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|---|---|---|---|---|
2,594 | 2 | Title: Can Recurrent Neural Networks Learn Natural Language Grammars? W&Z recurrent neural networks are able to
Abstract: Recurrent neural networks are complex parametric dynamic systems that can exhibit a wide range of different behavior. We consider the task of grammatical inference with recurrent neural networks. Sp... | [
411,
2306
] | Train |
2,595 | 2 | Title: TO IMPROVE FORECASTING
Abstract: Working Paper IS-97-007, Leonard N. Stern School of Business, New York University. In: Journal of Computational Intelligence in Finance 6 (1998) 14-23. (Special Issue on "Improving Generalization of Nonlinear Financial Forecasting Models".) http://www.stern.nyu.edu/~aweigend/Re... | [
1315,
2452,
2562
] | Train |
2,596 | 3 | Title: Regression shrinkage and selection via the lasso
Abstract: We propose a new method for estimation in linear models. The "lasso" minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant. Because of the nature of this constraint it tends to pro... | [
2669,
2680,
2686
] | Train |
2,597 | 0 | Title: Improved Heterogeneous Distance Functions
Abstract: Instance-based learning techniques typically handle continuous and linear input values well, but often do not handle nominal input attributes appropriately. The Value Difference Metric (VDM) was designed to find reasonable distance values between nominal attr... | [
1698,
2256
] | Test |
2,598 | 1 | Title: Duplication of Coding Segments in Genetic Programming
Abstract: Research into the utility of non-coding segments, or introns, in genetic-based encodings has shown that they expedite the evolution of solutions in domains by protecting building blocks against destructive crossover. We consider a genetic programm... | [
854,
956,
1230,
1232,
1631,
2330
] | Train |
2,599 | 2 | Title: Recognizing Handwritten Digit Strings Using Modular Spatio-temporal Connectionist Networks
Abstract: Research into the utility of non-coding segments, or introns, in genetic-based encodings has shown that they expedite the evolution of solutions in domains by protecting building blocks against destructive cros... | [
2162
] | Test |
2,600 | 1 | Title: Evolution of Iteration in Genetic Programming D a v d A The solution to many
Abstract: This paper introduces the new operation of restricted iteration creation that automatically Genetic programming extends Holland's genetic algorithm to the task of automatic programming. Early work on genetic programming demons... | [
163,
523,
1409,
2220
] | Train |
2,601 | 2 | Title: Stability and Chaos in an Inertial Two Neuron System in Statistical Mechanics and Complex Systems
Abstract: Inertia is added to a continuous-time, Hopfield [1], effective neuron system. We explore the effects on the stability of the fixed points of the system. A two neuron system with one or two inertial term... | [
2631
] | Train |
2,602 | 5 | Title: A Method for Partial-Memory Incremental Learning and its Application to Computer Intrusion Detection Machine Learning
Abstract: This paper describes a partial-memory incremental learning method based on the AQ15c inductive learning system. The method maintains a representative set of past training examples that ... | [
2070
] | Train |
2,603 | 2 | Title: Pointer Adaptation and Pruning of Min-Max Fuzzy Inference and Estimation
Abstract: This paper describes a partial-memory incremental learning method based on the AQ15c inductive learning system. The method maintains a representative set of past training examples that are used together with new examples to appr... | [
1756
] | Train |
2,604 | 1 | Title: Empirical studies of the genetic algorithm with non-coding segments
Abstract: The genetic algorithm (GA) is a problem solving method that is modelled after the process of natural selection. We are interested in studying a specific aspect of the GA: the effect of non-coding segments on GA performance. Non-codin... | [
163,
168,
1631,
2330
] | Train |
2,605 | 0 | Title: Case-based Acquisition of User Preferences for Solution Improvement in Ill-Structured Domains
Abstract: 1 We have developed an approach to acquire complicated user optimization criteria and use them to guide | [
951,
986,
1401,
2502
] | Train |
2,606 | 2 | Title: Computational modeling of spatial attention
Abstract: 1 We have developed an approach to acquire complicated user optimization criteria and use them to guide | [
