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|---|---|---|---|---|
1,794 | 2 | Title: NONLINEAR NONEQUILIBRIUM NONQUANTUM NONCHAOTIC STATISTICAL MECHANICS OF NEOCORTICAL INTERACTIONS
Abstract: The work in progress reported by Wright & Liley shows great promise, primarily because of their experimental and simulation paradigms. However, their tentative conclusion that macroscopic neocortex may be... | [
1795,
2178,
2545
] | Validation |
1,795 | 2 | Title: Application of statistical mechanics methodol- ogy to term-structure bond-pricing models, Mathl. Comput. Modelling Application of
Abstract: The work in progress reported by Wright & Liley shows great promise, primarily because of their experimental and simulation paradigms. However, their tentative conclusion th... | [
1775,
1788,
1793,
1794,
2082,
2178,
2181,
2545
] | Test |
1,796 | 1 | Title: Evaluating and Improving Steady State Evolutionary Algorithms on Constraint Satisfaction Problems
Abstract: The work in progress reported by Wright & Liley shows great promise, primarily because of their experimental and simulation paradigms. However, their tentative conclusion that macroscopic neocortex may b... | [
833,
1030,
1917,
2001
] | Validation |
1,797 | 1 | Title: Improving the Performance of Evolutionary Optimization by Dynamically Scaling the Evaluation Function
Abstract: Traditional evolutionary optimization algorithms assume a static evaluation function, according to which solutions are evolved. Incremental evolution is an approach through which a dynamic evaluation... | [
1221,
1409,
2200
] | Validation |
1,798 | 2 | Title: Toward a unified theory of spatiotemporal processing in the retina
Abstract: Traditional evolutionary optimization algorithms assume a static evaluation function, according to which solutions are evolved. Incremental evolution is an approach through which a dynamic evaluation function is scaled over time in or... | [
2120
] | Validation |
1,799 | 1 | Title: On the Effectiveness of Evolutionary Search in High-Dimensional NK-Landscapes
Abstract: NK-landscapes offer the ability to assess the performance of evolutionary algorithms on problems with different degrees of epistasis. In this paper, we study the performance of six algorithms in NK-landscapes with low and h... | [
163,
727,
1424,
2205
] | Validation |
1,800 | 3 | Title: Rational Belief Revision (Preliminary Report)
Abstract: Theories of rational belief revision recently proposed by Alchourron, Gardenfors, Makin-son, and Nebel illuminate many important issues but impose unnecessarily strong standards for correct revisions and make strong assumptions about what information is a... | [
342,
1901,
1907,
1994,
1995,
2016
] | Test |
1,801 | 2 | Title: A FAMILY OF FIXED-POINT ALGORITHMS FOR INDEPENDENT COMPONENT ANALYSIS
Abstract: Independent Component Analysis (ICA) is a statistical signal processing technique whose main applications are blind source separation, blind deconvolution, and feature extraction. Estimation of ICA is usually performed by optimizin... | [
576,
1067,
1814,
1821
] | Train |
1,802 | 3 | Title: Toward a Market Model for Bayesian Inference
Abstract: We present a methodology for representing probabilistic relationships in a general-equilibrium economic model. Specifically, we define a precise mapping from a Bayesian network with binary nodes to a market price system where consumers and producers trade ... | [
1777,
2064
] | Train |
1,803 | 3 | Title: Change Point and Change Curve Modeling in Stochastic Processes and Spatial Statistics
Abstract: 1 This article will appear in Volume 1, no. 4 (1994) of Journal of Applied Statistical Science. Adrian E. Raftery is Professor of Statistics and Sociology, Department of Statistics, GN-22, University of Washington, ... | [
84,
99,
1913
] | Validation |
1,804 | 0 | Title: CHARADE: a Platform for Emergencies Management Systems
