node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
1,594 | 1 | Title: An Evolutionary Approach to Vector Quantizer Design
Abstract: Vector quantization is a lossy coding technique for encoding a set of vectors from different sources such as image and speech. The design of vector quantizers that yields the lowest distortion is one of the most challenging problems in the field of ... | [
163,
1136
] | Train |
1,595 | 6 | Title: ID2-of-3: Constructive Induction of M of-N Concepts for Discriminators in Decision Trees
Abstract: We discuss an approach to constructing composite features during the induction of decision trees. The composite features correspond to m-of-n concepts. There are three goals of this research. First, we explore a ... | [
151,
836,
1301,
1576,
1657,
1776,
1824,
1862,
1863,
1964,
2346,
2675
] | Train |
1,596 | 5 | Title: First Order Regression
Abstract: We present a new approach, called First Order Regression (FOR), to handling numerical information in Inductive Logic Programming (ILP). FOR is a combination of ILP and numerical regression. First-order logic descriptions are induced to carve out those subspaces that are amenabl... | [
314,
348,
1244
] | Test |
1,597 | 0 | Title: an Opportunistic Enterprise
Abstract: Tech Report GIT-COGSCI-97/04 Abstract This paper identifies goal handling processes that begin to account for the kind of processes involved in invention. We identify new kinds of goals with special properties and mechanisms for processing such goals, as well as means of i... | [
486,
1138,
1148,
1534
] | Train |
1,598 | 1 | Title: Mutation Rates as Adaptations
Abstract: In order to better understand life, it is helpful to look beyond the envelop of life as we know it. A simple model of coevolution was implemented with the addition of a gene for the mutation rate of the individual. This allowed the mutation rate itself to evolve in a lin... | [
780,
1139,
1572
] | Train |
1,599 | 4 | Title: Finding Promising Exploration Regions by Weighting Expected Navigation Costs continuous environments, some first-order approximations to
Abstract: In many learning tasks, data-query is neither free nor of constant cost. Often the cost of a query depends on the distance from the current location in state space to... | [
671,
1697
] | Train |
1,600 | 2 | Title: First-Order vs. Second-Order Single Layer Recurrent Neural Networks
Abstract: We examine the representational capabilities of first-order and second-order Single Layer Recurrent Neural Networks (SLRNNs) with hard-limiting neurons. We show that a second-order SLRNN is strictly more powerful than a first-order S... | [
411,
946,
1293
] | Validation |
1,601 | 2 | Title: Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models
Abstract: Learning the past tense of English verbs | a seemingly minor aspect of language acquisition | has generated heated debates since 1986, and has become a landmark task for testing the adequacy of cognitiv... | [
224,
1155,
1428,
1429,
1644,
2423
] | Train |
1,602 | 3 | Title: Defining Explanation in Probabilistic Systems
Abstract: As probabilistic systems gain popularity and are coming into wider use, the need for a mechanism that explains the system's findings and recommendations becomes more critical. The system will also need a mechanism for ordering competing explanations. We e... | [
339,
971,
1326,
1549
] | Train |
1,603 | 1 | Title: Evolving Complex Structures via Co- operative Coevolution
Abstract: A cooperative coevolutionary approach to learning complex structures is presented which, although preliminary in nature, appears to have a number of advantages over non-coevolutionary approaches. The cooperative coevolutionary approach encoura... | [
1114,
1117,
2089
] | Train |
1,604 | 2 | Title: Analytic Comparison of Nonlinear H 1 -Norm Bounding Techniques for Low Order Systems with Saturation
Abstract: A cooperative coevolutionary approach to learning complex structures is presented which, although preliminary in nature, appears to have a number of advantages over non-coevolutionary approaches. The ... | [
1272,
1281,
1451
] | Train |
1,605 | 6 | Title: Learning from the Environment by Experimentation: The Need for Few and Informative Examples
Abstract: An intelligent system must be able to adapt and learn to correct and update its model of the environment incrementally and deliberately. In complex environments that have many parameters and where interactions... | [
1491
] | Test |
1,606 | 2 | Title: Pruning Recurrent Neural Networks for Improved Generalization Performance
