node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
2,494 | 4 | Title: Incremental Pruning: A Simple, Fast, Exact Algorithm for Partially Observable Markov Decision Processes
Abstract: Most exact algorithms for general pomdps use a form of dynamic programming in which a piecewise-linear and convex representation of one value function is transformed into another. We examine variat... | [
2063
] | Train |
2,495 | 6 | Title: Similar Classifiers and VC Error Bounds
Abstract: We improve error bounds based on VC analysis for classes with sets of similar classifiers. We apply the new error bounds to separating planes and artificial neural networks. Key words machine learning, learning theory, generalization, Vapnik-Chervonenkis, separ... | [
58,
571,
1762,
2694
] | Train |
2,496 | 2 | Title: Gene Structure Prediction by Linguistic Methods
Abstract: The higher-order structure of genes and other features of biological sequences can be described by means of formal grammars. These grammars can then be used by general-purpose parsers to detect and assemble such structures by means of syntactic pattern ... | [
613,
2107,
2571
] | Test |
2,497 | 2 | Title: Learning a Specialization for Face Recognition: The Effect of Spatial Frequency
Abstract: The double dissociation between prosopagnosia, a face recognition deficit occurring after brain damage, and visual object agnosia, difficulty recognizing other kinds of complex objects, indicates that face and non-face ob... | [
1915
] | Train |
2,498 | 2 | Title: Combining Exploratory Projection Pursuit And Projection Pursuit Regression With Application To Neural Networks
Abstract: We present a novel classification and regression method that combines exploratory projection pursuit (unsupervised training) with projection pursuit regression (supervised training), to yiel... | [
359,
2147,
2322,
2499,
2500,
2567
] | Test |
2,499 | 2 | Title: Objective Function Formulation of the BCM Theory of Visual Cortical Plasticity: Statistical Connections, Stability Conditions
Abstract: In this paper, we present an objective function formulation of the BCM theory of visual cortical plasticity that permits us to demonstrate the connection between the unsupervi... | [
203,
359,
863,
1068,
1418,
1787,
1871,
1935,
2147,
2322,
2357,
2376,
2385,
2422,
2498,
2500,
2505
] | Train |
2,500 | 2 | Title: Face Recognition using a Hybrid Supervised/Unsupervised Neural Network
Abstract: A system for automatic face recognition is presented. It consists of several steps; Automatic detection of the eyes and mouth is followed by a spatial normalization of the images. The classification of the normalized images is car... | [
1068,
2322,
2376,
2422,
2498,
2499
] | Validation |
2,501 | 2 | Title: EMRBF: A Statistical Basis for Using Radial Basis Functions for Process Control
Abstract: Radial Basis Function (RBF) neural networks offer an attractive equation form for use in model-based control because they can approximate highly nonlinear plants and yet are well suited for linear adaptive control. We sho... | [
611,
2260
] | Train |
2,502 | 0 | Title: Modeling Ill-Structured Optimization Tasks through Cases
Abstract: CABINS is a framework of modeling an optimization task in ill-structured domains. In such domains, neither systems nor human experts possess the exact model for guiding optimization. And the user's model of optimality is subjective and situatio... | [
717,
2605
] | Train |
2,503 | 2 | Title: `Balancing' of conductances may explain irregular cortical spiking.