Abstract: This paper describe the functional architecture of CHARADE a software platform devoted to the development of a new generation of intelligent environmental decision support systems. The CHARADE platform is based on the a task-oriented approach to ... | [
1805,
2289
] | Train |
1,805 | 0 | Title: Planning in a Complex Real Domain
Abstract: Dimensions of complexity raised during the definition of a system aimed at supporting the planning of initial attack to forest fires are presented and discussed. The complexity deriving from the highly dynamic and unpredictable domain of forest fire, the one realated... | [
1804,
2289
] | Test |
1,806 | 2 | Title: MBP on T0: mixing floating- and fixed-point formats in BP learning
Abstract: We examine the efficient implementation of back prop type algorithms on T0 [4], a vector processor with a fixed point engine, designed for neural network simulation. A matrix formulation of back prop, Matrix Back Prop [1], has been sh... | [
2279,
2570
] | Train |
1,807 | 1 | Title: A Preliminary Investigation of Evolution as a Form Design Strategy
Abstract: We describe the preliminary version of our investigative software, GGE Generative Genetic Explorer, in which genetic operations interact with Au-toCAD to generate novel 3D forms for the architect. GGE allows us to asess how evolutiona... | [
163,
2490
] | Validation |
1,808 | 6 | Title: Where Do SE-trees Perform? (Part I)
Abstract: As a classifier, a Set Enumeration (SE) tree can be viewed as a generalization of decision trees. We empirically characterize domains in which SE-trees are particularly advantageous relative to decision trees. Specifically, we show that: | [
638,
2210
] | Train |
1,809 | 0 | Title: Rule Generation and Compaction in the wwtp
Abstract: In this paper we discuss our approach to learning classification rules from data. We sketch out two modules of our architecture, namely LINNEO + and GAR. LINNEO + , which is a knowledge acquisition tool for ill-structured domains automatically generating cla... | [
2071,
2585
] | Train |
1,810 | 2 | Title: Computation and Psychophysics of Sensorimotor Integration
Abstract: In this paper we discuss our approach to learning classification rules from data. We sketch out two modules of our architecture, namely LINNEO + and GAR. LINNEO + , which is a knowledge acquisition tool for ill-structured domains automatically... | [
1766
] | Validation |
1,811 | 2 | Title: Disambiguation and Grammar as Emergent Soft Constraints
Abstract: When reading a sentence such as "The diplomat threw the ball in the ballpark for the princess" our interpretation changes from a dance event to baseball and back to dance. Such on-line disambiguation happens automatically and appears to be based... | [
204,
427,
2410
] | Train |
1,812 | 2 | Title: GENERALIZATION PERFORMANCE OF BACKPROPAGATION LEARNING ON A SYLLABIFICATION TASK
Abstract: We investigated the generalization capabilities of backpropagation learning in feed-forward and recurrent feed-forward connectionist networks on the assignment of syllable boundaries to orthographic representations in Du... | [
783,
785,
862,
1155,
1407,
1513,
2364
] | Validation |
1,813 | 2 | Title: Pruning Strategies for the MTiling Constructive Learning Algorithm
Abstract: We present a framework for incorporating pruning strategies in the MTiling constructive neural network learning algorithm. Pruning involves elimination of redundant elements (connection weights or neurons) from a network and is of con... | [
503,
1818,
2393
] | Train |
1,814 | 2 | Title: Independent Component Analysis by General Non-linear Hebbian-like Learning Rules
Abstract: A number of neural learning rules have been recently proposed for Independent Component Analysis (ICA). The rules are usually derived from information-theoretic criteria such as maximum entropy or minimum mutual informat... | [
570,
576,
834,
1067,
1801
] | Validation |
1,815 | 2 | Title: Submitted to Circuits, Systems and Signal Processing Neural Network Constructive Algorithms: Trading Generalization for Learning Efficiency?
