Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949465
J. Ranhel, Cacilda V. Lima, J. Monteiro, J. E. Kögler, M. Netto
Information can be encoded in spiking neural network (SNN) by precise spike-time relations. This hypothesis can explain cell assembly formation, such as polychronous group (PNG), a notion created to explain how groups of neurons fire time-locked to each other, not necessarily synchronously. In this paper we present a set of PNGs capable of retaining triggering events in bistable states. Triggering events may be data or computational controls. Both, data and control signals are memorized as a result of intrinsic operational PNG attributes, and no neural plasticity mechanisms are involved. This behavior can be fundamental for several computational operations in SNNs. It is shown how bistable neural pools can perform tasks such as binary and stack-like counting, and how they can realize hierarchical organization in parallel computing.
{"title":"Bistable memory and binary counters in spiking neural network","authors":"J. Ranhel, Cacilda V. Lima, J. Monteiro, J. E. Kögler, M. Netto","doi":"10.1109/FOCI.2011.5949465","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949465","url":null,"abstract":"Information can be encoded in spiking neural network (SNN) by precise spike-time relations. This hypothesis can explain cell assembly formation, such as polychronous group (PNG), a notion created to explain how groups of neurons fire time-locked to each other, not necessarily synchronously. In this paper we present a set of PNGs capable of retaining triggering events in bistable states. Triggering events may be data or computational controls. Both, data and control signals are memorized as a result of intrinsic operational PNG attributes, and no neural plasticity mechanisms are involved. This behavior can be fundamental for several computational operations in SNNs. It is shown how bistable neural pools can perform tasks such as binary and stack-like counting, and how they can realize hierarchical organization in parallel computing.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"102 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116295618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949471
Leticia Hernando, J. A. Pascual, A. Mendiburu, J. A. Lozano
This work is related to the search of complexity measures for instances of combinatorial optimization problems. Particularly, we have carried out a study about the complexity of random instances of the Traveling Salesman Problem under the 2-exchange neighbor system. We have proposed two descriptors of complexity: the proportion of the size of the basin of attraction of the global optimum over the size of the search space and the proportion of the number of different local optima over the size of the search space. We have analyzed the evolution of these descriptors as the size of the problem grows. After that, and using our complexity measures, we find a phase transition phenomenon in the complexity of the instances.
{"title":"A study on the complexity of TSP instances under the 2-exchange neighbor system","authors":"Leticia Hernando, J. A. Pascual, A. Mendiburu, J. A. Lozano","doi":"10.1109/FOCI.2011.5949471","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949471","url":null,"abstract":"This work is related to the search of complexity measures for instances of combinatorial optimization problems. Particularly, we have carried out a study about the complexity of random instances of the Traveling Salesman Problem under the 2-exchange neighbor system. We have proposed two descriptors of complexity: the proportion of the size of the basin of attraction of the global optimum over the size of the search space and the proportion of the number of different local optima over the size of the search space. We have analyzed the evolution of these descriptors as the size of the problem grows. After that, and using our complexity measures, we find a phase transition phenomenon in the complexity of the instances.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124755957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949462
S. Massanet, J. Torrens
A new class of fuzzy implications called (h, e)-implications is introduced. They are implications generated from an additive generator of a representable uninorm in a similar way of Yager's f- and g-implications which are generated from additive generators of continuous Archimedean t-norms and t-conorms, respectively. In addition, they satisfy a classical property of some types of implications derived from uninorms that is I(e, y) = y for all y ∈ [0, 1] and they are another example of a fuzzy implication satisfying the exchange principle but not the law of importation for any t-norm, in fact for any function F : [0, 1]2 → [0, 1]. Other properties of these implications are studied in detail such as other classical tautologies: contrapositive symmetry and distributivity. Finally, it is proved that they do not intersect with any of the most used classes of implications.
