pinecone/core-2020-05-10-deduplication huggingface dataset:
Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem
Gaussian Adaptation Revisited – An Entropic View on Covariance Matrix Adaptation

We revisit Gaussian Adaptation (GaA), a black-box optimizer for discrete and continuous problems that has been developed in the late 1960’s. This largely neglected search heuristic shares several interesting features with the well-known Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and with Simulated Annealing (SA). GaA samples single candidate solutions from a multivariate normal distribution and continuously adapts its first and second moments (mean and covariance) such as to maximize the entropy of the search distribution. Sample-point selection is controlled by a monotonically decreasing acceptance threshold, reminiscent of the cooling schedule in SA. We describe the theoretical foundations of GaA and analyze some key features of this algorithm. We empirically show that GaA converges log-linearly on the sphere function and analyze its behavior on selected non-convex test functions
A directed mutation operator for real coded genetic algorithms

Copyright @ Springer-Verlag Berlin Heidelberg 2010.Developing directed mutation methods has been an interesting research topic to improve the performance of genetic algorithms (GAs) for function optimization. This paper introduces a directed mutation (DM) operator for GAs to explore promising areas in the search space. In this DM method, the statistics information regarding the fitness and distribution of individuals over intervals of each dimension is calculated according to the current population and is used to guide the mutation of an individual toward the neighboring interval that has the best statistics result in each dimension. Experiments are carried out to compare the proposed DM technique with an existing directed variation on a set of benchmark test problems. The experimental results show that the proposed DM operator achieves a better performance than the directed variation on most test problems
Advancing Model-Building for Many-Objective Optimization Estimation of Distribution Algorithms

Proceedings of: 3rd European Event on Bio-Inspired Algorithms for Continuous Parameter Optimisation  (EvoNUM 2010) [associated to:  EvoApplications 2010. European Conference on the Applications of Evolutionary Computation]. Istambul, Turkey, April 7-9, 2010In order to achieve a substantial improvement of MOEDAs regarding MOEAs it is necessary to adapt their model-building algorithms. Most current model-building schemes used so far off-the-shelf machine learning methods. These methods are mostly error-based learning algorithms. However, the model-building problem has specific requirements that those methods do not meet and even avoid. In this work we dissect this issue and propose a set of algorithms that can be used to bridge the gap of MOEDA application. A set of experiments are carried out in order to sustain our assertionsThis work was supported by projects CICYT TIN2008-06742-C02-02/TSI, CICYT
TEC2008-06732-C02-02/TEC, SINPROB, CAM CONTEXTS S2009/TIC-1485 and DPS2008-07029-C02-0Publicad
Multi-population genetic algorithms with immigrants scheme for dynamic shortest path routing problems in mobile ad hoc networks

Copyright @ Springer-Verlag Berlin Heidelberg 2010.The static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless mesh network, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem in mobile wireless networks. In this paper, we propose to use multi-population GAs with immigrants scheme to solve the dynamic SP problem in MANETs which is the representative of new generation wireless networks. The experimental results show that the proposed GAs can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change.This work was supported by the Engineering and Physical Sciences Research Council(EPSRC) of UK under Grant EP/E060722/1
Evolutionary multi-stage financial scenario tree generation

Multi-stage financial decision optimization under uncertainty depends on a
careful numerical approximation of the underlying stochastic process, which
describes the future returns of the selected assets or asset categories.
Various approaches towards an optimal generation of discrete-time,
discrete-state approximations (represented as scenario trees) have been
suggested in the literature. In this paper, a new evolutionary algorithm to
create scenario trees for multi-stage financial optimization models will be
presented. Numerical results and implementation details conclude the paper
Haskell type constraints unleashed

The popular Glasgow Haskell Compiler extends the Haskell 98 
type system with several powerful features, leading to an expressive language of type terms. In contrast, constraints over types have received 
much less attention, creating an imbalance in the expressivity of the 
type system. In this paper, we rectify the imbalance, transferring familiar type-level constructs, synonyms and families, to the language of 
constraints, providing a symmetrical set of features at the type-level and 
constraint-level. We introduce constraint synonyms and constraint families, and illustrate their increased expressivity for improving the utility 
of polymorphic EDSLs in Haskell, amongst other examples. We provide 
a discussion of the semantics of the new features relative to existing type 
system features and similar proposals, including details of termination.status: publishe
Explanation of the BGS subsurface viewer