Abstract: There are currently several types of constructive, or growth, algorithms available for training a feed-forward neural network. This paper describes and explains... | [
238,
253,
489,
2670,
2671
] | Validation |
1,816 | 4 | Title: Generalized Prioritized Sweeping
Abstract: Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent's limited computational resources to achieve a good estimate of the value of environment states. To choose effectively where to spend a costly planning step, classic pr... | [
558,
559,
566,
1934,
2485
] | Train |
1,817 | 2 | Title: Selection of Distance Metrics and Feature Subsets for k-Nearest Neighbor Classifiers
Abstract: Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent's limited computational resources to achieve a good estimate of the value of environment states. To choose effective... | [
2464
] | Train |
1,818 | 2 | Title: Constructive Neural Network Learning Algorithms for Multi-Category Real-Valued Pattern Classification
Abstract: Prioritized sweeping is a model-based reinforcement learning method that attempts to focus an agent's limited computational resources to achieve a good estimate of the value of environment states. To... | [
1813,
2029,
2073
] | Validation |
1,819 | 5 | Title: The Difficulties of Learning Logic Programs with Cut
Abstract: As real logic programmers normally use cut (!), an effective learning procedure for logic programs should be able to deal with it. Because the cut predicate has only a procedural meaning, clauses containing cut cannot be learned using an extensiona... | [
224,
1781,
2580
] | Train |
1,820 | 2 | Title: The Gamma MLP for Speech Phoneme Recognition
Abstract: We define a Gamma multi-layer perceptron (MLP) as an MLP with the usual synaptic weights replaced by gamma filters (as proposed by de Vries and Principe (de Vries & Principe 1992)) and associated gain terms throughout all layers. We derive gradient descent... | [
2383,
2569
] | Train |
1,821 | 2 | Title: One-unit Learning Rules for Independent Component Analysis
Abstract: Neural one-unit learning rules for the problem of Independent Component Analysis (ICA) and blind source separation are introduced. In these new algorithms, every ICA neuron develops into a separator that tnds one of the independent components... | [
834,
1801
] | Train |
1,822 | 2 | Title: Book Review New Kids on the Block way in the field of connectionist modeling. The
Abstract: Connectionist Models is a collection of forty papers representing a wide variety of research topics in connectionism. The book is distinguished by a single feature: the papers are almost exclusively contributions of gradu... | [
1656,
2662
] | Test |
1,823 | 6 | Title: The Complexity of Theory Revision
Abstract: A knowledge-based system uses its database (a.k.a. its "theory") to produce answers to the queries it receives. Unfortunately, these answers may be incorrect if the underlying theory is faulty. Standard "theory revision" systems use a given set of "labeled queries" (... | [
2487,
2580
] | Test |
1,824 | 6 | Title: Constructing Conjunctions using Systematic Search on Decision Trees
Abstract: This paper investigates a dynamic path-based method for constructing conjunctions as new attributes for decision tree learning. It searches for conditions (attribute-value pairs) from paths to form new attributes. Compared with other... | [
102,
1595,
2006,
2675
] | Train |
1,825 | 2 | Title: GUESSING CAN OUTPERFORM MANY LONG TIME LAG ALGORITHMS
Abstract: Numerous recent papers focus on standard recurrent nets' problems with long time lags between relevant signals. Some propose rather sophisticated, alternative methods. We show: many problems used to test previous methods can be solved more quickly... | [
68,
121,
978,
979,
1966
] | Train |
1,826 | 1 | Title: A Computational View of Population Genetics (preliminary version)
Abstract: This paper contributes to the study of nonlinear dynamical systems from a computational perspective. These systems are inherently more powerful than their linear counterparts (such as Markov chains), which have had a wide impact in Com... | [
689,
2630
] | Train |
1,827 | 6 | Title: Efficient Algorithms for Inverting Evolution
Abstract: Evolution is a stochastic process which operates on the DNA of species. The evolutionary process leaves tell-tale signs in the DNA which can be used to construct phylogenies, or evolutionary trees, for a set of species. Maximum Likelihood Estimations (MLE)... | [
299,
574,
1962,
2083,
2110,
2224
] | Train |
1,828 | 4 | Title: Learning in Continuous Domains with Delayed Rewards