Abstract: Determining the architecture of a neural network is an important issue for any learning task. For recurrent neural networks no general methods exist that permit the estimation of the number of layers of hidden neurons, the size... | [
28,
409,
826,
1293,
2381
] | Train |
1,607 | 6 | Title: Characterizing the generalization performance of model selection strategies
Abstract: We investigate the structure of model selection problems via the bias/variance decomposition. In particular, we characterize the essential aspects of a model selection task by the bias and variance profiles it generates over ... | [
848,
1053,
1223,
1335
] | Validation |
1,608 | 3 | Title: Combining estimates in regression and classification
Abstract: We consider the problem of how to combine a collection of general regression fit vectors in order to obtain a better predictive model. The individual fits may be from subset linear regression, ridge regression, or something more complex like a neur... | [
431,
949,
987,
1220,
1512,
2225
] | Test |
1,609 | 5 | Title: Prognosing the femoral neck fracture recovery with machine learning
Abstract: We compare the performance and explanation abilities of several machine learning algorithms in the problem of predicting the femoral neck fracture recovery. Among different algorithms, the semi naive Bayesian classifier and Assistant... | [
1569
] | Validation |
1,610 | 2 | Title: Using Fourier-Neural Recurrent Networks to Fit Sequential Input/Output Data
Abstract: This paper suggests the use of Fourier-type activation functions in fully recurrent neural networks. The main theoretical advantage is that, in principle, the problem of recovering internal coefficients from input/output data... | [
1028,
1037
] | Train |
1,611 | 1 | Title: Island Model Genetic Algorithms and Linearly Separable Problems
Abstract: Parallel Genetic Algorithms have often been reported to yield better performance than Genetic Algorithms which use a single large panmictic population. In the case of the Island Model Genetic Algorithm, it has been informally argued that... | [
100,
163,
1153,
1379,
1380
] | Train |
1,612 | 2 | Title: Bootstrapping with Noise: An Effective Regularization Technique
Abstract: Bootstrap samples with noise are shown to be an effective smoothness and capacity control technique for training feed-forward networks and for other statistical methods such as generalized additive models. It is shown that noisy bootstra... | [
1517
] | Train |
1,613 | 3 | Title: Priors and Component Structures in Autoregressive Time Series Models
Abstract: New approaches to prior specification and structuring in autoregressive time series models are introduced and developed. We focus on defining classes of prior distributions for parameters and latent variables related to latent compo... | [
99,
784,
1162,
1614,
1619
] | Validation |
1,614 | 3 | Title: Bayesian Inference on Periodicities and Component Spectral Structure in Time Series
Abstract: Summary We detail and illustrate time series analysis and spectral inference in autoregressive models with a focus on the underlying latent structure and time series decompositions. A novel class of priors on paramete... | [
1613,
1619
] | Validation |
1,615 | 2 | Title: A Provably Convergent Dynamic Training Method for Multilayer Perceptron Networks
Abstract: This paper presents a new method for training multilayer perceptron networks called DMP1 (Dynamic Multilayer Perceptron 1). The method is based upon a divide and conquer approach which builds networks in the form of bina... | [
809,
1229,
1639
] | Train |
1,616 | 4 | Title: NeuroDraughts: the role of representation, search, training regime and architecture in a TD draughts player
Abstract: NeuroDraughts is a draughts playing program similar in approach to NeuroGammon and NeuroChess [Tesauro, 1992, Thrun, 1995]. It uses an artificial neural network trained by the method of tempora... | [
523,
565,
882
] | Validation |
1,617 | 0 | Title: Knowledge Discovery in International Conflict Databases
Abstract: Artificial Intelligence is heavily supported by military institutions, while practically no effort goes into the investigation of possible contributions of AI to the avoidance and termination of crises and wars. This paper makes a first step int... | [
236,
430,
1107
] | Test |
1,618 | 6 | Title: Selection of Relevant Features and Examples in Machine Learning