527,
2337,
2459,
2611,
2662
] | Validation |
2,607 | 0 | Title: Concept Learning and Flexible Weighting
Abstract: We previously introduced an exemplar model, named GCM-ISW, that exploits a highly flexible weighting scheme. Our simulations showed that it records faster learning rates and higher asymptotic accuracies on several artificial categorization tasks than models wit... | [
1987,
2074,
2310,
2369
] | Test |
2,608 | 2 | Title: Testing the Generalized Linear Model Null Hypothesis versus `Smooth' Alternatives 1
Abstract: We previously introduced an exemplar model, named GCM-ISW, that exploits a highly flexible weighting scheme. Our simulations showed that it records faster learning rates and higher asymptotic accuracies on several art... | [
519,
2549
] | Train |
2,609 | 5 | Title: ILP with Noise and Fixed Example Size: A Bayesian Approach
Abstract: Current inductive logic programming systems are limited in their handling of noise, as they employ a greedy covering approach to constructing the hypothesis one clause at a time. This approach also causes difficulty in learning recursive pred... | [
344,
2079,
2080
] | Train |
2,610 | 2 | Title: Lending Direction to Neural Networks
Abstract: We present a general formulation for a network of stochastic directional units. This formulation is an extension of the Boltzmann machine in which the units are not binary, but take on values on a cyclic range, between 0 and 2 radians. This measure is appropriate ... | [
2337
] | Train |
2,611 | 2 | Title: The end of the line for a brain-damaged model of unilateral neglect
Abstract: For over a century, it has been known that damage to the right hemisphere of the brain can cause patients to be unaware of the contralesional side of space. This condition, known as unilateral neglect, represents a collection of clin... | [
1763,
2606
] | Train |
2,612 | 2 | Title: Models of Parallel Adaptive Logic
Abstract: This paper overviews a proposed architecture for adaptive parallel logic referred to as ASOCS (Adaptive Self-Organizing Concurrent System). The ASOCS approach is based on an adaptive network composed of many simple computing elements which operate in a parallel async... | [
26,
724,
1903,
2625
] | Test |
2,613 | 1 | Title: Genetic Algorithms for Automated Tuning of Fuzzy Controllers: A Transportation Application
Abstract: We describe the design and tuning of a controller for enforcing compliance with a prescribed velocity profile for a rail-based transportation system. This requires following a trajectory, rather than fixed set-... | [
1756
] | Test |
2,614 | 0 | Title: PRONOUNCING NAMES BY A COMBINATION OF RULE-BASED AND CASE-BASED REASONING
Abstract: We describe the design and tuning of a controller for enforcing compliance with a prescribed velocity profile for a rail-based transportation system. This requires following a trajectory, rather than fixed set-points (as in aut... | [
986,
1644,
2484,
2616
] | Validation |
2,615 | 2 | Title: A Patient-Adaptive Neural Network ECG Patient Monitoring Algorithm
Abstract: The patient-adaptive classifier was compared with a well-established baseline algorithm on six major databases, consisting of over 3 million heartbeats. When trained on an initial 77 records and tested on an additional 382 records, th... | [
1647,
2074,
2084
] | Train |
2,616 | 0 | Title: A comparison of Anapron with seven other name-pronunciation systems
Abstract: This paper presents an experiment comparing a new name-pronunciation system, Anapron, with seven existing systems: three state-of-the-art commercial systems (from Bellcore, Bell Labs, and DEC), two variants of a machine-learning syst... | [
986,
1644,
2484,
2614
] | Train |
2,617 | 5 | Title: Predicting Ordinal Classes in ILP
Abstract: This paper is devoted to the problem of learning to predict ordinal (i.e., ordered discrete) classes in an ILP setting. We start with a relational regression algorithm named SRT (Structural Regression Trees) and study various ways of transforming it into a first-orde... | [
228,
344,
1275,
1428,
2091
] | Validation |
2,618 | 6 | Title: Mistake-Driven Learning in Text Categorization
Abstract: Learning problems in the text processing domain often map the text to a space whose dimensions are the measured features of the text, e.g., its words. Three characteristic properties of this domain are (a) very high dimensionality, (b) both the learned c... | [
453,
1269,
2509
] | Train |