Abstract: Five related factors are identified which enable single compartment Hodgkin-Huxley model neurons to convert random synaptic input into irregular spike trains similar to those seen in in vivo cortical recordings. We suggest that corti... | [
2358
] | Train |
2,504 | 1 | Title: Genetic Encoding Strategies for Neural Networks
Abstract: The application of genetic algorithms to neural network optimization (GANN) has produced an active field of research. This paper proposes a classification of the encoding strategies and it also gives a critical analysis of the current state of developme... | [
1536,
1663,
2667
] | Train |
2,505 | 2 | Title: Three-Dimensional Object Recognition Using an Unsupervised BCM Network: The Usefulness of Distinguishing Features
Abstract: We propose an object recognition scheme based on a method for feature extraction from gray level images that corresponds to recent statistical theory, called projection pursuit, and is de... | [
359,
611,
2499
] | Test |
2,506 | 3 | Title: Nonlinear wavelet shrinkage with Bayes rules and Bayes factors 1
Abstract: Wavelet shrinkage,the method proposed by seminal work of Donohoand Johnstone is a disarmingly simple and efficient way of de-noising data. Shrinking wavelet coefficients was proposed from several optimality criteria. The most notable ar... | [
1910,
2366,
2416,
2458,
2575,
2661
] | Train |
2,507 | 2 | Title: The Observer-Observation Dilemma in Neuro-Forecasting: Reliable Models From Unreliable Data Through CLEARNING
Abstract: This paper introduces the idea of clearning, of simultaneously cleaning data and learning the underlying structure. The cleaning step can be viewed as top-down processing (the model modifies ... | [
371,
2239,
2373,
2374
] | Train |
2,508 | 6 | Title: WRAPPERS FOR PERFORMANCE ENHANCEMENT AND OBLIVIOUS DECISION GRAPHS
Abstract: This paper introduces the idea of clearning, of simultaneously cleaning data and learning the underlying structure. The cleaning step can be viewed as top-down processing (the model modifies the data), and the learning step can be vie... | [
322,
632,
1235,
2137,
2577
] | Test |
2,509 | 6 | Title: Applying Winnow to Context-Sensitive Spelling Correction
Abstract: Multiplicative weight-updating algorithms such as Winnow have been studied extensively in the COLT literature, but only recently have people started to use them in applications. In this paper, we apply a Winnow-based algorithm to a task in natu... | [
517,
1962,
2618
] | Train |
2,510 | 3 | Title: Geometric Ergodicity and Hybrid Markov Chains
Abstract: Various notions of geometric ergodicity for Markov chains on general state spaces exist. In this paper, we review certain relations and implications among them. We then apply these results to a collection of chains commonly used in Markov chain Monte Carl... | [
416,
1713,
1977,
1978,
1991,
2002,
2362
] | Train |
2,511 | 6 | Title: A Faster Algorithm for the Perfect Phylogeny Problem when the number of Characters is Fixed TR94-05
Abstract: Various notions of geometric ergodicity for Markov chains on general state spaces exist. In this paper, we review certain relations and implications among them. We then apply these results to a collect... | [
2083,
2141,
2320,
2345,
2418
] | Train |
2,512 | 1 | Title: A Methodology for Strategy Optimization Under Uncertainty in the Extended Two-Dimensional Pursuer/Evader Problem
Abstract: | [
1930
] | Train |
2,513 | 2 | Title: Avoiding overfitting by locally matching the noise level of the data gating network discovers the
Abstract: When trying to forecast the future behavior of a real-world system, two of the key problems are nonstationarity of the process (e.g., regime switching) and overfitting of the model (particularly serious fo... | [
74,
310,
1366,
2239,
2374
] | Validation |
2,514 | 3 | Title: Learning Bayesian Prototype Trees by Simulated Annealing
Abstract: Given a set of samples of an unknown probability distribution, we study the problem of constructing a good approximative Bayesian network model of the probability distribution in question. This task can be viewed as a search problem, where the ... | [
485,
1838,
1908,
2380,
2558
] | Train |
2,515 | 1 | Title: Forward-Tracking: A Technique for Searching Beyond Failure
Abstract: In many applications, such as decision support, negotiation, planning, scheduling, etc., one needs to express requirements that can only be partially satisfied. In order to express such requirements, we propose a technique called forward-trac... | [
1999,
2003
] | Train |
2,516 | 1 | Title: When Gravity Fails: Local Search Topology
Abstract: Local search algorithms for combinatorial search problems frequently encounter a sequence of states in which it is impossible to improve the value of the objective function; moves through these regions, called plateau moves, dominate the time spent in local s... | [
1946
] | Train |
2,517 | 2 | Title: Solving the Temporal Binding Problem: A Neural Theory for Constructing and Updating Object Files