Abstract: In this survey, we review work in machine learning on methods for handling data sets containing large amounts of irrelevant information. We focus on two key issues: the problem of selecting relevant features, and the problem of selecting... | [
1112,
1220,
2343
] | Validation |
1,619 | 3 | Title: Exploratory Modelling of Multiple Non-Stationary Time Series: Latent Process Structure and Decompositions
Abstract: We describe and illustrate Bayesian approaches to modelling and analysis of multiple non-stationary time series. This begins with uni-variate models for collections of related time series assumed... | [
99,
1613,
1614,
1722,
1723
] | Test |
1,620 | 5 | Title: Efficient -Subsumption based on Graph Algorithms
Abstract: The -subsumption problem is crucial to the efficiency of ILP learning systems. We discuss two -subsumption algorithms based on strategies for preselecting suitable matching literals. The class of clauses, for which subsumption becomes polynomial, is a ... | [
1177,
1180
] | Train |
1,621 | 0 | Title: Evaluating the Effectiveness of Derivation Replay in Partial-order vs State-space Planning
Abstract: Case-based planning involves storing individual instances of problem-solving episodes and using them to tackle new planning problems. This paper is concerned with derivation replay, which is the main component ... | [
300,
594,
752,
824,
1194,
1448
] | Train |
1,622 | 5 | Title: Stochastic Propositionalization of Non-Determinate Background Knowledge
Abstract: It is a well-known fact that propositional learning algorithms require "good" features to perform well in practice. So a major step in data engineering for inductive learning is the construction of good features by domain experts... | [
344,
1312,
1322,
1428,
1578
] | Validation |
1,623 | 2 | Title: A Neural Network Model for the Gold Market
Abstract: A neural network trend predictor for the gold bullion market is presented. A simple recurrent neural network was trained to recognize turning points in the gold market based on a to-date history of ten market indices. The network was tested on data that was ... | [
1313
] | Validation |
1,624 | 3 | Title: Causal Discovery via MML
Abstract: Automating the learning of causal models from sample data is a key step toward incorporating machine learning in the automation of decision-making and reasoning under uncertainty. This paper presents a Bayesian approach to the discovery of causal models, using a Minimum Messa... | [
1550
] | Validation |
1,625 | 4 | Title: Reinforcement Learning by Probability Matching
Abstract: We present a new algorithm for associative reinforcement learning. The algorithm is based upon the idea of matching a network's output probability with a probability distribution derived from the environment's reward signal. This Probability Matching alg... | [
1580
] | Train |
1,626 | 0 | Title: A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms
Abstract: Many lazy learning algorithms are derivatives of the k-nearest neighbor (k-NN) classifier, which uses a distance function to generate predictions from stored instances. Several studies have shown th... | [
1164,
1407,
1584,
1698,
1735
] | Train |
1,627 | 5 | Title: Inductive Learning of Characteristic Concept Descriptions from Small Sets of Classified Examples
Abstract: This paper presents a novel idea to the problem of learning concept descriptions from examples. Whereas most existing approaches rely on a large number of classified examples, the approach presented in th... | [
344,
479,
1177
] | Train |
1,628 | 1 | Title: Local Selection
Abstract: Local selection (LS) is a very simple selection scheme in evolutionary algorithms. Individual fitnesses are compared to a fixed threshold, rather than to each other, to decide who gets to reproduce. LS, coupled with fitness functions stemming from the consumption of shared environment... | [
1063,
1175
] | Train |
1,629 | 2 | Title: Regional Stability of an ERS/JERS-1 Classifer
Abstract: The potential of combined ERS/JERS-1 SAR images for land cover classification was demonstrated for the Raco test site (Michigan) in recent papers and articles. Our goal is to develop a classification algorithm which is stable in terms of applicability in ... | [
796
] | Validation |
1,630 | 2 | Title: Averaging and Data Snooping
Abstract: Presenting and Analyzing the Results of AI Experiments: Data Averaging and Data Snooping, Proceedings of the Fourteenth National Conference on Artificial Intelligence, AAAI-97, AAAI Press, Menlo Park, California, pp. 362367, 1997. Copyright AAAI. Presenting and Analyzing t... | [
1150,
1195,
1203
] | Validation |