Abstract: Much has been done to develop learning techniques for delayed reward problems in worlds where the actions and/or states are approximated by discrete representations. Although this is acceptable in some applications there are many more situations whe... | [
567,
2014,
2018
] | Test |
1,829 | 3 | Title: On the Connection Between Stochastic Smoothing, Filtering and Estimation with Incomplete Data
Abstract: Connections between stochastic smoothing/filtering and estimation with incomplete data are investigated. It is shown, under the right censoring scheme, that the Kaplan-Meier estimator can be characterized as... | [
2421
] | Validation |
1,830 | 0 | Title: Inductive CBR for Customer Support
Abstract: Over the past few years, the telecommunications paradigm has been shifting rapidly from hardware to middleware. In particular, the traditional issues of service characteristics and network control are being replaced by the modern, customer-driven issues of network a... | [
2466,
2585
] | Train |
1,831 | 1 | Title: Some Training Subset Selection Methods for Supervised Learning in Genetic Programming
Abstract: When using the Genetic Programming (GP) Algorithm on a difficult problem with a large set of training cases, a large population size is needed and a very large number of function-tree evaluations must be carried out... | [
163,
1832,
1836
] | Train |
1,832 | 1 | Title: Tackling the Boolean Even N Parity Problem with Genetic Programming and Limited-Error Fitness standard GP
Abstract: This paper presents Limited Error Fitness (LEF), a modification to the standard supervised learning approach in Genetic Programming (GP), in which an individual's fitness score is based on how many... | [
55,
415,
1831,
1836,
2334
] | Train |
1,833 | 6 | Title: Pruning Decision Trees with Misclassification Costs
Abstract: We describe an experimental study of pruning methods for decision tree classifiers when the goal is minimizing loss rather than error. In addition to two common methods for error minimization, CART's cost-complexity pruning and C4.5's error-based pr... | [
2367
] | Train |
1,834 | 1 | Title: Genetic Algorithms, Tournament Selection, and the Effects of Noise
Abstract: IlliGAL Report No. 95006 July 1995 | [
1905
] | Test |
1,835 | 6 | Title: Implementation Issues in the Fourier Transform Algorithm
Abstract: The Fourier transform of boolean functions has come to play an important role in proving many important learnability results. We aim to demonstrate that the Fourier transform techniques are also a useful and practical algorithm in addition to b... | [
2011,
2182
] | Validation |
1,836 | 1 | Title: Small Populations over Many Generations can beat Large Populations over Few Generations in Genetic Programming
Abstract: This paper looks at the use of small populations in Genetic Programming (GP), where the trend in the literature appears to be towards using as large a population as possible, which requires ... | [
415,
1831,
1832,
2334
] | Train |
1,837 | 5 | Title: Data Mining and Knowledge Discovery, Adaptive Fraud Detection
Abstract: One method for detecting fraud is to check for suspicious changes in user behavior. This paper describes the automatic design of user profiling methods for the purpose of fraud detection, using a series of data mining techniques. Specific... | [
382,
2132
] | Validation |
1,838 | 3 | Title: Learning in neural networks with Bayesian prototypes
Abstract: Given a set of samples of a probability distribution on a set of discrete random variables, we study the problem of constructing a good approximative neural network model of the underlying probability distribution. Our approach is based on an unsup... | [
485,
719,
1908,
2380,
2514
] | Test |
1,839 | 1 | Title: Context Preserving Crossover in Genetic Programming.
Abstract: This paper introduces two new crossover operators for Genetic Programming (GP). Contrary to the regular GP crossover, the operators presented attempt to preserve the context in which subtrees appeared in the parent trees. A simple coordinate scheme... | [
290,
2688,
2705
] | Validation |
1,840 | 1 | Title: Hierarchical Genetic Programming (HGP) extensions discover, modify, and exploit subroutines to accelerate the evolution of
Abstract: A fundamental problem in learning from observation and interaction with an environment is defining a good representation, that is a representation which captures the underlying str... | [
2688,
2705
] | Train |
1,841 | 4 | Title: Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Abstract: Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much of the practice (see Barto et al., ... | [
564,
1741
] | Train |
1,842 | 3 | Title: Fall Diagnosis using Dynamic Belief Networks
