pinecone/core-2020-05-10-deduplication huggingface dataset:
Stochastic text models for music categorization

Music genre meta-data is of paramount importance for the organization of music repositories. People use genre in a natural way when entering a music store or looking into music collections. Automatic genre classification has become a popular topic in music information retrieval research. This work brings to symbolic music recognition some technologies, like the stochastic language models, already successfully applied to text categorization. In this work we model chord progressions and melodies as n-grams and strings and then apply perplexity and naïve Bayes classifiers, respectively, in order to assess how often those structures are found in the target genres. Also a combination of the different techniques as an ensemble of classifiers is proposed. Some genres and sub-genres among popular, jazz, and academic music have been considered. The results show that the ensemble is a good trade-off approach
able to perform well without the risk of choosing the wrong classifier.This work is supported by the Spanish PROSEMUS
project (TIN2006-14932-C02), the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018) and the Pascal Network of Excellence
Melody recognition with learned edit distances

In a music recognition task, the classification of a new melody is often achieved by looking for the closest piece in a set of already known prototypes. The definition of a relevant similarity measure becomes then a crucial point. So far, the edit distance approach with a-priori fixed operation costs has been one of the most used to accomplish the task. In this paper, the application of a probabilistic learning model to both string and tree edit distances is proposed and is compared to a genetic algorithm cost fitting approach. The results show that both learning models outperform
fixed-costs systems, and that the probabilistic approach is able to describe consistently the underlying melodic similarity model.This work was funded by the French ANR Marmota project, the Spanish PROSEMUS project (TIN2006-14932-C02), the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018), and the Pascal Network of Excellence
An island based hybrid evolutionary algorithm for optimization

This is a post-print version of the article - Copyright @ 2008 Springer-VerlagEvolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary techniques have been developed, especially hybrid evolutionary algorithms. This paper proposes an island based hybrid evolutionary algorithm (IHEA) for optimization, which is based on Particle swarm optimization (PSO), Fast Evolutionary Programming (FEP), and Estimation of Distribution Algorithm (EDA). Within IHEA, an island model is designed to cooperatively search for the global optima in search space. By combining the strengths of the three component algorithms, IHEA greatly improves the optimization performance of the three basic algorithms. Experimental results demonstrate that IHEA outperforms all the three component algorithms on the test problems.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
A generalized approach to construct benchmark problems for dynamic optimization

Copyright @ Springer-Verlag Berlin Heidelberg 2008.There has been a growing interest in studying evolutionary algorithms in dynamic environments in recent years due to its importance in real applications. However, different dynamic test problems have been used to test and compare the performance of algorithms. This paper proposes a generalized dynamic benchmark generator (GDBG) that can be instantiated into the binary space, real space and combinatorial space. This generator can present a set of different properties to test algorithms by tuning some control parameters. Some experiments are carried out on the real space to study the performance of the generator.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1
Reinforcement learning with the use of costly features

In many practical reinforcement learning problems, the state space is too large to permit an exact representation of the value function, much less the time required to compute it.  In such cases, a common solution approach is to compute an approximation of the value function in terms of state features.  However, relatively little attention has been paid to the cost of computing these state features.  For example, search-based features may be useful for value prediction, but their computational cost must be traded off with their impact on value accuracy.  To this end, we introduce a new cost-sensitive sparse linear regression paradigm for value function approximation in reinforcement learning where the learner is able to select only those
costly features that are sufficiently informative to justify their computation.  We illustrate the learning behavior of our approach using a simple experimental domain that allows us to explore the effects of a range of costs on the cost-performance trade-off.status: publishe
Probabilistic Inference for Fast Learning in Control

22.10.13 KB. Ok to add author version to spiralWe provide a novel framework for very fast model-based reinforcement learning in continuous state and action spaces. The framework requires probabilistic models that explicitly characterize their levels of confidence. Within this framework, we use flexible, non-parametric models to describe the world based on previously collected experience. We demonstrate learning on the cart-pole problem in a setting where we provide very limited prior knowledge about the task. Learning progresses rapidly, and a good policy is found after only a hand-full of iterations
USE OF CFD FOR THERMAL COUPLING IN AEROENGINE INTERNAL AIR SYSTEMS APPLICATIONS

With the rapid progress of computational fluid dynamics (CFD) and computer technology, CFD has been increasingly used for aero-engine component temperature predictions. This paper presents a review of the latest progress in this aspect with emphasis on internal air system applications. The thermal coupling methods discussed include the traditional finite element analysis (FEA), the conjugate heat transfer, FEA/CFD coupling procedure and other thermal coupling techniques. Special attention is made to identify the merits and disadvantages between the various methodologies. Discussion is further extended on the steady and transient thermal coupling applications
Floating Fault Analysis of Trivium