2,619 | 2 | Title: An Efficient Implementation of Sigmoidal Neural Nets in Temporal Coding with Noisy Spiking Neurons
Abstract: We show that networks of relatively realistic mathematical models for biological neurons can in principle simulate arbitrary feedforward sigmoidal neural nets in a way which has previously not been cons... | [
328,
1774,
1968
] | Test |
2,620 | 3 | Title: Monte Carlo Approach to Bayesian Regression Modeling
Abstract: In the framework of a functional response model (i.e. a regression model, or a feedforward neural network) an estimator of a nonlinear response function is constructed from a set of functional units. The parameters defining these functional units a... | [
1972
] | Test |
2,621 | 2 | Title: Information Processing in Primate Retinal Cone Pathways: A Model
Abstract: In the framework of a functional response model (i.e. a regression model, or a feedforward neural network) an estimator of a nonlinear response function is constructed from a set of functional units. The parameters defining these functi... | [
2105
] | Train |
2,622 | 0 | Title: Feature Selection by Means of a Feature Weighting Approach
Abstract: Selecting a set of features which is optimal for a given classification task is one of the central problems in machine learning. We address the problem using the flexible and robust filter technique EUBAFES. EUBAFES is based on a feature weig... | [
2033
] | Train |
2,623 | 6 | Title: Theoretical Models of Learning to Learn Editor:
Abstract: A Machine can only learn if it is biased in some way. Typically the bias is supplied by hand, for example through the choice of an appropriate set of features. However, if the learning machine is embedded within an environment of related tasks, then it... | [
2113
] | Test |
2,624 | 1 | Title: A Comparison between Cellular Encoding and Direct Encoding for Genetic Neural Networks
Abstract: This paper compares the efficiency of two encoding schemes for Artificial Neural Networks optimized by evolutionary algorithms. Direct Encoding encodes the weights for an a priori fixed neural network architecture.... | [
1204,
1878,
1931,
2277,
2317,
2429,
2702
] | Train |
2,625 | 2 | Title: Digital Neural Networks
Abstract: Demands for applications requiring massive parallelism in symbolic environments have given rebirth to research in models labeled as neura l networks. These models are made up of many simple nodes which are highly interconnected such that computation takes place as data flows a... | [
2612
] | Validation |
2,626 | 0 | Title: Focusing Construction and Selection of Abductive Hypotheses
Abstract: Many abductive understanding systems explain novel situations by a chaining process that is neutral to explainer needs beyond generating some plausible explanation for the event being explained. This paper examines the relationship of standa... | [
1843,
2399,
2656
] | Test |
2,627 | 6 | Title: Probability Estimation via Error-Correcting Output Coding
Abstract: Previous research has shown that a technique called error-correcting output coding (ECOC) can dramatically improve the classification accuracy of supervised learning algorithms that learn to classify data points into one of k 2 classes. In thi... | [
2423
] | Train |
2,628 | 4 | Title: Generalizing in TD() learning
Abstract: Previous research has shown that a technique called error-correcting output coding (ECOC) can dramatically improve the classification accuracy of supervised learning algorithms that learn to classify data points into one of k 2 classes. In this paper, we will extend the ... | [
565,
738,
2629
] | Train |
2,629 | 4 | Title: Towards a Reactive Critic
Abstract: In this paper we propose a reactive critic, that is able to respond to changing situations. We will explain why this is usefull in reinforcement learning, where the critic is used to improve the control strategy. We take a problem for which we can derive the solution analyti... | [
565,
738,
2536,
2628
] | Validation |
2,630 | 1 | Title: Simulating Quadratic Dynamical Systems is PSPACE-complete (preliminary version)
Abstract: Quadratic Dynamical Systems (QDS), whose definition extends that of Markov chains, are used to model phenomena in a variety of fields like statistical physics and natural evolution. Such systems also play a role in geneti... | [
1826
] | Train |
2,631 | 2 | Title: Nonlinear Resonance in Neuron Dynamics in Statistical Mechanics and Complex Systems