Abstract: The task is to monitor walking patterns and give early warning of falls using foot switch and mercury trigger sensors. We describe a dynamic belief network model for fall diagnosis which, given evidence from sensor observations, outputs beliefs about the c... | [
1268,
1757,
2341
] | Train |
1,843 | 0 | Title: Goal-based Explanation Evaluation 1
Abstract: 1 I would like to thank my dissertation advisor, Roger Schank, for his very valuable guidance on this research, and to thank the Cognitive Science reviewers for their helpful comments on a draft of this paper. The research described here was conducted primarily at ... | [
2626
] | Validation |
1,844 | 4 | Title: Two Methods for Hierarchy Learning in Reinforcement Environments
Abstract: This paper describes two methods for hierarchically organizing temporal behaviors. The first is more intuitive: grouping together common sequences of events into single units so that they may be treated as individual behaviors. This sys... | [
1845,
1979
] | Test |
1,845 | 4 | Title: ON LEARNING HOW TO LEARN LEARNING STRATEGIES
Abstract: This paper introduces the "incremental self-improvement paradigm". Unlike previous methods, incremental self-improvement encourages a reinforcement learning system to improve the way it learns, and to improve the way it improves the way it learns ..., with... | [
68,
979,
1844,
1979
] | Train |
1,846 | 2 | Title: A Neural Network Architecture for High-Speed Database Query Processing
Abstract: Artificial neural networks (ANN), due to their inherent parallelism and potential fault tolerance, offer an attractive paradigm for robust and efficient implementations of large modern database and knowledge base systems. This pap... | [
1847,
1927,
2537
] | Train |
1,847 | 2 | Title: A Neural Network Architecture for Syntax Analysis
Abstract: Artificial neural networks (ANN), due to their inherent parallelism and potential fault tolerance, offer an attractive paradigm for robust and efficient implementations of large modern database and knowledge base systems. This paper explores a neural ... | [
1846,
1927
] | Test |
1,848 | 6 | Title: On the Power of Equivalence Queries
Abstract: In 1990, Angluin showed that no class exhibiting a combinatorial property called "approximate fingerprints" can be identified exactly using polynomially many Equivalence queries (of polynomial size). Here we show that this is a necessary condition: every class with... | [
2483
] | Train |
1,849 | 5 | Title: Profile-Driven Instruction Level Parallel Scheduling with Application to Super Blocks
Abstract: Code scheduling to exploit instruction level parallelism (ILP) is a critical problem in compiler optimization research, in light of the increased use of long-instruction-word machines. Unfortunately, optimum schedul... | [
2163
] | Test |
1,850 | 1 | Title: Genetic Programming for Pedestrians
Abstract: We propose an extension to the Genetic Programming paradigm which allows users of traditional Genetic Algorithms to evolve computer programs. To this end, we have to introduce mechanisms like transscription, editing and repairing into Genetic Programming. We demons... | [
163,
2554
] | Validation |
1,851 | 2 | Title: Faster Learning in Multi-Layer Networks by Handling
Abstract: Generalized delta rule, popularly known as back-propagation (BP) [9, 5] is probably one of the most widely used procedures for training multi-layer feed-forward networks of sigmoid units. Despite reports of success on a number of interesting problem... | [
503,
1896
] | Validation |
1,852 | 3 | Title: On Sequential Simulation-Based Methods for Bayesian Filtering
Abstract: In this report, we present an overview of sequential simulation-based methods for Bayesian filtering of nonlinear and non-Gaussian dynamic models. It includes in a general framework numerous methods proposed independently in various areas ... | [
99,
2592
] | Train |
1,853 | 6 | Title: 99-113. Construction of Phylogenetic Trees, Science, Fitting the Gene Lineage Into Its Species Lineage. A
Abstract: 6] Farach, M. and Thorup, M. 1993. Fast Comparison of Evolutionary Trees, Technical Report 93-46, DIMACS, Rutgers University, Piscataway, NJ. | [
1861,
2320
] | Train |
1,854 | 0 | Title: Case Retrieval Nets: Basic Ideas and Extensions
Abstract: An efficient retrieval of a relatively small number of relevant cases from a huge case base is a crucial subtask of Case-Based Reasoning. In this article, we present Case Retrieval Nets (CRNs), a memory model that has recently been developed for this ta... | [
75,
1855,
1864,
1976,
2048,
2122,
2299,
2482,
2645
] | Train |
1,855 | 0 | Title: Applying Case Retrieval Nets to Diagnostic Tasks in Technical Domains