Abstract: Visual objects are perceived only if their parts are correctly identified and integrated. A neural network theory is proposed that seeks to explain how the human visual system binds together visual proper... | [
2533
] | Test |
2,518 | 1 | Title: Tracing the Behavior of Genetic Algorithms Using Expected Values of Bit and Walsh Products
Abstract: We consider two methods for tracing genetic algorithms. The first method is based on the expected values of bit products and the second method on the expected values of Walsh products. We treat proportional sel... | [
163,
2298
] | Train |
2,519 | 1 | Title: An Evolutionary Approach to Time Constrained Routing Problems
Abstract: Routing problems are an important class of planning problems. Usually there are many different constraints and optimization criteria involved, and it is difficult to find general methods for solving routing problems. We propose an evolutio... | [
2264
] | Validation |
2,520 | 0 | Title: Cooperative Case-Based Reasoning
Abstract: We are investigating possible modes of cooperation among homogeneous agents with learning capabilities. In this paper we will be focused on agents that learn and solve problems using Case-based Reasoning (CBR), and we will present two modes of cooperation among them: ... | [
66,
2359
] | Test |
2,521 | 1 | Title: Case-Based Probability Factoring in Bayesian Belief Networks
Abstract: Bayesian network inference can be formulated as a combinatorial optimization problem, concerning in the computation of an optimal factoring for the distribution represented in the net. Since the determination of an optimal factoring is a co... | [
145,
163,
2164,
2529
] | Validation |
2,522 | 2 | Title: A Symbolic Complexity Analysis of Connectionist Algorithms for Distributed-Memory Machines
Abstract: This paper attempts to rigorously determine the computation and communication requirements of connectionist algorithms running on a distributed-memory machine. The strategy involves (1) specifying key connectio... | [
2275
] | Train |
2,523 | 2 | Title: ADAPTIVE LOOK-AHEAD PLANNING problem of finding good initial plans is solved by the use of
Abstract: We present a new adaptive connectionist planning method. By interaction with an environment a world model is progressively constructed using the backpropagation learning algorithm. The planner constructs a look-a... | [
2684
] | Train |
2,524 | 3 | Title: ADAPTIVE LOOK-AHEAD PLANNING problem of finding good initial plans is solved by the use of
Abstract: In the Proceedings of the Conference on Uncertainty in Artificial Intelli- gence (UAI-94), Seattle, WA, 46-54, July 29-31, 1994. Technical Report R-213-B April, 1994 Abstract Evaluation of counterfactual queries ... | [
260,
1527,
1894,
2088,
2166
] | Validation |
2,525 | 3 | Title: Bayesian Networks
Abstract: In the Proceedings of the Conference on Uncertainty in Artificial Intelli- gence (UAI-94), Seattle, WA, 46-54, July 29-31, 1994. Technical Report R-213-B April, 1994 Abstract Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is important to fault... | [
1527,
2088
] | Train |
2,526 | 2 | Title: Logistic Response Projection Pursuit
Abstract: In the Proceedings of the Conference on Uncertainty in Artificial Intelli- gence (UAI-94), Seattle, WA, 46-54, July 29-31, 1994. Technical Report R-213-B April, 1994 Abstract Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is... | [
2448
] | Train |
2,527 | 5 | Title: 248 Efficient Superscalar Performance Through Boosting
Abstract: The foremost goal of superscalar processor design is to increase performance through the exploitation of instruction-level parallelism (ILP). Previous studies have shown that speculative execution is required for high instruction per cycle (IPC) ... | [
735,
1956,
1961,
2100
] | Train |
2,528 | 6 | Title: The Minimum Feature Set Problem
Abstract: This paper appeared in Neural Networks 7 (1994), no. 3, pp. 491-494. | [
1858
] | Train |
2,529 | 3 | Title: Decision-Theoretic Case-Based Reasoning
Abstract: Technical Report MSR-TR-95-03 | [
2294,
2521
] | Train |
2,530 | 2 | Title: Clustering Learning Tasks and the Selective Cross-Task Transfer of Knowledge
Abstract: This research is sponsored in part by the National Science Foundation under award IRI-9313367, and by the Wright Laboratory, Aeronautical Systems Center, Air Force Materiel Command, USAF, and the Advanced Research Projects A... | [
2090,
2415
] | Validation |
2,531 | 3 | Title: Utility Elicitation as a Classification Problem
Abstract: We investigate the application of classification techniques to utility elicitation. In a decision problem, two sets of parameters must generally be elicited: the probabilities and the utilities. While the prior and conditional probabilities in the model... | [
2566
] | Validation |
2,532 | 3 | Title: Ensemble Learning for Hidden Markov Models
