence for discrete Bayesian sequence predictors

Bayesian sequence prediction is a simple technique for predicting future symbols sampled from an unknown measure on infinite sequences over a countable alphabet. While strong bounds on the expected cumulative error are known, there are only limited results on the distribution of this error. We prove tight high-probability bounds on the cumulative error, which is measured in terms of the Kullback-Leibler (KL) divergence. We also consider the problem of constructing upper confidence bounds on the KL and Hellinger errors similar to those constructed from Hoeffding-like bounds in the i.i.d. case. The new results are applied to show that Bayesian sequence prediction can be used in the Knows What It Knows (KWIK) framework with bounds that match the state-of-the-art
Reasoning about actions meets strategic logics

We introduce ATLEA, a novel extension of Alternating-time Temporal Logic with explicit actions in the object language. ATLEA allows to reason about abilities of agents under commitments to play certain actions. Pre- and postconditions as well as availability and unavailability of actions can be expressed. We show that the multiagent extension of Reiter’s solution to the frame problem can be encoded into ATLEA. We also consider an epistemic extension of ATLEA. We demonstrate that the resulting logic is sufficiently expressive to reason about uniform choices of actions. Complexity results for the satisfiability problem of ATLEA and its epistemic extension are given in the paper
Listen to me! Public announcements to agents that pay attention - or not

In public announcement logic it is assumed that all agents pay attention (listen to/observe) to the announcement. Weaker observational conditions can be modelled in event (action) model logic. In this work, we propose a version of public announcement logic wherein it is encoded in the states of the epistemic model which agents pay attention to the announcement. This logic is called attention-based announcement logic, abbreviated ABAL. We give an axiomatization and prove that complexity of satisfiability is the same as that of public announcement logic, and therefore lower than that of action model logic [2]. We exploit our logic to formalize the concept of joint attention that has been widely discussed in the philosophical and cognitive science literature. Finally, we extend our logic by integrating attention change
QoCIM : A Meta-model for Quality of Context

In the last decade, several works proposed their own list of quality of context (QoC) criteria. This article relates a comparative study of these successive propositions. The result is that no consensus has been reached about the semantic and the comprehensiveness of QoC criteria. Facing this situation, the QoCIM meta-model offers a generic, computable and expressive solution to handle and to exploit any QoC criterion within distributed context managers and context-aware applications. For validation purposes, QoCIM is successfully applied to the modelling of a set of simple and composite QoC criteria
Detecting bicliques in GF[q]

We consider the problem of finding planted bicliques in random matrices over $\GF[q]$. That is, our input matrix is a $\GF[q]$-sum of an unknown biclique (rank-1 matrix) and a random matrix. We study different models for the random graphs and characterize the conditions when the planted biclique can be recovered. We also empirically show that a simple heuristic can reliably recover the planted bicliques when our theory predicts that they are recoverable. 


Existing methods can detect bicliques of $O(\sqrt{N})$, while it is \NP-hard to find the largest such clique. Real graphs, however, are typically extremely sparse and seldom contain such large bicliques. Further, the noise can destroy parts of the planted biclique. We investigate the practical problem of how small a biclique can be and how much noise there can be such that we can still approximately correctly identify the biclique. Our derivations show that with high probability planted bicliques of size logarithmic in the network size can be detected in data following the Erd\H{o}s-R\'{e}nyi model and two bipartite variants of the Barab\'{a}si-Albert model.status: publishe
Efficient frequent connected induced subgraph mining in graphs of bounded treewidth

Abstract. We study frequent connected induced subgraph mining, i.e.,
the problem of listing all connected graphs that are induced subgraph
isomorphic to at least a certain number of transaction graphs. We first
show that this problem cannot be solved for arbitrary transaction graphs
in output polynomial time (if P = NP) and then prove that for graphs
of bounded tree-width, frequent connected induced subgraph mining is
possible in incremental polynomial time by levelwise search. Our algo-
rithm is an adaptation of the technique developed for frequent connected
subgraph mining in bounded tree-width graphs. While the adaptation
is relatively natural for many steps of the original algorithm, we need
entirely different combinatorial arguments to show the correctness and
efficiency of the new algorithm. Since induced subgraph isomorphism
between bounded tree-width graphs is NP-complete, the positive result
of this paper provides another example of efficient pattern mining with
respect to computationally intractable pattern matching operators.status: publishe
SCCQL: A constraint-based clustering system

demo presentationThis paper presents the rst version of a new inductive database system called SCCQL. The system performs constraint-based clustering on a relational database. Clustering problems are formulated with a query language, an extension of SQL for clustering that includes must-link and cannot-link constraints. The functioning of the system is explained. As an example of use of this system, an application in the context of microbioloy has been developed that is presented here.status: publishe
Discovering skylines of subgroup sets