1,631 | 1 | Title: A Survey of Intron Research in Genetics
Abstract: A brief survey of biological research on non-coding DNA is presented here. There has been growing interest in the effects of non-coding segments in evolutionary algorithms (EAs). To better understand and conduct research on non-coding segments and EAs, it is im... | [
934,
2330,
2407,
2598,
2604
] | Validation |
1,632 | 4 | Title: Learning Team Strategies With Multiple Policy-Sharing Agents: A Soccer Case Study
Abstract: We use simulated soccer to study multiagent learning. Each team's players (agents) share action set and policy but may behave differently due to position-dependent inputs. All agents making up a team are rewarded or pun... | [
68,
471,
1687
] | Train |
1,633 | 2 | Title: Changing Supply Functions in Input/State Stable Systems
Abstract: We consider the problem of characterizing possible supply functions for a given dissipative nonlinear system, and provide a result that allows some freedom in the modification of such functions. | [
1471
] | Train |
1,634 | 2 | Title: Combining Linear Discriminant Functions with Neural Networks for Supervised Learning
Abstract: A novel supervised learning method is presented by combining linear discriminant functions with neural networks. The proposed method results in a tree-structured hybrid architecture. Due to constructive learning, the... | [
74,
1252
] | Test |
1,635 | 0 | Title: Redesigning control knowledge of knowledge-based systems: machine learning meets knowledge engineering
Abstract: Machine learning and knowledge engineering have always been strongly related, but the introduction of new representations in knowledge engineering has created a gap between them. This paper describe... | [
1214,
1706
] | Train |
1,636 | 0 | Title: Context-Sensitive Feature Selection for Lazy Learners
Abstract: | [
245,
928,
983,
1073,
1684,
2074
] | Validation |
1,637 | 2 | Title: The Effective Size of a Neural Network: A Principal Component Approach
Abstract: Often when learning from data, one attaches a penalty term to a standard error term in an attempt to prefer simple models and prevent overfitting. Current penalty terms for neural networks, however, often do not take into account ... | [
157,
430,
1562
] | Validation |
1,638 | 1 | Title: Walsh Functions and Predicting Problem Complexity
Abstract: | [
1441
] | Validation |
1,639 | 2 | Title: The Effect of Decision Surface Fitness on Dynamic Multilayer Perceptron Networks (DMP1)
Abstract: The DMP1 (Dynamic Multilayer Perceptron 1) network training method is based upon a divide and conquer approach which builds networks in the form of binary trees, dynamically allocating nodes and layers as needed. ... | [
809,
1615
] | Train |
1,640 | 0 | Title: KRITIK: AN EARLY CASE-BASED DESIGN SYSTEM
Abstract: In the late 1980s, we developed one of the early case-based design systems called Kritik. Kritik autonomously generated preliminary (conceptual, qualitative) designs for physical devices by retrieving and adapting past designs stored in its case memory. Each ... | [
540,
603,
1121,
1345,
1355,
2706
] | Test |
1,641 | 3 | Title: Learning Bayesian Networks from Incomplete Data
Abstract: Much of the current research in learning Bayesian Networks fails to effectively deal with missing data. Most of the methods assume that the data is complete, or make the data complete using fairly ad-hoc methods; other methods do deal with missing data ... | [
71,
558,
1086
] | Test |
1,642 | 0 | Title: CHIRON: Planning in an Open-Textured Domain
Abstract: Much of the current research in learning Bayesian Networks fails to effectively deal with missing data. Most of the methods assume that the data is complete, or make the data complete using fairly ad-hoc methods; other methods do deal with missing data but ... | [
313,
986,
1377,
1475
] | Train |
1,643 | 4 | Title: Learning to coordinate without sharing information
Abstract: Researchers in the field of Distributed Artificial Intelligence (DAI) have been developing efficient mechanisms to coordinate the activities of multiple autonomous agents. The need for coordination arises because agents have to share resources and ex... | [
566,
649,
773,
868,
1189,
1649
] | Train |
1,644 | 2 | Title: A Comparative Study of ID3 and Backpropagation for English Text-to-Speech Mapping
Abstract: The performance of the error backpropagation (BP) and ID3 learning algorithms was compared on the task of mapping English text to phonemes and stresses. Under the distributed output code developed by Sejnowski and Rosen... | [
318,