Abstract: The standard method for training Hidden Markov Models optimizes a point estimate of the model parameters. This estimate, which can be viewed as the maximum of a posterior probability density over the model parameters, may be susceptible to over-fitting, and ... | [
76,
518,
766,
2417
] | Validation |
2,533 | 2 | Title: An Object-Based Neural Model of Serial Processing in Visual Multielement Tracking
Abstract: A quantitative model is provided for psychophysical data on the tracking of multiple visual elements (multielement tracking). The model employs an object-based attentional mechanism for constructing and updating object ... | [
2517
] | Train |
2,534 | 5 | Title: Data Value Prediction Methods and Performance
Abstract: A quantitative model is provided for psychophysical data on the tracking of multiple visual elements (multielement tracking). The model employs an object-based attentional mechanism for constructing and updating object representations. The model selective... | [
2009
] | Train |
2,535 | 2 | Title: Adaptive Wavelet Control of Nonlinear Systems
Abstract: This paper considers the design and analysis of adaptive wavelet control algorithms for uncertain nonlinear dynamical systems. The Lyapunov synthesis approach is used to develop a state-feedback adaptive control scheme based on nonlinearly parametrized wa... | [
1668,
2176
] | Train |
2,536 | 4 | Title: Truncating Temporal Differences: On the Efficient Implementation of TD() for Reinforcement Learning
Abstract: Temporal difference (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor . Currently the most important application o... | [
502,
1957,
2629
] | Test |
2,537 | 2 | Title: Toward Learning Systems That Integrate Different Strategies and Representations TR93-22
Abstract: Temporal difference (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor . Currently the most important application of these meth... | [
451,
1846,
1927,
2198
] | Train |
2,538 | 2 | Title: INCREMENTAL POLYNOMIAL CONTROLLER NETWORKS: two self-organising non-linear controllers
Abstract: Temporal difference (TD) methods constitute a class of methods for learning predictions in multi-step prediction problems, parameterized by a recency factor . Currently the most important application of these metho... | [
2325
] | Train |
2,539 | 5 | Title: Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail
Abstract: This paper presents first results of an interdisciplinary project in scientific data mining. We analyze data about the carcinogenicity of chemicals derived from the carcinogenesis bioassay program performed by the U... | [
1322,
1428,
2213
] | Train |
2,540 | 2 | Title: Efficient Implementation of Gaussian Processes
Abstract: Neural networks and Bayesian inference provide a useful framework within which to solve regression problems. However their parameterization means that the Bayesian analysis of neural networks can be difficult. In this paper, we investigate a method for r... | [
157,
160,
611,
1857
] | Train |
2,541 | 1 | Title: PLEASE: A prototype learning system using genetic algorithms
Abstract: Prototypes have been proposed as representation of concepts that are used effectively by humans. Developing computational schemes for generating prototypes from examples, however, has proved to be a difficult problem. We present a novel gen... | [
638,
686,
2673
] | Validation |
2,542 | 2 | Title: Worst-Case Identification of Nonlinear Fading Memory Systems
Abstract: In this paper, the problem of asymptotic identification for a class of fading memory systems in the presence of bounded noise is studied. For any experiment, the worst-case error is characterized in terms of the diameter of the worst-case u... | [
2236,
2262
] | Validation |
2,543 | 3 | Title: Combining Connectionist and Symbolic Learning to Refine Certainty-Factor Rule Bases
Abstract: This paper describes Rapture | a system for revising probabilistic knowledge bases that combines connectionist and symbolic learning methods. Rapture uses a modified version of backpropagation to refine the certainty ... | [
136,
159,
1479,
1776,
2409,
2440,
2674
] | Validation |
2,544 | 0 | Title: Choosing Learning Strategies to Achieve Learning Goals
Abstract: In open world applications a number of machine-learning techniques may potentially apply to a given learning situation. The research presented here illustrates the complexity involved in automatically choosing an appropriate technique in a multis... | [
2568
] | Validation |
2,545 | 2 | Title: Volatility of Volatility of Financial Markets
Abstract: We present empirical evidence for considering volatility of Eurodollar futures as a stochastic process, requiring a generalization of the standard Black-Scholes (BS) model which treats volatility as a constant. We use a previous development of a statistic... | [
1773,
1794,
1795,
2082,
2178
] | Train |
2,546 | 3 | Title: Plausibility Measures: A User's Guide