Abstract: Hubler's technique using aperiodic forces to drive nonlinear oscillators to resonance is analyzed. The oscillators being examined are effective neurons that model Hopfield neural networks. The method is shown to be v... | [
2601
] | Validation |
2,632 | 2 | Title: The Role of Activity in Synaptic Competition at the Neuromuscular Junction
Abstract: An extended version of the dual constraint model of motor end-plate morphogenesis is presented that includes activity dependent and independent competition. It is supported by a wide range of recent neurophysiological evidence... | [
2584
] | Train |
2,633 | 6 | Title: Learning Using Group Representations (Extended Abstract)
Abstract: We consider the problem of learning functions over a fixed distribution. An algorithm by Kushilevitz and Mansour [7] learns any boolean function over f0; 1g n in time polynomial in the L 1 -norm of the Fourier transform of the function. We show... | [
2011,
2182
] | Validation |
2,634 | 3 | Title: Bayesian Model Averaging
Abstract: Standard statistical practice ignores model uncertainty. Data analysts typically select a model from some class of models and then proceed as if the selected model had generated the data. This approach ignores the uncertainty in model selection, leading to over-confident infe... | [
1197,
1876
] | Train |
2,635 | 0 | Title: Utilising Explanation to Assist the Refinement of Knowledge-Based Systems
Abstract: Standard statistical practice ignores model uncertainty. Data analysts typically select a model from some class of models and then proceed as if the selected model had generated the data. This approach ignores the uncertainty i... | [
136,
2231
] | Train |
2,636 | 5 | Title: EMERALD: An Integrated System of Machine Learning and Discovery Programs to Support AI Education and
Abstract: With the rapid expansion of machine learning methods and applications, there is a strong need for computer-based interactive tools that support education in this area. The EMERALD system was developed t... | [
479,
2300
] | Train |
2,637 | 1 | Title: A Computational Environment for Exhaust Nozzle Design
Abstract: The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design new aircraft or to design new nozzles that adapt existing aircraft so they may ... | [
2652
] | Train |
2,638 | 1 | Title: An Evolutionary Heuristic for the Minimum Vertex Cover Problem
Abstract: The Nozzle Design Associate (NDA) is a computational environment for the design of jet engine exhaust nozzles for supersonic aircraft. NDA may be used either to design new aircraft or to design new nozzles that adapt existing aircraft so ... | [
163,
2202
] | Train |
2,639 | 2 | Title: New Modes of Generalization in Perceptual Learning
Abstract: The learning of many visual perceptual tasks, such as motion discrimination, has been shown to be specific to the practiced stimulus, and new stimuli require re-learning from scratch [1-6]. This specificity, found in so many different tasks, supports... | [
2117
] | Train |
2,640 | 5 | Title: Learning Evolving Concepts Using Partial-Memory Approach Machine Learning and Inference Laboratory
Abstract: This paper addresses the problem of learning evolving concepts, that is, concepts whose meaning gradually evolves in time. Solving this problem is important to many applications, for example, building ... | [
2070
] | Train |
2,641 | 1 | Title: Toward Simulated Evolution of Machine-Language Iteration
Abstract: We use a simulated evolution search (genetic programming) for the automatic synthesis of small iterative machine-language programs. For an integer register machine with an addition instruction as its sole arithmetic operator, we show that genet... | [
380,
1745
] | Validation |
2,642 | 2 | Title: Learning to Play Games From Experience: An Application of Artificial Neural Networks and Temporal Difference Learning
Abstract: We use a simulated evolution search (genetic programming) for the automatic synthesis of small iterative machine-language programs. For an integer register machine with an addition in... | [
523,
565,
2368
] | Validation |
2,643 | 1 | Title: GP-Music: An Interactive Genetic Programming System for Music Generation with Automated Fitness Raters
Abstract: Technical Report CSRP-98-13 Abstract In this paper we present the GP-Music System, an interactive system which allows users to evolve short musical sequences using interactive genetic programming, a... | [
2470,