322,
378,
462,
701,
822,
986,
1256,
1290,
1328,
1601,
1732,
1862,
1863,
1964,
2364,
2409,
2423,
2484,
2614,
2616
] | Train |
1,645 | 2 | Title: Acquiring the mapping from meaning to sounds
Abstract: 1 We thank Steen Ladegaard Knudsen for his assistance in programming, analysis and running of simulations, Scott Baden for his assistance in vectorizing our code for the Cray Y-MP, the Division of Engineering Block Grant for time on the Cray at the San Die... | [
204,
477,
797
] | Test |
1,646 | 1 | Title: Generation Gaps Revisited
Abstract: There has been a lot of recent interest in so-called "steady state" genetic algorithms (GAs) which, among other things, replace only a few individuals (typically 1 or 2) each generation from a fixed size population of size N. Understanding the advantages and/or disadvantages... | [
145,
943
] | Train |
1,647 | 6 | Title: Recognition and Exploitation of Contextual Clues via Incremental Meta-Learning (Extended Version)
Abstract: Daily experience shows that in the real world, the meaning of many concepts heavily depends on some implicit context, and changes in that context can cause more or less radical changes in the concepts. I... | [
1684,
1908,
2074,
2586,
2615
] | Train |
1,648 | 0 | Title: Creative Design: Reasoning and Understanding
Abstract: This paper investigates memory issues that influence long- term creative problem solving and design activity, taking a case-based reasoning perspective. Our exploration is based on a well-documented example: the invention of the telephone by Alexander Grah... | [
1355
] | Train |
1,649 | 4 | Title: Multi-Agent Reinforcement Learning: Independent vs. Cooperative Agents
Abstract: Intelligent human agents exist in a cooperative social environment that facilitates learning. They learn not only by trial-and-error, but also through cooperation by sharing instantaneous information, episodic experience, and lear... | [
148,
691,
868,
1213,
1228,
1557,
1643,
1687
] | Train |
1,650 | 1 | Title: Genetic Algorithms For Vertex Splitting in DAGs 1
Abstract: 1 This paper has been submitted to the 5th International Conference on Genetic Algorithms 2 electronic mail address: matze@cs.umr.edu 3 electronic mail address: ercal@cs.umr.edu | [
163,
1466
] | Train |
1,651 | 5 | Title: An application of ILP in a musical database: learning to compose the two-voice counterpoint
Abstract: We describe SFOIL, a descendant of FOIL that uses the advanced stochastic search heuristic, and its application in learning to compose the two-voice counterpoint. The application required learning a 4-ary rela... | [
877,
1010,
1061,
1578
] | Train |
1,652 | 2 | Title: A Theory of Visual Relative Motion Perception: Grouping, Binding, and Gestalt Organization
Abstract: The human visual system is more sensitive to the relative motion of objects than to their absolute motion. An understanding of motion perception requires an understanding of how neural circuits can group moving... | [
1659
] | Train |
1,653 | 0 | Title: Problem Solving for Redesign
Abstract: A knowledge-level analysis of complex tasks like diagnosis and design can give us a better understanding of these tasks in terms of the goals they aim to achieve and the different ways to achieve these goals. In this paper we present a knowledge-level analysis of redesign... | [
1385
] | Test |
1,654 | 3 | Title: Hyperparameter estimation in Dirichlet process mixture models
Abstract: In Bayesian density estimation and prediction using Dirichlet process mixtures of standard, exponential family distributions, the precision or total mass parameter of the mixing Dirichlet process is a critical hyperparame-ter that strongly... | [
852,
855,
1338
] | Train |
1,655 | 2 | Title: Strategies for the Parallel Training of Simple Recurrent Neural Networks
Abstract: In Bayesian density estimation and prediction using Dirichlet process mixtures of standard, exponential family distributions, the precision or total mass parameter of the mixing Dirichlet process is a critical hyperparame-ter th... | [
1313
] | Train |
1,656 | 2 | Title: Unsupervised Neural Network Learning Procedures For Feature Extraction and Classification
Abstract: Technical report CNS-TR-95-1 Center for Neural Systems McMaster University | [
527,
731,
1710,
1822,
2357
] | Train |
1,657 | 2 | Title: Using Neural Networks to Automatically Refine Expert System Knowledge Bases: Experiments in the NYNEX MAX Domain
Abstract: In this paper we describe our study of applying knowledge-based neural networks to the problem of diagnosing faults in local telephone loops. Currently, NYNEX uses an expert system called ... | [