Abstract: We examine a new approach to modeling uncertainty based on plausibility measures, where a plausibility measure just associates with an event its plausibility, an element is some partially ordered set. This approach is easily seen to generalize other approaches to... | [
276,
342,
1993
] | Train |
2,547 | 0 | Title: Temporal abstractions for pre-processing and interpreting diabetes monitoring time series
Abstract: In this paper we describe a number of intelligent data analysis techniques to pre-process and analyze data coming from home monitoring of diabetic patients. In particular, we show how the combination of temporal... | [
2492
] | Test |
2,548 | 6 | Title: A Framework for Multiple-Instance Learning
Abstract: Multiple-instance learning is a variation on supervised learning, where the task is to learn a concept given positive and negative bags of instances. Each bag may contain many instances, but a bag is labeled positive even if only one of the instances in it f... | [
507,
2391,
2427
] | Validation |
2,549 | 2 | Title: A Generalized Approximate Cross Validation for Smoothing Splines with Non-Gaussian Data 1
Abstract: Multiple-instance learning is a variation on supervised learning, where the task is to learn a concept given positive and negative bags of instances. Each bag may contain many instances, but a bag is labeled pos... | [
193,
280,
519,
2608
] | Train |
2,550 | 5 | Title: Language Series Revisited: The Complexity of Hypothesis Spaces in ILP
Abstract: Restrictions on the number and depth of existential variables as defined in the language series of Clint [Rae92] are widely used in ILP and expected to produce a considerable reduction in the size of the hypothesis space. In this p... | [
2045
] | Train |
2,551 | 4 | Title: The Role of Forgetting in Learning
Abstract: This paper is a discussion of the relationship between learning and forgetting. An analysis of the economics of learning is carried out and it is argued that knowledge can sometimes have a negative value. A series of experiments involving a program which learns to t... | [
523,
2473
] | Train |
2,552 | 2 | Title: Inferring sparse, overcomplete image codes using an efficient coding framework
Abstract: We apply a general technique for learning overcomplete bases to the problem of finding efficient image codes. The bases learned by the algorithm are localized, oriented, and bandpass, consistent with earlier results obtain... | [
576,
2026
] | Validation |
2,553 | 2 | Title: TURING COMPUTABILITY WITH NEURAL NETS
Abstract: This paper shows the existence of a finite neural network, made up of sigmoidal neurons, which simulates a universal Turing machine. It is composed of less than 10 5 synchronously evolving processors, interconnected linearly. High-order connections are not requir... | [
1875
] | Train |
2,554 | 1 | Title: Genetic Programming Estimates of Kolmogorov Complexity
Abstract: In this paper the problem of the Kolmogorov complexity related to binary strings is faced. We propose a Genetic Programming approach which consists in evolving a population of Lisp programs looking for the optimal program that generates a given s... | [
163,
1850
] | Train |
2,555 | 6 | Title: Knowing What Doesn't Matter: Exploiting Omitted Superfluous Data
Abstract: Most inductive inference algorithms (i.e., "learners") work most effectively when their training data contain completely specified labeled samples. In many diagnostic tasks, however, the data will include the values of only some of the ... | [
2560
] | Train |
2,556 | 0 | Title: A Case-Based Approach to Reactive Control for Autonomous Robots
Abstract: We propose a case-based method of selecting behavior sets as an addition to traditional reactive robotic control systems. The new system (ACBARR | A Case BAsed Reactive Robotic system) provides more flexible performance in novel environm... | [
858,
1904
] | Train |
2,557 | 2 | Title: Growing Simpler Decision Trees to Facilitate Knowledge Discovery
Abstract: When using machine learning techniques for knowledge discovery, output that is comprehensible to a human is as important as predictive accuracy. We introduce a new algorithm, SET-Gen, that improves the comprehensibility of decision tree... | [
163,
430,
686,
1947
] | Validation |
2,558 | 3 | Title: Using Bayesian networks for incorporating probabilistic a priori knowledge into Boltzmann machines
Abstract: We present a method for automatically determining the structure and the connection weights of a Boltzmann machine corresponding to a given Bayesian network representation of a probability distribution o... | [
450,
2514
] | Test |
2,559 | 3 | Title: "Linear Dependencies Represented by Chain Graphs," "Graphical Modelling With MIM," Manual. "Identifying Independence in Bayesian
Abstract: 8] Dori, D. and Tarsi, M., "A Simple Algorithm to Construct a Consistent Extension of a Partially Oriented Graph," Computer Science Department, Tel-Aviv University. Also Tech... | [
51,
260,
841,
1241,
1747,
2076
] | Train |
2,560 | 6 | Title: Learning Default Concepts