One of the eSTREAM final portfolio ciphers is the hardwareoriented
stream cipher Trivium. It is based on 3 nonlinear feedback shift
registers with a linear output function. Although Trivium has attached
a lot of interest, it remains unbroken by passive attacks.
At FSE 2008 a differential fault analysis of Trivium was presented. It is
based on the fact that one-bit fault induction reveals many polynomial
equations among which a few are linear and a few quadratic in the inner
state bits. The attack needs roughly 43 induced one-bit random faults
and uses only linear and quadratic equations.
In this paper we present an improvement of this attack. It requires only
3.2 one-bit fault injections in average to recover the Trivium inner state
(and consequently its key) while in the best case it succeeds after 2
fault injections. We termed this attack floating fault analysis since it
exploits the floating model of the cipher. The use of this model leads to
the transformation of many obtained high-degree equations into linear
equations.
The presented work shows how a change of the cipher representation
may result in much better attack
An approach to description logic with support for propositional attitudes and belief fusion

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-89765-1_8Revised Selected and Invited Papers of ISWC International Workshops, URSW 2005-2007.In the (Semantic) Web, the existence or producibility of certain, consensually agreed or authoritative knowledge cannot be assumed, and criteria to judge the trustability and reputation of knowledge sources may not be given. These issues give rise to formalizations of web information which factor in heterogeneous and possibly inconsistent assertions
and intentions, and make such heterogeneity explicit and manageable for reasoning mechanisms. Such approaches can provide valuable metaknowledge in contemporary application fields, like open or distributed ontologies, social software, ranking and recommender systems, and domains with a high amount of controversies, such as politics and culture. As an approach to this, we introduce a lean formalism for the Semantic
Web which allows for the explicit representation of controversial individual and group opinions and goals by means of so-called social contexts, and optionally for the probabilistic belief merging of uncertain or conflicting statements. Doing so, our approach generalizes concepts such as provenance annotation and voting in the context of ontologies and other kinds of Semantic Web knowledgeThis work was partially funded by the German National Research Foundation DFG (Br609/13-1, research project “Open Ontologies and Open Knowledge Bases”) and by the Spanish National Plan of R+D, project no. TSI2005-08225-C07-0
Enabling resource sharing between transactional and batch workloads using dynamic application placement

We present a technique that enables existing middleware to fairly manage mixed workloads: batch jobs and transactional applications. The technique leverages a generic application placement controller, which dynamically allocates compute resources to application instances. The controller works towards a fairness goal while also trying to maximize individual workload performance.\ud
We use relative performance functions to drive the application placement controller.\ud
Such functions are derived from workload-specific performance models in the case of transactional workloads, we use queuing theory to build the performance model. For batch workloads, we evaluate a candidate placement by calculating long-term estimates of the completion times that are achievable with that placement according to a scheduling policy. In this paper, we propose a lowest relative performancwe first scheduling policy as a way to also achieve fair resource allocation among batch jobs. Our technique permits collocation of the workload types on the same physical hardware, and leverages control mechanisms such as suspension and migration to perform online system reconfiguration. In our experiments we demonstrate that our technique maximizes mixed workload performance while providing service differentiation based on high-level performance goals.Peer ReviewedPreprin
Rules and Apriori Algorithm in Non-deterministic Information Systems

This paper presents a framework of rule generation in Non-deterministic Information Systems (NISs), which follows rough sets based rule generation in Deterministic Information Systems (DISs). Our previous work about NISs coped with certain rules, minimal certain rules and possible rules. These rules are characterized by the concept of consistency. This paper relates possible rules to rules by the criteria support and accuracy in NISs. On the basis of the information incompleteness in NISs, it is possible to define new criteria, i.e., minimum support, maximum support, minimum accuracy and maximum accuracy. Then, two strategies of rule generation are proposed based on these criteria. The first strategy is Lower Approximation strategy, which defines rule generation under the worst condition. The second strategy is Upper Approximation strategy, which defines rule generation under the best condition. To implement these strategies, we extend Apriori algorithm in DISs to Apriori algorithm in NISs. A prototype system is implemented, and this system is applied to some data sets with incomplete information
The inContext Pervasive Collaboration Services Architecture