1307,
1422,
1462,
1595
] | Train |
1,658 | 6 | Title: Learning One-Dimensional Geometric Patterns Under One-Sided Random Misclassification Noise
Abstract: In this paper we describe our study of applying knowledge-based neural networks to the problem of diagnosing faults in local telephone loops. Currently, NYNEX uses an expert system called MAX to aid human exper... | [
884
] | Validation |
1,659 | 2 | Title: In Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections
Abstract: Human vision systems integrate information nonlocally, across long spatial ranges. For example, a moving stimulus appears smeared when viewed briefly (30 ms), yet sharp when viewed for a longer exposure (100 ms) ... | [
1093,
1094,
1652
] | Validation |
1,660 | 3 | Title: Explaining "Explaining Away"
Abstract: Explaining away is a common pattern of reasoning in which the confirmation of one cause of an observed or believed event reduces the need to invoke alternative causes. The opposite of explaining away also can occur, in which the confirmation of one cause increases belief ... | [
952,
1083
] | Test |
1,661 | 6 | Title: Simulating Access to Hidden Information while Learning
Abstract: We introduce a new technique which enables a learner without access to hidden information to learn nearly as well as a learner with access to hidden information. We apply our technique to solve an open problem of Maass and Turan [18], showing tha... | [
109,
453,
791,
1358,
1469
] | Train |
1,662 | 1 | Title: Evolution of Homing Navigation in a Real Mobile Robot
Abstract: In this paper we describe the evolution of a discrete-time recurrent neural network to control a real mobile robot. In all our experiments the evolutionary procedure is carried out entirely on the physical robot without human intervention. We show... | [
1036
] | Train |
1,663 | 1 | Title: Evolution of the Topology and the Weights of Neural Networks using Genetic Programming with a
Abstract: Genetic programming is a methodology for program development, consisting of a special form of genetic algorithm capable of handling parse trees representing programs, that has been successfully applied to a va... | [
1266,
1756,
2504
] | Train |
1,664 | 2 | Title: "What is the best thing to do right now?": getting beyond greedy exploration
Abstract: Genetic programming is a methodology for program development, consisting of a special form of genetic algorithm capable of handling parse trees representing programs, that has been successfully applied to a variety of proble... | [
740,
804,
1559,
1697
] | Train |
1,665 | 0 | Title: Conceptual Analogy: Conceptual clustering for informed and efficient analogical reasoning
Abstract: Conceptual analogy (CA) is a general approach that applies conceptual clustering and concept representations to facilitate the efficient use of past experiences (cases) during analogical reasoning (Borner 1995).... | [
539,
883
] | Train |
1,666 | 3 | Title: Efficient Non-parametric Estimation of Probability Density Functions
Abstract: Accurate and fast estimation of probability density functions is crucial for satisfactory computational performance in many scientific problems. When the type of density is known a priori, then the problem becomes statistical estima... | [
719,
1133
] | Train |
1,667 | 2 | Title: Advances in Neural Information Processing Systems 8 Active Learning in Multilayer Perceptrons
Abstract: We propose an active learning method with hidden-unit reduction, which is devised specially for multilayer perceptrons (MLP). First, we review our active learning method, and point out that many Fisher-infor... | [
740,
1697
] | Test |
1,668 | 2 | Title: Space-Frequency Localized Basis Function Networks for Nonlinear System Estimation and Control
Abstract: Stable neural network control and estimation may be viewed formally as a merging of concepts from nonlinear dynamic systems theory with tools from multivariate approximation theory. This paper extends earlie... | [
611,
1488,
1910,
2378,
2535
] | Validation |
1,669 | 6 | Title: Bias and the Quantification of Stability Bias and the Quantification of Stability Bias and the
Abstract: Research on bias in machine learning algorithms has generally been concerned with the impact of bias on predictive accuracy. We believe that there are other factors that should also play a role in the evaluat... | [
1236
] | Train |
1,670 | 1 | Title: Raising GA Performance by Simultaneous Tuning of Selective Pressure and Recombination Disruptiveness