Abstract: Classical concepts, based on necessary and sufficient defining conditions, cannot classify logically insufficient object descriptions. Many reasoning systems avoid this limitation by using "default concepts" to classify incompletely described objects. We address the task of ... | [
251,
323,
649,
865,
1505,
2555
] | Train |
2,561 | 3 | Title: MDL Learning of Probabilistic Neural Networks for Discrete Problem Domains
Abstract: Given a problem, a case-based reasoning (CBR) system will search its case memory and use the stored cases to find the solution, possibly modifying retrieved cases to adapt to the required input specifications. In discrete doma... | [
485,
719,
1527,
1908,
2380
] | Train |
2,562 | 2 | Title: NONLINEAR TRADING MODELS THROUGH SHARPE RATIO MAXIMIZATION
Abstract: Working Paper IS-97-005, Leonard N. Stern School of Business, New York University. In: Decision Technologies for Financial Engineering (Proceedings of the Fourth International Conference on Neural Networks in the Capital Markets, NNCM-96), pp... | [
668,
1366,
2595
] | Train |
2,563 | 1 | Title: Analysis of Neurocontrollers Designed by Simulated Evolution
Abstract: Randomized, adaptive, greedy search using evolutionary algorithms offers a powerful and versatile approach to the automated design of neural network architectures for a variety of tasks in artificial intelligence and robotics. In this paper... | [
163,
219,
1583,
2220,
2396
] | Test |
2,564 | 1 | Title: Embedding of a sequential procedure within an evolutionary algorithm for coloring problems in graphs
Abstract: Randomized, adaptive, greedy search using evolutionary algorithms offers a powerful and versatile approach to the automated design of neural network architectures for a variety of tasks in artificial ... | [
163,
1159,
1558,
1785
] | Validation |
2,565 | 0 | Title: Defining and Combining Symmetric and Asymmetric Similarity Measures
Abstract: In this paper, we present a framework for the definition of similarity measures using lattice-valued functions. We show their strengths (particularly for combining similarity measures). Then we investigate a particular instantiation ... | [
2157
] | Validation |
2,566 | 3 | Title: A Constraint-Based Approach to Preference Elicitation and Decision Making
Abstract: We investigate the solution of constraint-based configuration problems in which the preference function over outcomes is unknown or incompletely specified. The aim is to configure a system, such as a personal computer, so that ... | [
62,
2531
] | Train |
2,567 | 2 | Title: On the Combination of Supervised and Unsupervised Learning reducing the overall error measure of a classifier.
Abstract: | [
359,
2498
] | Validation |
2,568 | 0 | Title: Abstract
Abstract: Self-selection of input examples on the basis of performance failure is a powerful bias for learning systems. The definition of what constitutes a learning bias, however, has been typically restricted to bias provided by the input language, hypothesis language, and preference criteria betwee... | [
289,
583,
612,
717,
2544
] | Train |
2,569 | 2 | Title: The Gamma MLP Using Multiple Temporal Resolutions for Improved Classification
Abstract: We have previously introduced the Gamma MLP which is defined as an MLP with the usual synaptic weights replaced by gamma filters and associated gain terms throughout all layers. In this paper we apply the Gamma MLP to a lar... | [
1820
] | Train |
2,570 | 2 | Title: In Fast Non-Linear Dimension Reduction
Abstract: We present a fast algorithm for non-linear dimension reduction. The algorithm builds a local linear model of the data by merging PCA with clustering based on a new distortion measure. Experiments with speech and image data indicate that the local linear algorit... | [
480,
667,
1806,
1928
] | Validation |
2,571 | 2 | Title: Non-Deterministic, Constraint-Based Parsing of Human Genes
Abstract: We present a fast algorithm for non-linear dimension reduction. The algorithm builds a local linear model of the data by merging PCA with clustering based on a new distortion measure. Experiments with speech and image data indicate that the l... | [
268,
613,
1878,
2107,
2496
] | Train |
2,572 | 2 | Title: Negative observations concerning approximations from spaces generated by scattered shifts of functions vanishing at 1
Abstract: Approximation by scattered shifts f( ff)g ff2A of a basis function are considered, and different methods for localizing these translates are compared. It is argued in the note that th... | [
365,
2112
] | Train |
2,573 | 3 | Title: An Optimum Decision Rule for Pattern Recognition
Abstract: | [
1942
] | Train |
2,574 | 2 | Title: Identification of Protein Coding Regions In Genomic DNA Molecular, Cellular and Developmental Biology, Keywords: gene
Abstract: | [
427,
2107
] | Validation |
2,575 | 3 | Title: The Stationary Wavelet Transform and some Statistical Applications