2646
] | Train |
2,644 | 6 | Title: Bayesian Induction of Features in Temporal Domains
Abstract: Most concept induction algorithms process concept instances described in terms of properties that remain constant over time. In temporal domains, instances are best described in terms of properties whose values vary with time. Data engineering is cal... | [
2134
] | Train |
2,645 | 0 | Title: CBR on Semi-structured Documents: The ExperienceBook and the FAllQ Project
Abstract: In this article, we present a case-based approach on flexible query answering systems in two different application areas: The ExperienceBook supports technical diagnosis in the field of system administration. In the FAllQ proj... | [
1854,
2482
] | Train |
2,646 | 1 | Title: Automated Fitness Raters for the GP-Music System
Abstract: | [
2470,
2643
] | Train |
2,647 | 4 | Title: Using Local Trajectory Optimizers To Speed Up Global Optimization In Dynamic Programming
Abstract: Dynamic programming provides a methodology to develop planners and controllers for nonlinear systems. However, general dynamic programming is computationally intractable. We have developed procedures that allow m... | [
2430,
2658
] | Test |
2,648 | 2 | Title: The Task Rehearsal Method of Sequential Learning
Abstract: An hypothesis of functional transfer of task knowledge is presented that requires the development of a measure of task relatedness and a method of sequential learning. The task rehearsal method (TRM) is introduced to address the issues of sequential le... | [
1889
] | Test |
2,649 | 5 | Title: Limits of Control Flow on Parallelism
Abstract: This paper discusses three techniques useful in relaxing the constraints imposed by control flow on parallelism: control dependence analysis, executing multiple flows of control simultaneously, and speculative execution. We evaluate these techniques by using trac... | [
249,
735,
1956,
2106,
2436
] | Validation |
2,650 | 5 | Title: Learning Search-Control Heuristics for Logic Programs: Applications to Speedup Learning and Language Acquisition
Abstract: This paper presents a general framework, learning search-control heuristics for logic programs, which can be used to improve both the efficiency and accuracy of knowledge-based systems exp... | [
204,
2215
] | Test |
2,651 | 6 | Title: Relative Loss Bounds for Multidimensional Regression Problems
Abstract: We study on-line generalized linear regression with multidimensional outputs, i.e., neural networks with multiple output nodes but no hidden nodes. We allow at the final layer transfer functions such as the softmax function that need to co... | [
1062,
2059
] | Train |
2,652 | 0 | Title: Knowledge-Based Re-engineering of Legacy Programs for Robustness in Automated Design
Abstract: Systems for automated design optimization of complex real-world objects can, in principle, be constructed by combining domain-independent numerical routines with existing domain-specific analysis and simulation progr... | [
240,
2308,
2637
] | Train |
2,653 | 6 | Title: On the Sample Complexity of Weakly Learning
Abstract: In this paper, we study the sample complexity of weak learning. That is, we ask how much data must be collected from an unknown distribution in order to extract a small but significant advantage in prediction. We show that it is important to distinguish bet... | [
456,
672,
1363,
2028
] | Train |
2,654 | 3 | Title: On the Sample Complexity of Weakly Learning
Abstract: Convergence Results for the EM Approach to Abstract The Expectation-Maximization (EM) algorithm is an iterative approach to maximum likelihood parameter estimation. Jordan and Jacobs (1993) recently proposed an EM algorithm for the mixture of experts archit... | [
74,
2421
] | Train |
2,655 | 4 | Title: Associative Reinforcement Learning: A Generate and Test Algorithm
Abstract: An agent that must learn to act in the world by trial and error faces the reinforcement learning problem, which is quite different from standard concept learning. Although good algorithms exist for this problem in the general case, the... | [
1975
] | Train |
2,656 | 0 | Title: ADAPtER: an Integrated Diagnostic System Combining Case-Based and Abductive Reasoning
Abstract: The aim of this paper is to describe the ADAPtER system, a diagnostic architecture combining case-based reasoning with abductive reasoning and exploiting the adaptation of the solution of old episodes, in order to f... | [
799,