The Subsurface Viewer is a package developed by INSIGHT Geologische\ud
Softwaresysteme GmbH for the visualisation and analysis of\ud
digital geoscientific spatial models.\ud
The viewer has been developed following the popularity of\ud
INSIGHT’s Geological Surveying and Investigation in 3D (GSI3D)\ud
software tool that is in use extensively inside the British Geological\ud
Survey (BGS) for the construction of systematic near surface models\ud
(Kessler and Mathers 2004; Kessler et al. 2005; Kessler et al. 2009).\ud
These notes describe and display the use of the interface windows to\ud
the software.\ud
A Geological Model is embedded within the Viewer as a means of\ud
publication and distribution to the wider world. In this way the constructed\ud
model can be examined and analysed to produce:\ud
 models displaying the geology or other pre-selected\ud
applied themes (e.g. hydrogeological properties)\ud
 geological maps (at surface and uncovered)\ud
 user defined synthetic borehole logs\ud
 user defined horizontal slices and vertical sections\ud
 visualisation of the geometry of single and combined\ud
units\ud
The model supplied with the Subsurface Viewer is encrypted and\ud
cannot be altered, nor can users add additional data as the viewer is a\ud
standalone package. The model and the necessary Java software and\ud
extensions are all included in the package. The model described\ud
herein (West Thurrock) is freely downloadable from the BGS website\ud
at:\ud
http://www.bgs.ac.uk/science/thamesgateway/3dModels.htm
Using the quantum probability ranking principle to rank interdependent documents

A known limitation of the Probability Ranking Principle (PRP) is that it does not cater for dependence between documents. Recently, the Quantum Probability Ranking Principle (QPRP) has been proposed, which implicitly captures dependencies between documents through “quantum interference”. This paper explores whether this new ranking principle leads to improved performance for subtopic retrieval, where novelty and diversity is required. In a thorough empirical investigation, models based on the PRP, as well as other recently proposed ranking strategies for subtopic retrieval (i.e. Maximal Marginal Relevance (MMR) and Portfolio Theory(PT)), are compared against the QPRP. On the given task, it is shown that the QPRP outperforms these other ranking strategies. And unlike MMR and PT, one of the main advantages of the QPRP is that no parameter estimation/tuning is required; making the QPRP both simple and effective. This research demonstrates that the application of quantum theory to problems within information retrieval can lead to significant improvements
A performance prediction approach to enhance collaborative filtering performance

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-12275-0_34Proceedings of 32nd European Conference on IR Research, ECIR 2010, Milton Keynes, UK, March 28-31, 2010.Performance prediction has gained increasing attention in the IR field since the half of the past decade and has become an established research topic in the field. The present work restates the problem in the area of Collaborative Filtering (CF), where it has barely been researched so far. We investigate the adaptation of clarity-based query performance predictors to predict neighbor performance in CF. A predictor is proposed and introduced in a kNN CF algorithm to produce a dynamic variant where neighbor ratings are weighted based on their predicted performance. The properties of the predictor are empirically studied by, first, checking the correlation of the predictor output with a proposed measure of neighbor performance. Then, the performance of the dynamic kNN variant is examined on different sparsity and neighborhood size conditions, where the variant consistently outperforms the baseline algorithm, with increasing difference on small neighborhoods.This work was supported by the Spanish Ministry of Science and
Innovation (TIN2008-06566-C04-02) and the Ministry of Industry, Tourism and
Commerce (CENIT-2007-1012
Personalizing web search with folksonomy-based user and document profiles

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-12275-0_37Proceedings of 32nd European Conference on IR Research, ECIR 2010, Milton Keynes, UK, March 28-31, 2010.Web search personalization aims to adapt search results to a user based on his tastes, interests and needs. The way in which such personal preferences are captured, modeled and exploited distinguishes the different personalization strategies. In this paper, we propose to represent a user profile in terms of social tags, manually provided by users in folksonomy systems to describe, categorize and organize items of interest, and investigate a number of novel techniques that exploit the users’ social tags to re-rank results obtained with a Web search engine. An evaluation conducted with a dataset from Delicious social bookmarking system shows that our personalization techniques clearly outperform state of the art approaches.This research was supported by the European Commission
under contract FP6-027122-SALERO and by the Spanish Ministry of Science and
Education (TIN2008-06566-C04-02
Polygonal light source estimation