Many tasks in exploratory data mining aim to discover the
top-k results with respect to a certain interestingness measure. Unfortunately, in practice top-k solution sets are hardly satisfactory, if only because redundancy in such results is a severe problem. To address this, a recent trend is to nd diverse sets of high-quality patterns. However, a `perfect' diverse top-k cannot possibly exist, since there is an inherent trade-o between quality and diversity.

We argue that the best way to deal with the quality-diversity trade-off is to explicitly consider the Pareto front, or skyline, of non-dominated solutions, i.e. those solutions for which neither quality nor diversity can
be improved without degrading the other quantity. In particular, we focus on k-pattern set mining in the context of Subgroup Discovery [6]. For this setting, we present two algorithms for the discovery of skylines; an exact algorithm and a levelwise heuristic.

We evaluate the performance of the two proposed skyline algorithms, and the accuracy of the levelwise method. Furthermore, we show that the skylines can be used for the objective evaluation of subgroup set heuristics. Finally, we show characteristics of the obtained skylines, which reveal
that dierent quality-diversity trade-os result in clearly dierent subgroup sets. Hence, the discovery of skylines is an important step towards a better understanding of `diverse top-k's'.status: publishe
Evasion Attacks against Machine Learning at Test Time

In security-sensitive applications, the success of machine learning depends
on a thorough vetting of their resistance to adversarial data. In one
pertinent, well-motivated attack scenario, an adversary may attempt to evade a
deployed system at test time by carefully manipulating attack samples. In this
work, we present a simple but effective gradient-based approach that can be
exploited to systematically assess the security of several, widely-used
classification algorithms against evasion attacks. Following a recently
proposed framework for security evaluation, we simulate attack scenarios that
exhibit different risk levels for the classifier by increasing the attacker's
knowledge of the system and her ability to manipulate attack samples. This
gives the classifier designer a better picture of the classifier performance
under evasion attacks, and allows him to perform a more informed model
selection (or parameter setting). We evaluate our approach on the relevant
security task of malware detection in PDF files, and show that such systems can
be easily evaded. We also sketch some countermeasures suggested by our
analysis.Comment: In this paper, in 2013, we were the first to introduce the notion of
  evasion attacks (adversarial examples) created with high confidence (instead
  of minimum-distance misclassifications), and the notion of surrogate learners
  (substitute models). These two concepts are now widely re-used in developing
  attacks against deep networks (even if not always referring to the ideas
  reported in this work). arXiv admin note: text overlap with arXiv:1401.772
Collaborative Schema Matching Reconciliation

Schema matching is the process of establishing correspondences between the attributes of database schemas for data integration purpose. Although several schema matching tools have been developed, their results are often incomplete or erroneous. To obtain correct attribute correspondences, in practice, human experts edit the mapping results and fix the mapping problems. As the scale and complexity of data integration tasks have increased dramatically in recent years, the reconciliation phase becomes more and more a bottleneck. Moreover, one often needs to establish the correspondences in not only between two but a network of schemas simultaneously. In such reconciliation settings, it is desirable to involve several experts. In this paper, we propose a tool that supports a group of experts to collaboratively reconcile a set of matched correspondences. The experts might have conflicting views whether a given correspondence is correct or not. As one expects global consistency conditions in the network, the conflict resolution might require discussion and negotiation among the experts to resolve such disagreements. We have developed techniques and a tool that allow approaching this reconciliation phase in a systematic way. We represent the expert’s views as arguments to enable formal reasoning on the assertions of the experts. We detect complex dependencies in their arguments, guide and present them the possible consequences of their decisions. These techniques thus can greatly help them to overlook the complex cases and work more effectively.Full Tex
Completeness and Ambiguity of Schema Cover