Abstract: In many Genetic Algorithms applications the objective is to find a (near-)optimal solution using a limited amount of computation. Given these requirements it is difficult to find a good balance betwee... | [
1016,
1218
] | Validation |
1,671 | 6 | Title: From: Computational Learning Theory and Natural Systems, Chapter 18, "Cross-validation and Modal Theories", Cross-Validation and
Abstract: Cross-validation is a frequently used, intuitively pleasing technique for estimating the accuracy of theories learned by machine learning algorithms. During testing of a mach... | [
344,
1512
] | Test |
1,672 | 2 | Title: Learning Controllers for Industrial Robots
Abstract: One of the most significant cost factors in robotics applications is the design and development of real-time robot control software. Control theory helps when linear controllers have to be developed, but it doesn't sufficiently support the generation of non-... | [
294,
696,
807,
899,
903,
1352,
1564
] | Test |
1,673 | 1 | Title: EVOLVING ROBOT BEHAVIORS
Abstract: This paper discusses the use of evolutionary computation to evolve behaviors that exhibit emergent intelligent behavior. Genetic algorithms are used to learn navigation and collision avoidance behaviors for robots. The learning is performed under simulation, and the resulting... | [
910,
964,
965,
966,
1573
] | Train |
1,674 | 0 | Title: Proceedings of CogSci89 Structural Evaluation of Analogies: What Counts?
Abstract: Judgments of similarity and soundness are important aspects of human analogical processing. This paper explores how these judgments can be modeled using SME, a simulation of Gentner's structure-mapping theory. We focus on struct... | [
1123,
1354,
1680
] | Train |
1,675 | 1 | Title: A Study of Genetic Algorithms to Find Approximate Solutions to Hard 3CNF Problems
Abstract: Genetic algorithms have been used to solve hard optimization problems ranging from the Travelling Salesman problem to the Quadratic Assignment problem. We show that the Simple Genetic Algorithm can be used to solve an o... | [
163,
1153
] | Train |
1,676 | 2 | Title: TD Learning of Game Evaluation Functions with Hierarchical Neural Architectures
Abstract: Genetic algorithms have been used to solve hard optimization problems ranging from the Travelling Salesman problem to the Quadratic Assignment problem. We show that the Simple Genetic Algorithm can be used to solve an opt... | [
74,
207,
523,
565,
1146
] | Train |
1,677 | 2 | Title: ICSIM: An Object Oriented Simulation Environment for Structured Connectionist Nets. Class Project Report, Physics 250
Abstract: ICSIM is a simulator for structured connectionism under development at ICSI. Structured connectionism is characterized by the need for flexibility, efficiency and support for the desi... | [
1120
] | Train |
1,678 | 6 | Title: Induction of One-Level Decision Trees
Abstract: In recent years, researchers have made considerable progress on the worst-case analysis of inductive learning tasks, but for theoretical results to have impact on practice, they must deal with the average case. In this paper we present an average-case analysis of... | [
378,
861,
1339,
1570
] | Validation |
1,679 | 5 | Title: Machine learning in prognosis of the femoral neck fracture recovery examples, estimating attributes, explanation ability,
Abstract: We compare the performance of several machine learning algorithms in the problem of prognos-tics of the femoral neck fracture recovery: the K-nearest neighbours algorithm, the semi-... | [
627,
1569,
1726
] | Train |
1,680 | 0 | Title: Making SME greedy and pragmatic
Abstract: The Structure-Mapping Engine (SME) has successfully modeled several aspects of human consistent interpretations of an analogy. While useful for theoretical explorations, this aspect of the algorithm is both psychologically implausible and computationally inefficient. (... | [
1123,
1354,
1674
] | Train |
1,681 | 3 | Title: Understanding WaveShrink: Variance and Bias Estimation
Abstract: Research Report | [
1682
] | Train |
1,682 | 3 | Title: WaveShrink: Shrinkage Functions and Thresholds
Abstract: Donoho and Johnstone's WaveShrink procedure has proven valuable for signal de-noising and non-parametric regression. WaveShrink is based on the principle of shrinking wavelet coefficients towards zero to remove noise. WaveShrink has very broad asymptotic... | [
1681
] | Train |
1,683 | 6 | Title: An Algorithm for Active Data Collection for Learning Feasibility Study with Neural Networks.