{"title":"Implications generated from additive generators of representable uninorms: (h, e)-implications","authors":"S. Massanet, J. Torrens","doi":"10.1109/FOCI.2011.5949462","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949462","url":null,"abstract":"A new class of fuzzy implications called (h, e)-implications is introduced. They are implications generated from an additive generator of a representable uninorm in a similar way of Yager's f- and g-implications which are generated from additive generators of continuous Archimedean t-norms and t-conorms, respectively. In addition, they satisfy a classical property of some types of implications derived from uninorms that is I(e, y) = y for all y ∈ [0, 1] and they are another example of a fuzzy implication satisfying the exchange principle but not the law of importation for any t-norm, in fact for any function F : [0, 1]2 → [0, 1]. Other properties of these implications are studied in detail such as other classical tautologies: contrapositive symmetry and distributivity. Finally, it is proved that they do not intersect with any of the most used classes of implications.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127244315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949469
D. Anguita, L. Ghelardoni, A. Ghio, S. Ridella
In this paper, we focus the attention on one of the oldest problems in pattern recognition and machine learning: the estimation of the generalization error of a classifier through a test set. Despite this problem has been addressed for several decades, the last word has not yet been written, as new proposals continue to appear in the literature. Our objective is to survey and compare old and new techniques, in terms of quality of the estimation, easiness of use, and rigorousness of the approach.
{"title":"Test error bounds for classifiers: A survey of old and new results","authors":"D. Anguita, L. Ghelardoni, A. Ghio, S. Ridella","doi":"10.1109/FOCI.2011.5949469","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949469","url":null,"abstract":"In this paper, we focus the attention on one of the oldest problems in pattern recognition and machine learning: the estimation of the generalization error of a classifier through a test set. Despite this problem has been addressed for several decades, the last word has not yet been written, as new proposals continue to appear in the literature. Our objective is to survey and compare old and new techniques, in terms of quality of the estimation, easiness of use, and rigorousness of the approach.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"5 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114118677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949475
Enrico Ferrari, M. Muselli
Starting from the theoretical framework of reliable learning, a new classification algorithm capable of using prior information on the reliability of a training set has been developed. It consists in a straightforward modification of the standard technique adopted in the conventional Support Vector Machine (SVM) approach: the knowledge about reliability, encoded by adding a binary label to each example of the training set (asserting if the classification is reliable or not), is employed to properly modify the constrained optimization problem for the generalized optimal hyperplane. Hence, the name Reliable Support Vector Machines (RSVM) is adopted for models built according to the proposed algorithm. Specific tests have been carried out to verify how RSVM performs in comparison with standard SVM, showing a significant improvement in classification accuracy.
{"title":"Implementing reliable learning through Reliable Support Vector Machines","authors":"Enrico Ferrari, M. Muselli","doi":"10.1109/FOCI.2011.5949475","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949475","url":null,"abstract":"Starting from the theoretical framework of reliable learning, a new classification algorithm capable of using prior information on the reliability of a training set has been developed. It consists in a straightforward modification of the standard technique adopted in the conventional Support Vector Machine (SVM) approach: the knowledge about reliability, encoded by adding a binary label to each example of the training set (asserting if the classification is reliable or not), is employed to properly modify the constrained optimization problem for the generalized optimal hyperplane. Hence, the name Reliable Support Vector Machines (RSVM) is adopted for models built according to the proposed algorithm. Specific tests have been carried out to verify how RSVM performs in comparison with standard SVM, showing a significant improvement in classification accuracy.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123419708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949479
D. Dubois, H. Prade
Two important ideas at the core of Zadeh's seminal contributions to fuzzy logic and approximate reasoning are the notions of granulation and of possibilistic uncertainty. In this paper, elaborating on the basis of some formal analogy, recently made by the authors, between possibility theory and formal concept analysis, we suggest other bridges between theories for which the concept of granulation is central. We highlight the common features between the notion of extensional fuzzy set with respect to a similarity relation and the notion of concept. We also discuss the case of fuzzy rough sets. Thus, we point out some fruitful cross-fertilizations between the possibilistic representation of information and several views of granulation emphasizing the idea of clusters of points that can be identified respectively on the basis of their closeness, or of their common labeling in terms of properties.
{"title":"Bridging gaps between several frameworks for the idea of granulation","authors":"D. Dubois, H. Prade","doi":"10.1109/FOCI.2011.5949479","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949479","url":null,"abstract":"Two important ideas at the core of Zadeh's seminal contributions to fuzzy logic and approximate reasoning are the notions of granulation and of possibilistic uncertainty. In this paper, elaborating on the basis of some formal analogy, recently made by the authors, between possibility theory and formal concept analysis, we suggest other bridges between theories for which the concept of granulation is central. We highlight the common features between the notion of extensional fuzzy set with respect to a similarity relation and the notion of concept. We also discuss the case of fuzzy rough sets. Thus, we point out some fruitful cross-fertilizations between the possibilistic representation of information and several views of granulation emphasizing the idea of clusters of points that can be identified respectively on the basis of their closeness, or of their common labeling in terms of properties.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125675374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949477
Maria Letizia Guerra, Luciano Stefanini
The comparison of intervals, following several order relations, is relevant in interval linear programming methods to solve many real-life problems. The determination of coefficients as crisp values is practically impossible in reality, where data sources are often uncertain, vague and incomplete. The uncertainty can be modelled with coefficients that vary in intervals, making possible as decision making process that is common in the areas of soft sciences like social science, economics, finance and management studies. To help comparison of intervals according to different relevant order relations, a general comparison index is proposed and some properties are illustrated.