This is the author's final draft of the paper published as Lecture Notes in Computer Science, 2008, 5377, pp. 134-146.  The final version is available from http://www.springerlink.com/content/h3733v757423278m/.  Doi: 10.1007/978-3-540-89897-9_12Traditional collaborative work environments are often proprietary systems. However, the demands of todays e-worker are such\ud
that they use their own tools and services and collaborate across company boundaries making highly integrated solutions less feasible. Service oriented computing provides an obvious solution here, in providing mechanisms to loosely integrate many tools and services. In this paper,\ud
we present the inContext PCSA (Pervasive Collaboration Services Architecture), which is a reference architecture for building context aware collaborative systems that are based on service oriented techniques
Intelligence and Security Informatics

The book constitutes the proceedings of the First European Conference on Intelligence and Security Informatics, EuroISI 2008

Intelligence and security informatics (ISI) is a multidisciplinary field encompassing methodologies, models, algorithms, and advanced tools for intelligence analysis, homeland security, terrorism research as well as security-related public policies. These proceedings contain 25 original papers, out of 48 submissions received, related to the topics of intelligence and security informatics. These papers cover a broad range of fields such as: social network analysis, knowledge discovery, web-based intelligence and analysis, privacy protection, access control, digital rights management, malware and intrusion detection, surveillance, crisis management, and computational intelligence, among others.JRC.G.2-Support to external securit
Rough web caching\ud
\ud

The demand for Internet content rose dramatically in recent years. Servers became more and more powerful and the bandwidth of end user connections and backbones grew constantly during the last decade. Nevertheless users often experience poor performance when they access web sites or download files. Reasons for such problems are often performance problems, which occur directly on the servers (e.g. poor performance of server-side applications or during flash crowds) and problems concerning the network infrastructure (e.g. long geographical distances, network overloads, etc.). Web caching and prefetching have been recognized as the effective schemes to alleviate the service bottleneck and to minimize the user access latency and reduce the network traffic. In this chapter, we model the uncertainty in Web caching using the granularity of rough set (RS) and inductive learning. The proposed framework is illustrated using the trace-based experiments from Boston University Web trace data set
Automatic composition of melodic and harmonic music by answer set programming

The composition of most styles of music is governed by rules. The natural statement of these rules is declarative (``The highest and lowest notes in a piece must be separated by a consonant interval'') and non deterministic (``The base note of a key can be followed by any note in the key''). We show that by approaching the automation and analysis of composition as a knowledge representation task and formalising these rules in a suitable logical language, powerful and expressive intelligent composition tools can easily be built. This paper describes the use of answer set programming to construct an automated system that can compose both melodic and harmonic music, diagnose errors in human compositions and serve as a computer-aided composition tool. The use of a fully declarative language and an ``off-the-shelf'' reasoning engine allows the creation of tools which are significantly simpler, smaller and more flexible than those produced by existing approaches. It also combines harmonic and melodic composition in a single framework, which is a new feature in the growing area of algorithmic composition
Building a knowledge base system for an integration of logic programming and classical logic

This paper presents a Knowledge Base project for FO(ID), an extension of classical logic with inductive deﬁnitions. This logic is a natural integration of classical logic and logic programming based on the view of a logic program as a deﬁnition. We discuss the relationship between inductive deﬁnitions and common sense reasoning and the strong similarities and striking differences with ASP and Abductive LP. We report on inference systems that combine state-of-the-art techniques of SAT and ASP. Experiments show that FO(ID) model expansion systems are competitive with the best ASP-solvers.status: publishe
Uniting the Prolog community

Abstract of session at the 24th International Conference on Logic Programming (ICLP 2008).In his article A Wake-Up Cal l for the Logic Programming Community, published in the December 2007 issue of the ALP Newsletter, the ﬁrst author raised concerns about the viability of the Prolog programming language in the near 
future. The article had a pessimistic undertone, but expressed the hope that the current evolution can be reversed by uniting the Prolog community. Now, 
almost a year later, it is time for more optimistic news and we are happy that the ALP —through the ICLP 2008 program chairs— has given us the opportunity to 
re-iterate the arguments, present the recent positive developments and involve the whole community.status: publishe
On the efficient execution of ProbLog programs

acceptance rate = 31,6%The past few years have seen a surge of interest in the field of
  probabilistic logic learning or statistical relational learning.  In
  this endeavor, many probabilistic logics have been
  developed. ProbLog is a recent probabilistic extension of Prolog
  motivated by the mining of large biological networks. In ProbLog,
  facts can be labeled with mutually independent probabilities that
  they belong to a randomly sampled program.