Abstract: This paper presents Objectdirected Case Retrieval Nets, a memory model developed for an application of Case-Based Reasoning to the task of technical diagnosis. The key idea is to store cases, i.e. observed symptoms and diagnoses, i... | [
75,
1854,
1864,
2075,
2122,
2299,
2482
] | Train |
1,856 | 3 | Title: Identifiability, Improper Priors and Gibbs Sampling for Generalized Linear Models
Abstract: Alan E. Gelfand is a Professor in the Department of Statistics at the University of Connecti-cut, Storrs, CT 06269. Sujit K. Sahu is a Lecturer at the School of Mathematics, University of Wales, Cardiff, CF2 4YH, UK. Th... | [
2421
] | Train |
1,857 | 3 | Title: Monte Carlo Implementation of Gaussian Process Models for Bayesian Regression and Classification
Abstract: Technical Report No. 9702, Department of Statistics, University of Toronto Abstract. Gaussian processes are a natural way of defining prior distributions over functions of one or more input variables. In ... | [
125,
160,
2020,
2540,
2681
] | Train |
1,858 | 6 | Title: NP-Completeness of Minimum Rule Sets
Abstract: Rule induction systems seek to generate rule sets which are optimal in the complexity of the rule set. This paper develops a formal proof of the NP-Completeness of the problem of generating the simplest rule set (MIN RS) which accurately predicts examples in the t... | [
2481,
2528
] | Train |
1,859 | 4 | Title: Self-Improving Factory Simulation using Continuous-time Average-Reward Reinforcement Learning
Abstract: Many factory optimization problems, from inventory control to scheduling and reliability, can be formulated as continuous-time Markov decision processes. A primary goal in such problems is to find a gain-opt... | [
471,
548,
554,
565,
621,
1791
] | Train |
1,860 | 0 | Title: Efficient Locally Weighted Polynomial Regression Predictions
Abstract: Locally weighted polynomial regression (LWPR) is a popular instance-based algorithm for learning continuous non-linear mappings. For more than two or three inputs and for more than a few thousand dat-apoints the computational expense of pre... | [
548,
683,
906,
2428,
2430,
2658
] | Train |
1,861 | 6 | Title: A Six-Point Condition for Ordinal Matrices keywords: additive, algorithm, evolution, ordinal, phylogeny
Abstract: Ordinal assertions in an evolutionary context are of the form "species s is more similar to species x than to species y" and can be deduced from a distance matrix M of interspecies dissimilarities... | [
1853
] | Train |
1,862 | 6 | Title: Continuous-valued Xof-N Attributes Versus Nominal Xof-N Attributes for Constructive Induction: A Case Study
Abstract: An Xof-N is a set containing one or more attribute-value pairs. For a given instance, its value corresponds to the number of its attribute-value pairs that are true. In this paper, we explore t... | [
1595,
1644,
1863,
1964,
2675
] | Test |
1,863 | 6 | Title: Effects of Different Types of New Attribute on Constructive Induction
Abstract: This paper studies the effects on decision tree learning of constructing four types of attribute (conjunctive, disjunctive, Mof-N, and Xof-N representations). To reduce effects of other factors such as tree learning methods, new at... | [
1595,
1644,
1862,
1964
] | Test |
1,864 | 0 | Title: An Investigation of Marker-Passing Algorithms for Analogue Retrieval
Abstract: If analogy and case-based reasoning systems are to scale up to very large case bases, it is important to analyze the various methods used for retrieving analogues to identify the features of the problem for which they are appropriat... | [
1854,
1855,
2122,
2276
] | Train |
1,865 | 2 | Title: DNA Sequence Classification Using Compression-Based Induction
Abstract: DIMACS Technical Report 95-04 April 1995 | [
2107
] | Train |
1,866 | 2 | Title: A Model of Rapid Memory Formation in the Hippocampal System
Abstract: Our ability to remember events and situations in our daily life demonstrates our ability to rapidly acquire new memories. There is a broad consensus that the hippocampal system (HS) plays a critical role in the formation and retrieval of suc... | [
2272
] | Train |
1,867 | 2 | Title: A comparison of neural net and conventional techniques for lighting control
Abstract: We compare two techniques for lighting control in an actual room equipped with seven banks of lights and photoresistors to detect the lighting level at four sensing points. Each bank of lights can be independently set to one ... | [
1718,
1754
] | Train |
1,868 | 3 | Title: Convergence in Norm for Alternating Expectation-Maximization (EM) Type Algorithms 1
Abstract: We provide a sufficient condition for convergence of a general class of alternating estimation-maximization (EM) type continuous-parameter estimation algorithms with respect to a given norm. This class includes EM, pe... | [