LNCS v. 5996 is the conference proceedings of AACV 2009This paper studies the problem of light estimation using a specular sphere. Most existing work on light estimation assumes distant point light sources, while this work considers an area light source which is estimated in 3D space by reconstructing its edges. An empirical analysis on existing methods for line estimation from a single view is carried out, and it is shown that line estimation for a single view of a sphere is an ill-conditioned configuration. By considering a second identical sphere, a closed form solution for single view polygonal light estimation is proposed. In addition, this paper also proposes an iterative approach based on two unknown views of just a single sphere. Experimental results on both synthetic and real data are presented. © Springer-Verlag 2010.postprintThe 9th Asian Conference on Computer Vision (AACV 2009), Xi’an, China, 23-27 September 2009. In Lecture Notes in Computer Science, 2009, v. 5996, p. 96-10
Globally Optimal Spatio-temporal Reconstruction from Cluttered Videos

International audienceWe propose a method for multi-view reconstruction from videos adapted to dynamic cluttered scenes under uncontrolled imaging conditions. Taking visibility into account, and being based on a global optimization of a true spatio-temporal energy, it oilers several desirable properties: no need for silhouettes, robustness to noise, independent from any initialization, no heuristic force, reduced flickering results, etc. Results on real-world data proves the potential of what is, to our knowledge, the only globally optimal spatio-temporal multi-view reconstruction method
A Graph-based Feature Combination Approach to Object Tracking

In this paper, we present a feature combination approach to object tracking based upon graph embedding techniques. The method presented here abstracts the low complexity features used for purposes of tracking to a relational structure and employs graph-spectral methods to combine them. This gives rise to a feature combination scheme which minimises the mutual cross-correlation between features and is devoid of free parameters. It also allows an analytical solution making use of matrix factorisation techniques. The new target location is recovered making use of a weighted combination of target-centre shifts corresponding to each of the features under study, where the feature weights arise from a cost function governed by the embedding process. This treatment permits the update of the feature weights in an on-line fashion in a straightforward manner. We illustrate the performance of our method in real-world image sequences and compare our results to a number of alternatives.Full Tex
Transductive Segmentation of Textured Meshes

International audienceThis paper addresses the problem of segmenting a textured mesh into objects or object classes, consistently with user-supplied seeds. We view this task as transductive learning and use the flexibility of kernel-based weights to incorporate a various number of diverse features. Our method combines a Laplacian graph regularizer that enforces spatial coherence in label propagation and an SVM classifier that ensures dissemination of the seeds characteristics. Our interactive framework allows to easily specify classes seeds with sketches drawn on the mesh and potentially refine the segmentation. We obtain qualitatively good segmentations on several architectural scenes and show the applicability of our method to outliers removing
The RIPE NCC internet measurement data repository

This paper describes datasets that will shortly be made available to the research community through an Internet measurement data repository operated by the RIPE NCC. The datasets include measurements collected by RIPE NCC projects, packet trace sets recovered from the defunct NLANR website and datasets collected and currently hosted by other research institutions. This work aims to raise awareness of these datasets amongst researchers and to promote discussion about possible changes to the data collection processes to ensure that the measurements are relevant and useful to the community
Efficient Entropy Estimation for Mutual                                    Information Analysis Using B-Splines

International audienceThe Correlation Power Analysis (CPA) is probably the                            most used side-channel attack because it seems to fit the power model of                            most standard CMOS devices and is very efficiently computed. However,                            the Pearson correlation coefficient used in the CPA measures only linear                            statistical dependences where the Mutual Information (MI) takes into                            account both linear and nonlinear dependences. Even if there can be                            simultaneously large correlation coefficients quantified by the                            correlation coefficient and weak dependences quantified by the MI, we                            can expect to get a more profound understanding about interactions from                            an MI Analysis (MIA). We study methods that improve the non-parametric                            Probability Density Functions (PDF) in the estimation of the entropies                            and, in particular, the use of B-spline basis functions as pdf                            estimators. Our results indicate an improvement of two fold in the                            number of required samples compared to a classic MI estimation. The                            B-spline smoothing technique can also be applied to the rencently                            introduced Cramér-von-Mises test
An Energy-Efficient Symmetric Cryptography Based Authentication Scheme for Wireless Sensor Networks