1699,
2626
] | Train |
2,657 | 6 | Title: Learning Complex Boolean Functions: Algorithms and Applications
Abstract: The most commonly used neural network models are not well suited to direct digital implementations because each node needs to perform a large number of operations between floating point values. Fortunately, the ability to learn from exam... | [
1161,
2423
] | Validation |
2,658 | 0 | Title: Control Systems Magazine, 14, 1, pp.57-71. Robot Juggling: An Implementation of Memory-based Learning
Abstract: This paper explores issues involved in implementing robot learning for a challenging dynamic task, using a case study from robot juggling. We use a memory-based local model - ing approach (locally we... | [
427,
477,
566,
691,
843,
1559,
1860,
2647
] | Train |
2,659 | 1 | Title: Adaptation of Genetic Algorithms for Engineering Design Optimization
Abstract: Genetic algorithms have been extensively used in different domains as a means of doing global optimization in a simple yet reliable manner. However, in some realistic engineering design optimization domains it was observed that a si... | [
163,
743,
2030,
2316
] | Train |
2,660 | 3 | Title: Discovering Structure in Continuous Variables Using Bayesian Networks
Abstract: We study Bayesian networks for continuous variables using nonlinear conditional density estimators. We demonstrate that useful structures can be extracted from a data set in a self-organized way and we present sampling techniques f... | [
558,
577,
1933
] | Validation |
2,661 | 3 | Title: Minimax Risk over l p -Balls for l q -error Key Words. Minimax Decision Theory.
Abstract: Consider estimating the mean vector from data N n (; 2 I) with l q norm loss, q 1, when is known to lie in an n-dimensional l p ball, p 2 (0; 1). For large n, the ratio of minimax linear risk to minimax risk can be arbitrar... | [
1910,
2159,
2242,
2375,
2506
] | Train |
2,662 | 2 | Title: Efficient Visual Search: A Connectionist Solution
Abstract: Searching for objects in scenes is a natural task for people and has been extensively studied by psychologists. In this paper we examine this task from a connectionist perspective. Computational complexity arguments suggest that parallel feed-forward ... | [
527,
1822,
2606
] | Train |
2,663 | 5 | Title: Inverting Implication with Small Training Sets
Abstract: We present an algorithm for inducing recursive clauses using inverse implication (rather than inverse resolution) as the underlying generalization method. Our approach applies to a class of logic programs similar to the class of primitive recursive funct... | [
1781,
2229
] | Train |
2,664 | 1 | Title: Coevolving Communicative Behavior in a Linear Pursuer-Evader Game
Abstract: The pursuer-evader (PE) game is recognized as an important domain in which to study the coevolution of robust adaptive behavior and protean behavior (Miller and Cliff, 1994). Nevertheless, the potential of the game is largely unrealize... | [
189,
415,
712,
2102
] | Train |
2,665 | 0 | Title: Parametric Design Problem Solving
Abstract: The aim of this paper is to understand what is involved in parametric design problem solving. In order to achieve this goal, in this paper i) we identify and detail the conceptual elements defining a parametric design task specification; ii) we illustrate how these e... | [
2395
] | Test |
2,666 | 4 | Title: A Distributed Reinforcement Learning Scheme for Network Routing
Abstract: In this paper we describe a self-adjusting algorithm for packet routing in which a reinforcement learning method is embedded into each node of a network. Only local information is used at each node to keep accurate statistics on which ro... | [
451,
2411,
2453
] | Train |
2,667 | 1 | Title: Biological metaphors and the design of modular artificial neural networks Master's thesis of
Abstract: In this paper we describe a self-adjusting algorithm for packet routing in which a reinforcement learning method is embedded into each node of a network. Only local information is used at each node to keep ac... | [
163,
2295,
2381,
2429,
2504
] | Validation |
2,668 | 5 | Title: Efficient Instruction Scheduling Using Finite State Automata
Abstract: Modern compilers employ sophisticated instruction scheduling techniques to shorten the number of cycles taken to execute the instruction stream. In addition to correctness, the instruction scheduler must also ensure that hardware resources ... | [
2365
] | Train |