Given a schema and a set of concepts, representative of entities in the domain of discourse, schema cover defines correspondences between concepts and parts of the schema. Schema cover aims at interpreting the schema in terms of concepts and thus, vastly simplifying the task of schema integration. In this work we investigate two properties of schema cover, namely completeness and ambiguity. The former measures the part of a schema that can be covered by a set of concepts and the latter examines the amount of overlap between concepts in a cover. To study the tradeoffs between completeness and ambiguity we define a cover model to which previous frameworks are special cases. We analyze the theoretical complexity of variations of the cover problem, some aim at maximizing completeness while others aim at minimizing ambiguity. We show that variants of the schema cover problem are hard problems in general and formulate an exhaustive search solution using integer linear programming. We then provide a thorough empirical analysis, using both real-world and simulated data sets, showing empirically that the integer linear programming solution scales well for large schemata. We also show that some instantiations of the general schema cover problem are more effective than others.Full Tex
Dynamic weaving in aspect oriented business process management

Reducing complexity in Information Systems is an important topic in both research and industry. One strategy to deal with complexity is separation of concerns, which results in less complex, easily maintainable and more reusable systems. Separation of concerns can be addressed through the Aspect Oriented paradigm. Although this paradigm has been well researched in programming, it is still at the preliminary stage in the area of Business Process Management. While some efforts have been made to extend business process modelling with aspect oriented capability, it has not yet been investigated how aspect oriented business process models should be executed at runtime. In this paper, we propose a generic solution to support execution of aspect oriented business process models based on the principle behind dynamic weaving of aspects. This solution is formally specified using Coloured Petri Nets. The resulting formal specification serves as the blueprint to the implementation of a service module in the framework of a state-of-the-art Business Process Management System. Using this developed artefact, a case study is performed in which two simplified processes from real business in the domain of banking are modelled and executed in an aspect oriented manner. Through this case study, we also demonstrate that adoption of aspect oriented modularization increases the reusability while reducing the complexity of business process models in practice
Federated authorization for Software-as-a-Service applications

Software-as-a-Service (SaaS) is a type of cloud computing in which a tenant rents access to a shared, typically web-based application hosted by a provider. Access control for SaaS should enable the tenant to control access to data that are located at the provider based on tenant-specific access control policies. To achieve this, state-of-practice SaaS applications provide application-specific access control configuration interfaces and as a result, the tenant policies are evaluated at the provider side. This approach does not support collaboration between provider-side and tenant-side access control infrastructures, thus scattering tenant access control management and forcing the tenant to disclose sensitive access control data. To address these issues, we describe the concept of federated authorization in which management and evaluation of the tenant policies is externalized from the SaaS application to the tenant. This centralizes tenant access control management and lowers the required trust in the provider. This paper presents a generic middleware architecture for federated authorization, describing required extensions to current policy languages and a distributed execution environment. Our evaluation explores the trade-off between performance and security and shows that federated authorization is a feasible and promising approach.status: publishe
Machine-Readable Privacy Certificates for Services

Privacy-aware processing of personal data on the web of services requires
managing a number of issues arising both from the technical and the legal
domain. Several approaches have been proposed to matching privacy requirements
(on the clients side) and privacy guarantees (on the service provider side).
Still, the assurance of effective data protection (when possible) relies on
substantial human effort and exposes organizations to significant
(non-)compliance risks. In this paper we put forward the idea that a privacy
certification scheme producing and managing machine-readable artifacts in the
form of privacy certificates can play an important role towards the solution of
this problem. Digital privacy certificates represent the reasons why a privacy
property holds for a service and describe the privacy measures supporting it.
Also, privacy certificates can be used to automatically select services whose
certificates match the client policies (privacy requirements).
  Our proposal relies on an evolution of the conceptual model developed in the
Assert4Soa project and on a certificate format specifically tailored to
represent privacy properties. To validate our approach, we present a worked-out
instance showing how privacy property Retention-based unlinkability can be
certified for a banking financial service.Comment: 20 pages, 6 figure
Modelling a Sustainable Cooperative Healthcare:   An Interoperability-Driven Approach

Modern healthcare is confronted with serious issues that are threatening its viability and sustainability. Increasing costs and complexity, global population ageing and pandemics are major culprits of the healthcare quandary. In this context, effective interoperability of the participants in the healthcare effort becomes paramount. However, this is also a major challenge as unfortunately, healthcare institutions typically feature strong hierarchy and heterogeneity. As the pressure on healthcare resources and management cost is constantly increasing, governments can no longer rely on outdated 'silo' paradigms for managing population wellbeing. New cooperative and integrated models and procedures taking into account all essential cooperation aspects, elements, participants and their life cycle are necessary to drive cooperative healthcare sustainability. Based on previous research and applications, this paper argues that the necessary artefacts can be built using a life cycle-based, holistic paradigm enabled by advances in Interoperability, Enterprise Architecture and Collaborative Networks research and practice. The proposed modelling approach aims to provide a solid base for sustainable solutions to long and short-term challenges to population health and well-being.Full Tex
Sustainability and Interoperability: Two Facets of the Same Gold Medal