  Different kinds of queries can be posed to ProbLog programs. We
  introduce algorithms that allow the efficient execution
  of these queries, discuss their implementation on top of the YAP-Prolog system,  and evaluate their performance in the context of large networks of biological entities.status: publishe
A folding algorithm for eliminating existential variables from constraint logic programs

The existential variables of a clause in a constraint logic program are the variables which occur in the body of the clause and not in its head. The elimination of these variables is a transformation technique which is often used for improving program efficiency and verifying program properties. We, consider a folding transformation rifle which ensures the elimination of existential variables and we propose an algorithm for applying this rule in the case where the constraints are linear inequations over rational or real numbers. The algorithm combines techniques for matching, terms modulo equational theories and for solving systems of linear inequations. We show that an implementation of our folding algorithm performs well in practice
Optimization of CHR propagation rules

full paper acceptance rate = 31.6%Constraint Handling Rules (CHR) is an elegant, high-level programming language based on multi-headed, forward chaining rules. To ensure CHR propagation rules are applied at most once with the same combination of constraints, CHR implementations maintain a so-called propagation history. The performance impact of this history can be significant. We introduce several optimizations that, for the majority of CHR rules, eliminate this overhead. We formally prove their correctness, and evaluate their implementation in two state-of-the-art CHR systems.status: publishe
Termination analysis of CHR revisited

Today, two distinct direct approaches to prove termination of CHR programs exist. The first approach, by T. Fr\"uhwirth, proves termination of CHR programs without propagation. The second, by Voets et al., deals with programs that contain propagation. It is however less powerful on programs without propagation. In this paper, we present new termination conditions that are strictly more powerful than those from previous approaches and that are also applicable to a new class of programs. Furthermore, we present a new representation for CHR states for which size-decreases between consecutive states correspond to termination. Both contributions are linked: our termination conditions correspond to the existence of a well-founded order on the new state representation, which decreases for consecutive computation states.status: publishe
Transactions in Constraint Handling Rules

CHR is a highly concurrent language, and yet it is by no 
means a trivial task to write correct concurrent CHR programs. We propose a new semantics for CHR, which allows specifying and reasoning about transactions. Transactions alleviate the complexity of writing concurrent programs by oﬀering entire derivations to run atomically and in 
isolation. 
We derive several program transformations based on our semantics that transform particular classes of transitional CHR programs to non-transactional ones. These transformations are useful because they obviate a 
general purpose transaction manager, and may lift unnecessary sequentialization present in the transactional semantics.status: publishe
Cadmium: An implementation of ACD term rewriting

Cadmium is a rule based programming language for compiling solver independent constraint models to various solver dependent back-ends. Cadmium is based on a hybrid between
Constraint Handling Rules (CHR) and term rewriting modulo Associativity, Commutativity and a restricted form of Distributivity (ACD) called Conjunctive Context (CC).
Experience with using Cadmium in the G12 project shows that CC is a powerful language feature, as local model mapping can depend on some non-local context, such as variable declarations or other constraints. However, CC significantly complicates the Cadmium normalisation algorithm, since the normal form of a term may depend on what context it appears in. In this paper we present an implementation of Cadmium based on classic bottom-up evaluation, but modified to handle CC matching. We evaluate the performance of the new implementation compared to earlier prototype normalisation algorithms. We show that the resulting system is fast enough to run "real-world" Cadmium applications.status: publishe
Two WAM implementations of   action rules

Two implementations of Action Rules are presented in the context of a
WAM-like Prolog system: one follows a meta-call based approach, the
other uses suspended WAM environments on the WAM heap. Both are based
on a similar program transformation that clarifies the semantics of
Action Rules, while using different primitives. Their implementation
is compared experimentally to the TOAM-based implementation of Action
Rules in B-Prolog. The suspension based approach is faster at
reactivating agents on the instantiation event. The meta-call
approach is easier to implement, performs overall very good and much
better for synchronous events, and it is more flexible than the
suspension based approaches.status: publishe
Towards typed Prolog

Prolog is traditionally not statically typed. Since the benefits of static typing are huge, it was decided to grow a portable type system inside two widely used open source Prolog systems: SWI-Prolog and Yap. This requires close cooperation and agreement between the two systems. The type system is Hindley-Milner.  The main characteristics
of the introduction of types in SWI and Yap are that typing is not mandatory, that typed and untyped code can be mixed, and that the type checker can insert dynamic type checks at the boundaries between typed and untyped code.

The basic decisions and the current status of the Typed Prolog project are described, as well as the remaining tasks and problems to be solved.status: publishe