Abstract: Macquarie University Technical Report No. 95-173C Department of Computing School of MPCE, Macquarie University, New South Wales, Australia | [
740,
1198,
1559,
1697
] | Train |
1,684 | 5 | Title: Context-sensitive attribute estimation in regression
Abstract: One of key issues in both discrete and continuous class prediction and in machine learning in general seems to be the problem of estimating the quality of attributes. Heuristic measures mostly assume independence of attributes so their use is non-o... | [
314,
1182,
1569,
1636,
1647,
1726
] | Test |
1,685 | 1 | Title: Optimization by Means of Genetic Algorithms
Abstract: Genetic Algorithms (GAs) are powerful heuristic search strategies based upon a simple model of organic evolution. The basic working scheme of GAs as developed by Holland [Hol75] is described within this paper in a formal way, and extensions based upon the s... | [
163,
422,
1069,
1455
] | Validation |
1,686 | 5 | Title: Learning with Abduction
Abstract: We investigate how abduction and induction can be integrated into a common learning framework through the notion of Abductive Concept Learning (ACL). ACL is an extension of Inductive Logic Programming (ILP) to the case in which both the background and the target theory are abd... | [
837,
2282,
2426
] | Train |
1,687 | 4 | Title: Markov games as a framework for multi-agent reinforcement learning
Abstract: In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be... | [
54,
148,
523,
773,
870,
898,
1137,
1189,
1228,
1459,
1557,
1632,
1649
] | Train |
1,688 | 1 | Title: Co-Evolving Soccer Softbot Team Coordination with Genetic Programming
Abstract: Genetic Programming is a promising new method for automatically generating functions and algorithms through natural selection. In contrast to other learning methods, Genetic Programming's automatic programming makes it a natural ap... | [
1178,
1228
] | Validation |
1,689 | 1 | Title: Selection for Wandering Behavior in a Small Robot
Abstract: We have evolved artificial neural networks to control the wandering behavior of small robots. The task was to touch as many squares in a grid as possible during a fixed period of time. A number of the simulated robots were embodied in small Lego (Trad... | [
38,
163,
219,
538,
1738
] | Train |
1,690 | 1 | Title: Evolving Behavioral Strategies in Predators and Prey
Abstract: The predator/prey domain is utilized to conduct research in Distributed Artificial Intelligence. Genetic Programming is used to evolve behavioral strategies for the predator agents. To further the utility of the predator strategies, the prey popula... | [
995,
1178,
1736
] | Test |
1,691 | 1 | Title: Evolutionary Algorithms: Some Very Old Strategies for Optimization and Adaptation
Abstract: Genetic Algorithms and Evolution Strategies, the main representatives of a class of algorithms based on the model of natural evolution, are discussed w.r.t. their basic working mechanisms, differences, and application p... | [
163,
422,
793
] | Validation |
1,692 | 6 | Title: Boosting Trees for Cost-Sensitive Classifications
Abstract: This paper explores two boosting techniques for cost-sensitive tree classification in the situation where misclassification costs change very often. Ideally, one would like to have only one induction, and use the induced model for different misclassif... | [
70,
228,
1484
] | Train |
1,693 | 4 | Title: INCREMENTAL SELF-IMPROVEMENT FOR LIFE-TIME MULTI-AGENT REINFORCEMENT LEARNING
Abstract: Previous approaches to multi-agent reinforcement learning are either very limited or heuristic by nature. The main reason is: each agent's or "animat's" environment continually changes because the other learning animats kee... | [
1228
] | Validation |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.