'To sustain is to endure' - that is, to be able to survive and continue to  function in the face of significant changes. The commonly accepted concept of  'sustainability' currently encompasses three main pillars: environmental,  social/ethical and economic. In a metaphor of survival, they can be seen as  water, food and air; one needs all three, only with varying degrees of urgency.  In today's globally networked environment, it is becoming obvious that one  cannot achieve environmental, social or economic sustainability of any artefact  (be it physical or virtual, e.g. enterprise, project, information system, policy,  etc) without achieving ubiquitous ability of the artefact and its creators and  users to exchange and understand shared information and if necessary perform  processes on behalf of each other - capabilities that are usually defined as  'interoperability'. Thus, sustainability relies on interoperability, while,  conversely, interoperability as an ongoing concern relies for its existence on all  three main pillars of sustainability. This paper aims to test the hypothesis that  interoperability and sustainability are two inseparable and inherently linked  aspects of any universe of discourse. To achieve this, it applies the dualistic  sustainability / interoperability viewpoint to a variety of areas (manufacturing,  healthcare, information and communication technology and standardisation),  analyses the results and synthesizes conclusions and guidelines for future work.Full Tex
Robustness in Timed Automata

In this paper we survey several approaches to the robustness of timed automata, that is, the ability of a system to resist to slight perturbations or errors. We will concentrate on robustness against timing errors which can be due to measuring errors, imprecise clocks, and unexpected runtime behaviors such as execution times that are longer or shorter than expected.
We consider the perturbation model of guard enlargement and formulate several robust verification problems that have been studied recently, including robustness analysis, robust implementation, and robust control
Reachability problems for hierarchical piecewise constant derivative systems

The final publication is available at link.springer.com.In this paper, we investigate the computability and complexity of reachability problems for two-dimensional hierarchical piecewise constant derivative (HPCD) systems. The main interest in HPCDs stems from the fact that their reachability problem is on the border between decidability and undecidability, since it is equivalent to that of reachability for one-dimensional piecewise affine maps (PAMs) which is a long standing open problem. Understanding the most expressive hybrid system models that retain decidability for reachability has generated a great deal of interest over the past few years. In this paper, we show a restriction of HPCDs (called RHPCDs) which leads to the reachability problem becoming decidable. We then study which additional powers we must add to the RHPCD model to render it 1D PAM-equivalent. Finally, we show NP-hardness of reachability for nondeterministic RHPCDs
Using ‘search transitions’ to study searchers investment of effort: experiences with client and server side logging

We are investigating the value of using the concept ‘search transition’ for studying effort invested in information search processes. In this paper we present findings from a comparative study of data collected from client and server side loggings. The purpose is to see what factors of effort can be captured from the two logging methods. The data stems from studies of searchers interaction with an XML information retrieval system. The searchers interaction was simultaneously logged by a screen capturing software and the IR systems logging facility. In order to identify the advantages and disadvantages we have compared the data gathered from a selection of sessions. We believe there is value in identifying the effort investment in a search process, both to evaluate the quality of the search system and to suggest areas of system intervention in the search process, if effort investment can be detected dynamicall
An exploratory study on content-based filtering of call for papers

Due to the increasing number of conferences, researchers need to spend more and more time browsing through the respective calls for papers (CFPs) to identify those conferences which might be of interest to them. In this paper we study several content-based techniques to filter CFPs retrieved from the web. To this end, we explore how to exploit the information available in a typical CFP: a short introductory text, topics in the scope of the conference, and the names of the people in  the program committee. While the introductory text and the topics can be directly used to model the document (e.g. to derive a tf-idf weighted vector), the names of the members of the program committee can be used in several indirect ways. One strategy we pursue in particular is to take into account the papers that these people have recently written. Along similar lines, to find out the research interests of the users, and thus  to decide which CFPs to select, we look at the abstracts of the papers that they have recently written. We compare and contrast a number of approaches based on the vector space model and on generative language models