{"title":"A comparison index for interval ordering","authors":"Maria Letizia Guerra, Luciano Stefanini","doi":"10.1109/FOCI.2011.5949477","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949477","url":null,"abstract":"The comparison of intervals, following several order relations, is relevant in interval linear programming methods to solve many real-life problems. The determination of coefficients as crisp values is practically impossible in reality, where data sources are often uncertain, vague and incomplete. The uncertainty can be modelled with coefficients that vary in intervals, making possible as decision making process that is common in the areas of soft sciences like social science, economics, finance and management studies. To help comparison of intervals according to different relevant order relations, a general comparison index is proposed and some properties are illustrated.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125896430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949481
A. Gegov
This tutorial introduces the novel concept of a fuzzy rule based network whose nodes are fuzzy rule bases and the connections between the nodes are the interactions between these rule bases. A fuzzy network is viewed as a fuzzy system with networked rule bases as opposed to fuzzy systems with single or multiple rule bases. A comparison between different types of fuzzy systems is presented as well as formal models for fuzzy networks such as Boolean matrices, binary relations, block schemes and topological expressions.
{"title":"Fuzzy rule based networks","authors":"A. Gegov","doi":"10.1109/FOCI.2011.5949481","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949481","url":null,"abstract":"This tutorial introduces the novel concept of a fuzzy rule based network whose nodes are fuzzy rule bases and the connections between the nodes are the interactions between these rule bases. A fuzzy network is viewed as a fuzzy system with networked rule bases as opposed to fuzzy systems with single or multiple rule bases. A comparison between different types of fuzzy systems is presented as well as formal models for fuzzy networks such as Boolean matrices, binary relations, block schemes and topological expressions.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116655790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949476
N. Madrid, M. Ojeda‐Aciego
Based on the recently proved fact that the continuity of the connectives involved in a normal residuated logic program ensures the existence of fuzzy stable models, we focus on the assignment of a fuzzy stable model semantics to inconsistent classical logic programs on the basis of the separation of the notion of inconsistency and uncertainty.
{"title":"On the use of fuzzy stable models for inconsistent classical logic programs","authors":"N. Madrid, M. Ojeda‐Aciego","doi":"10.1109/FOCI.2011.5949476","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949476","url":null,"abstract":"Based on the recently proved fact that the continuity of the connectives involved in a normal residuated logic program ensures the existence of fuzzy stable models, we focus on the assignment of a fuzzy stable model semantics to inconsistent classical logic programs on the basis of the separation of the notion of inconsistency and uncertainty.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117332873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-04-11DOI: 10.1109/FOCI.2011.5949466
M. Daňková, M. Štěpnička, B. Baets
In this contribution, we will introduce a notion of monotonicity of a fuzzy relation as a graded property. We will study its behavior w.r.t. fuzzy set operations and show relationship between monotone crisp functions and monotone fuzzy relations. Finally, a connection to special models of a monotone fuzzy rule base system will be provided.
{"title":"Grades of Monotonicity of Fuzzy Relations and Their Application to Fuzzy Rule Bases","authors":"M. Daňková, M. Štěpnička, B. Baets","doi":"10.1109/FOCI.2011.5949466","DOIUrl":"https://doi.org/10.1109/FOCI.2011.5949466","url":null,"abstract":"In this contribution, we will introduce a notion of monotonicity of a fuzzy relation as a graded property. We will study its behavior w.r.t. fuzzy set operations and show relationship between monotone crisp functions and monotone fuzzy relations. Finally, a connection to special models of a monotone fuzzy rule base system will be provided.","PeriodicalId":106271,"journal":{"name":"2011 IEEE Symposium on Foundations of Computational Intelligence (FOCI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130385257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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