8 páginas.Sensor networks are ad-hoc mobile networks that include sensor nodes with limited computational and communication capabilities. They have become an economically viable monitoring solution for a wide variety of applications. Obviously, it is important to ensure security and, taking into account limited resources available in wireless sensor networks, the use of symmetric cryptography is strongly recommended. In this paper we present a light-weight authentication model for wireless sensor networks composed of a key management and an authentication protocol. It is based on simple symmetric cryptographic primitives with very low computational requirements, and it achieves better results than other similar proposals in the literature. Compared to SPINS and BROSK protocols, our system can reduce energy consumption by up to 98% and 67% respectively. It also scales well with the size of the network, due to it only requiring one interchanged message, regardless of the total number of nodes in the network.This work was supported in part by CDTI (Spain) and the companies INDRA, Uni´on\ud
Fenosa, Tecnobit, Visual Tool, Brainstorm, SAC and Technosafe under Project\ud
Cenit-HESPERIA as well as supported by Ministry of Science and Innovation and\ud
European FEDER Fund under Project TIN2008-02236/TSI.Peer reviewe
An architecture for the design of context-aware conversational agents

Proceedings of: 8th International Conference on Practical Applications of Agents and Multiagent Systems, Salamanca, Spain, April 26-28, 2010.In this paper, we present a architecture for the development of conversational agents that provide a personalized service to the user. The different agents included in our architecture facilitate an adapted service by taking into account context information and users specific requirements and preferences. This functionality is achieved by means of the introduction of a context manager and the definition of user profiles. We describe the main characteristics of our architecture and its application to develop and evaluate an information system for an academic domain.CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02- 02/TEC,
SINPROB, CAM MADRINET S-0505/TIC/0255 and DPS2008-07029-C02-02.Publicad
Biometric database acquisition close to “Real World” conditions

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-12397-9_16Revised Selected Papers of Second COST 2102 International Training School, Dublin, Ireland, March 23-27, 2009In this paper we present an autonomous biometric device developed in the framework of a national project. This system is able to capture speech, hand-geometry, online signature and face, and can open a door when the user is positively verified. Nevertheless the main purpose is to acquire a database without supervision (normal databases are collected in the presence of a supervisor that tells you what to do in front of the device, which is an unrealistic situation). This system will permit us to explain the main differences between what we call "real conditions" as opposed to "laboratory conditions".This work has been supported by FEDER and MEC, TEC2006-13141-C03/TCM, and
COST-210
Multi-agent personal memory assistant

Springer - Series Advances in Intelligent and Soft Computing, vol. 71Memory is one of our most precious goods has it gives us the ability to store,
retain and recall information thus giving a meaning to our past and help us to envision our
future, dreams and expectations. However, ageing decreases the capacity of remembering
and the capacity to store new memories, thus affecting our life quality. These presented
problems configure a social and human dilemma. With the presented work we intend to
address some of these problems, thru the use of the Personal Memory Assistant (PMA)
concept in order to help its user to remember things and occurrences in a proactive manner.
We will also address socialization and relaxation events that should be part of the user's
life. With the use of a Multi-Agent System to implement the PMA, the objectives can be
achieved in a ubiquitous and highly configurable manner. It is presented here the platform
concept, scheme and the agent characteristics and their contribution to each and every
agent
Enhancing the role of multi-agent systems in the development of intelligent environments

Springer - Series Advances in Intelligent and Soft Computing, vol. 71The development of Intelligent Environments is a complex challenge. This
complexity arises, in part, from the amount of different devices that need to be seamlessly
integrated in a common and homogeneous environment, despite the fact of each device
having its own characteristics. This heterogeneity of devices is particularly risky when one
passes from the specification to the implementation phase, where all unexpected things start
to happen. Multi-agent systems are the paradigm par excellence for implementing
Intelligent Environments. However, traditionally, agents are only used at the
implementation phase. In this paper we propose a new 3 step approach in which agents are
used during all the development process, playing undoubtedly a much more preponderant
role and making the path from the specification to the implementation a much easier and
controllable one, always having in mind the challenges of the development of Intelligent
Environments