2,669 | 3 | Title: A proposal for variable selection in the Cox model
Abstract: We propose a new method for variable selection and estimation in Cox's proportional hazards model. Our proposal minimizes the log partial likelihood subject to the sum of the absolute values of the parameters being bounded by a constant. Because of t... | [
2596
] | Validation |
2,670 | 2 | Title: A proposal for variable selection in the Cox model
Abstract: GMD Report #633 Abstract Many of the current artificial neural network systems have serious limitations, concerning accessibility, flexibility, scaling and reliability. In order to go some way to removing these we suggest a reflective neural network ... | [
253,
489,
1815
] | Train |
2,671 | 2 | Title: Rejection of Incorrect Answers from a Neural Net Classifier
Abstract: Frank Smieja Report number: 1993/2 | [
1815
] | Train |
2,672 | 2 | Title: REINFORCEMENT LEARNING FOR COORDINATED REACTIVE CONTROL
Abstract: The demands of rapid response and the complexity of many environments make it difficult to decompose, tune and coordinate reactive behaviors while ensuring consistency. Reinforcement learning networks can address the tuning problem, but do not a... | [
465,
565,
636,
2409
] | Train |
2,673 | 1 | Title: A genetic prototype learner
Abstract: Supervised classification problems have received considerable attention from the machine learning community. We propose a novel genetic algorithm based prototype learning system, PLEASE, for this class of problems. Given a set of prototypes for each of the possible classes... | [
163,
638,
995,
1224,
2541
] | Test |
2,674 | 2 | Title: Comparing Methods for Refining Certainty-Factor Rule-Bases
Abstract: This paper compares two methods for refining uncertain knowledge bases using propositional certainty-factor rules. The first method, implemented in the Rapture system, employs neural-network training to refine the certainties of existing rule... | [
159,
1352,
2066,
2543
] | Train |
2,675 | 6 | Title: CONSTRUCTING CONJUNCTIVE TESTS FOR DECISION TREES
Abstract: This paper discusses an approach of constructing new attributes based on decision trees and production rules. It can improve the concepts learned in the form of decision trees by simplifying them and improving their predictive accuracy. In addition, t... | [
1256,
1595,
1824,
1862,
1964
] | Test |
2,676 | 2 | Title: Models of perceptual learning in vernier hyperacuity
Abstract: Performance of human subjects in a wide variety of early visual processing tasks improves with practice. HyperBF networks (Poggio and Girosi, 1990) constitute a mathematically well-founded framework for understanding such improvement in performance... | [
611,
1787,
2385
] | Test |
2,677 | 3 | Title: Mining and Model Simplicity: A Case Study in Diagnosis
Abstract: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD), 1996. The official version of this paper has been published by the American Association for Artificial Intelligence (http://www.aaai.org) c fl 1996, Ame... | [
1339,
1582,
1909,
2017,
2338
] | Train |
2,678 | 2 | Title: Egocentric spatial representation in early vision
Abstract: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD), 1996. The official version of this paper has been published by the American Association for Artificial Intelligence (http://www.aaai.org) c fl 1996, American... | [
2477,
2576
] | Validation |
2,679 | 3 | Title: STUDIES OF QUALITY MONITOR TIME SERIES: THE V.A. HOSPITAL SYSTEM build on foundational contributions in
Abstract: This report describes statistical research and development work on hospital quality monitor data sets from the nationwide VA hospital system. The project covers statistical analysis, exploration and ... | [
99,
2578
] | Train |
2,680 | 2 | Title: Least Absolute Shrinkage is Equivalent to Quadratic Penalization
Abstract: Adaptive ridge is a special form of ridge regression, balancing the quadratic penalization on each parameter of the model. This paper shows the equivalence between adaptive ridge and lasso (least absolute shrinkage and selection operato... | [
101,
157,
2596
] | Train |
2,681 | 2 | Title: Regression with Input-dependent Noise: A Gaussian Process Treatment
Abstract: Technical Report NCRG/98/002, available from http://www.ncrg.aston.ac.uk/ To appear in Advances in Neural Information Processing Systems 10 eds. M. I. Jordan, M. J. Kearns and S. A. Solla. Lawrence Erlbaum (1998). Abstract Gaussian p... | [