2421
] | Test |
1,869 | 2 | Title: Refining PID Controllers using Neural Networks
Abstract: The Kbann approach uses neural networks to refine knowledge that can be written in the form of simple propositional rules. We extend this idea further by presenting the Manncon algorithm by which the mathematical equations governing a PID controller dete... | [
1754,
2409
] | Train |
1,870 | 3 | Title: Von Mises type statistics for single site updated local interaction random fields
Abstract: Random field models in image analysis and spatial statistics usually have local interactions. They can be simulated by Markov chains which update a single site at a time. The updating rules typically condition on only a... | [
1713,
2362
] | Validation |
1,871 | 2 | Title: 3D Object Recognition Using Unsupervised Feature Extraction
Abstract: Intrator (1990) proposed a feature extraction method that is related to recent statistical theory (Huber, 1985; Friedman, 1987), and is based on a biologically motivated model of neuronal plasticity (Bienenstock et al., 1982). This method ha... | [
359,
2499
] | Test |
1,872 | 1 | Title: Modeling Building-Block Interdependency Dynamical and Evolutionary Machine Organization Group
Abstract: The Building-Block Hypothesis appeals to the notion of problem decomposition and the assembly of solutions from sub-solutions. Accordingly, there have been many varieties of GA test problems with a structur... | [
163,
1257,
1696,
1771
] | Train |
1,873 | 2 | Title: Achieving Super Computer Performance with a DSP Array Processor
Abstract: The MUSIC system (MUlti Signal processor system with Intelligent Communication) is a parallel distributed memory architecture based on digital signal processors (DSP). A system with 60 processor elements is operational. It has a peak per... | [
1998
] | Validation |
1,874 | 2 | Title: DYNAMICAL BEHAVIOR OF ARTIFICIAL NEURAL NETWORKS WITH RANDOM WEIGHTS
Abstract: In this paper we report a Monte Carlo study of the dynamics of large untrained, feedforward, neural networks with randomly chosen weights and feedback. The analysis consists of looking at the percent of the systems that exhibit chao... | [
1920
] | Validation |
1,875 | 6 | Title: On the Effect of Analog Noise in Discrete-Time Analog Computations
Abstract: We introduce a model for analog computation with discrete time in the presence of analog noise that is flexible enough to cover the most important concrete cases, such as noisy analog neural nets and networks of spiking neurons. This ... | [
407,
1891,
2439,
2553
] | Validation |
1,876 | 3 | Title: An Improved Model for Spatially Correlated Binary Responses
Abstract: In this paper we extend the basic autologistic model to include covariates and an indication of sampling effort. The model is applied to sampled data instead of the traditional use for image analysis where complete data are available. We ado... | [
2634
] | Train |
1,877 | 0 | Title: Learning High Utility Rules by Incorporating Search Control Guidance Committee
Abstract: In this paper we extend the basic autologistic model to include covariates and an indication of sampling effort. The model is applied to sampled data instead of the traditional use for image analysis where complete data a... | [
251,
414,
578,
717,
2215
] | Test |
1,878 | 1 | Title: Evolving Deterministic Finite Automata Using Cellular Encoding programming and cellular encoding. Programs are evolved that
Abstract: This paper presents a method for the initial singlestate zygote. The results evolution of deterministic finite | [
2571,
2624
] | Train |
1,879 | 2 | Title: Rochester Connectionist Simulator
Abstract: Specifying, constructing and simulating structured connectionist networks requires significant programming effort. System tools can greatly reduce the effort required, and by providing a conceptual structure within which to work, make large and complex network simula... | [
763,
1760,
2355
] | Test |
1,880 | 1 | Title: On the relationship between distributed group-behaviour and the behavioural complexity of individuals [Wilson Sober 1994])
Abstract: | [
2302
] | Train |
1,881 | 5 | Title: Integrity Constraints in ILP using a Monte Carlo approach
Abstract: Many state-of-the-art ILP systems require large numbers of negative examples to avoid overgeneralization. This is a considerable disadvantage for many ILP applications, namely indu ctive program synthesis where relativelly small and sparse exa... | [
344,
2449,
2450
] | Train |
1,882 | 0 | Title: Symposium Title: Tutorial Discourse What Makes Human Explanations Effective?