78,
160,
1857
] | Validation |
2,682 | 3 | Title: Importance Sampling
Abstract: Technical Report No. 9805, Department of Statistics, University of Toronto Abstract. Simulated annealing | moving from a tractable distribution to a distribution of interest via a sequence of intermediate distributions | has traditionally been used as an inexact method of handling... | [
48,
2348
] | Train |
2,683 | 2 | Title: Introduction to Radial Basis Function Networks
Abstract: This document is an introduction to radial basis function (RBF) networks, a type of artificial neural network for application to problems of supervised learning (e.g. regression, classification and time series prediction). It is available in either PostS... | [
427,
668,
687,
2044
] | Train |
2,684 | 2 | Title: INVERSION IN TIME
Abstract: Inversion of multilayer synchronous networks is a method which tries to answer questions like "What kind of input will give a desired output?" or "Is it possible to get a desired output (under special input/output constraints)?". We will describe two methods of inverting a connectio... | [
2523
] | Validation |
2,685 | 6 | Title: Learning under persistent drift
Abstract: In this paper we study learning algorithms for environments which are changing over time. Unlike most previous work, we are interested in the case where the changes might be rapid but their "direction" is relatively constant. We model this type of change by assuming th... | [
2053,
2054
] | Test |
2,686 | 2 | Title: Penalisation multiple adaptative un nouvel algorithme de regression, la penalisation multiple adapta-tive. Cet algorithme represente
Abstract: Chaque parametre du modele est penalise individuellement. Le reglage de ces penalisations se fait automatiquement a partir de la definition d'un hyperparametre de regular... | [
101,
916,
2596
] | Train |
2,687 | 4 | Title: ALECSYS and the AutonoMouse: Learning to Control a Real Robot by Distributed Classifier Systems
Abstract: Chaque parametre du modele est penalise individuellement. Le reglage de ces penalisations se fait automatiquement a partir de la definition d'un hyperparametre de regularisation globale. Cet hyperparametre... | [
636,
764,
2174
] | Train |
2,688 | 1 | Title: An Adverse Interaction between the Crossover Operator and a Restriction on Tree Depth of Crossover
Abstract: The Crossover operator is common to most implementations of Genetic Programming (GP). Another, usually unavoidable, factor is some form of restriction on the size of trees in the GP population. This paper... | [
1784,
1839,
1840,
2216
] | Train |
2,689 | 6 | Title: Expected Mistake Bound Model for On-Line Reinforcement Learning
Abstract: We propose a model of efficient on-line reinforcement learning based on the expected mistake bound framework introduced by Haussler, Littlestone and Warmuth (1987). The measure of performance we use is the expected difference between the... | [
1975,
2209
] | Test |
2,690 | 6 | Title: Robust Trainability of Single Neurons
Abstract: We propose a model of efficient on-line reinforcement learning based on the expected mistake bound framework introduced by Haussler, Littlestone and Warmuth (1987). The measure of performance we use is the expected difference between the total reward received by ... | [
591,
2053
] | Train |
2,691 | 2 | Title: A map of the protein space An automatic hierarchical classification of all protein sequences
Abstract: We investigate the space of all protein sequences. We combine the standard measures of similarity (SW, FASTA, BLAST), to associate with each sequence an exhaustive list of neighboring sequences. These lists i... | [
1751
] | Test |
2,692 | 0 | Title: Multi-Strategy Learning and Theory Revision
Abstract: This paper presents the system WHY, which learns and updates a diagnostic knowledge base using domain knowledge and a set of examples. The a-priori knowledge consists of a causal model of the domain, stating the relationships among basic phenomena, and a bo... | [
1370,
2038,
2172
] | Validation |
2,693 | 3 | Title: FROM METROPOLIS TO DIFFUSIONS: GIBBS STATES AND OPTIMAL SCALING
Abstract: This paper investigates the behaviour of the random walk Metropolis algorithm in high dimensional problems. Here we concentrate on the case where the components in the target density is a spatially homogeneous Gibbs distribution with fin... | [
2025
] | Train |
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