Abstract: Many state-of-the-art ILP systems require large numbers of negative examples to avoid overgeneralization. This is a considerable disadvantage for many ILP applications, namely indu ctive program synthesis where relativelly s... | [
1989
] | Train |
1,883 | 1 | Title: A Trade Network Game With Endogenous Partner Selection 1
Abstract: This paper develops an evolutionary trade network game (TNG) that combines evolutionary game play with endogenous partner selection. Successive generations of resource-constrained buyers and sellers choose and refuse trade partners on the basis... | [
2177
] | Test |
1,884 | 2 | Title: Using Neural Networks to Identify Jets
Abstract: A neural network method for identifying the ancestor of a hadron jet is presented. The idea is to find an efficient mapping between certain observed hadronic kinematical variables and the quark/gluon identity. This is done with a neuronic expansion in terms of a... | [
745,
1885,
1886,
1902
] | Train |
1,885 | 2 | Title: LU TP 90-3 Finding Gluon Jets with a Neural Trigger
Abstract: Using a neural network classifier we are able to separate gluon from quark jets originating from Monte Carlo generated e + e events with 85 90% accuracy. PACS numbers: 13.65.+i, 12.38Qk, 13.87.Fh | [
745,
1884,
1886,
1902
] | Train |
1,886 | 2 | Title: LU TP 91-4 Self-organizing Networks for Extracting Jet Features
Abstract: Self-organizing neural networks are briefly reviewed and compared with supervised learning algorithms like back-propagation. The power of self-organization networks is in their capability of displaying typical features in a transparent m... | [
745,
1884,
1885,
1902
] | Validation |
1,887 | 2 | Title: LU TP 93-13 On Langevin Updating in Multilayer Perceptrons
Abstract: The Langevin updating rule, in which noise is added to the weights during learning, is presented and shown to improve learning on problems with initially ill-conditioned Hessians. This is particularly important for multilayer perceptrons with... | [
1902,
2258
] | Validation |
1,888 | 6 | Title: Approximating Hyper-Rectangles: Learning and Pseudo-random Sets
Abstract: The PAC learning of rectangles has been studied because they have been found experimentally to yield excellent hypotheses for several applied learning problems. Also, pseudorandom sets for rectangles have been actively studied recently b... | [
109,
507,
2427
] | Train |
1,889 | 2 | Title: The Functional Transfer of Knowledge for Coronary Artery Disease Diagnosis
Abstract: A distinction between two forms of task knowledge transfer, representational and functional, is reviewed followed by a discussion of MTL, a modified version of the multiple task learning (MTL) neural network method of function... | [
562,
730,
2586,
2648
] | Test |
1,890 | 1 | Title: Genetic Algorithms for Adaptive Planning of Path and Trajectory of a Mobile Robot in 2D Terrains
Abstract: This paper proposes genetic algorithms (GAs) for path planning and trajectory planning of an autonomous mobile robot. Our GA-based approach has an advantage of adaptivity such that the GAs work even if an... | [
163,
1060,
2039
] | Validation |
1,891 | 2 | Title: Vapnik-Chervonenkis Dimension of Recurrent Neural Networks
Abstract: Most of the work on the Vapnik-Chervonenkis dimension of neural networks has been focused on feedforward networks. However, recurrent networks are also widely used in learning applications, in particular when time is a relevant parameter. Thi... | [
58,
200,
206,
411,
1149,
1774,
1875
] | Validation |
1,892 | 0 | Title: Abstraction and Decomposition in Hillclimbing Design Optimization
Abstract: The performance of hillclimbing design optimization can be improved by abstraction and decomposition of the design space. Methods for automatically finding and exploiting such abstractions and decompositions are presented in this paper... | [
2131
] | Validation |
1,893 | 2 | Title: Learning NonLinearly Separable Boolean Functions With Linear Threshold Unit Trees and Madaline-Style Networks
Abstract: This paper investigates an algorithm for the construction of decisions trees comprised of linear threshold units and also presents a novel algorithm for the learning of non-linearly separable... | [
102,
1895,
1908
] | Train |
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