Abstract: Wavelets are of wide potential use in statistical contexts. The basics of the discrete wavelet transform are reviewed using a filter notation that is useful subsequently in the paper. A `stationary wavelet transform', where the coeffi... | [
1910,
2366,
2388,
2506
] | Validation |
2,576 | 2 | Title: A Neural Model of the Cortical Representation of Egocentric Distance
Abstract: Wavelets are of wide potential use in statistical contexts. The basics of the discrete wavelet transform are reviewed using a filter notation that is useful subsequently in the paper. A `stationary wavelet transform', where the coef... | [
1051,
2678
] | Train |
2,577 | 3 | Title: Targeting Business Users with Decision Table Classifiers
Abstract: Business users and analysts commonly use spreadsheets and 2D plots to analyze and understand their data. On-line Analytical Processing (OLAP) provides these users with added flexibility in pivoting data around different attributes and drilling ... | [
1020,
2180,
2342,
2367,
2508
] | Test |
2,578 | 3 | Title: Analysis of hospital quality monitors using hierarchical time series models
Abstract: The VA management services department invests considerably in the collection and assessment of data to inform on hospital and care-area specific levels of quality of care. Resulting time series of quality monitors provide inf... | [
99,
2679
] | Train |
2,579 | 2 | Title: SPERT-II: A Vector Microprocessor System and its Application to Large Problems in Backpropagation Training
Abstract: We report on our development of a high-performance system for neural network and other signal processing applications. We have designed and implemented a vector microprocessor and packaged it as... | [
2279,
2336
] | Train |
2,580 | 6 | Title: The Challenge of Revising an Impure Theory
Abstract: A pure rule-based program will return a set of answers to each query; and will return the same answer set even if its rules are re-ordered. However, an impure program, which includes the Prolog cut "!" and not() operators, can return different answers if the... | [
52,
136,
1819,
1823
] | Train |
2,581 | 0 | Title: Four Challenges for a Computational Model of Legal Precedent
Abstract: Identifying the open research issues in a field is a necessary step for progress in that field. This paper describes four open research problems in computational models of precedent-based legal reasoning: relating case representation to pre... | [
649,
2403
] | Validation |
2,582 | 2 | Title: Noisy Time Series Prediction using Symbolic Representation and Recurrent Neural Network Grammatical Inference
Abstract: Financial forecasting is an example of a signal processing problem which is challenging due to small sample sizes, high noise, non-stationarity, and non-linearity. Neural networks have been v... | [
409,
411,
462,
1718,
2178
] | Train |
2,583 | 6 | Title: Dynamic Automatic Model Selection
Abstract: COINS Technical Report 92-30 February 1992 Abstract The problem of how to learn from examples has been studied throughout the history of machine learning, and many successful learning algorithms have been developed. A problem that has received less attention is how t... | [
102,
378,
1173,
1423,
2135,
2310,
2333
] | Train |
2,584 | 2 | Title: Presynaptic and Postsynaptic Competition in Models for the Development of Neuromuscular Connections
Abstract: The development of the nervous system involves in many cases interactions on a local scale rather than the execution of a fully specified genetic blueprint. The problem is to discover the nature of the... | [
2632
] | Test |
2,585 | 0 | Title: Rule Induction and Instance-Based Learning: A Unified Approach
Abstract: This paper presents a new approach to inductive learning that combines aspects of instance-based learning and rule induction in a single simple algorithm. The RISE system searches for rules in a specific-to-general fashion, starting with ... | [
1263,
1809,
1830,
2441
] | Train |
2,586 | 4 | Title: Learning One More Thing
Abstract: Most research on machine learning has focused on scenarios in which a learner faces a single, isolated learning task. The lifelong learning framework assumes that the learner encounters a multitude of related learning tasks over its lifetime, providing the opportunity for the ... | [
1647,
1889,
2113,
2162,
2486
] | Test |
2,587 | 5 | Title: Predicate Invention and Learning from Positive Examples Only
Abstract: Previous bias shift approaches to predicate invention are not applicable to learning from positive examples only, if a complete hypothesis can be found in the given language, as negative examples are required to determine whether new predic... | [
2312
] | Train |
2,588 | 3 | Title: Some recent ideas on utility (and probability) (not for distribution or reference)
Abstract: | [
2301
] | Train |
2,589 | 5 | Title: Pac-Learning Recursive Logic Programs: Efficient Algorithms
Abstract: We present algorithms that learn certain classes of function-free recursive logic programs in polynomial time from equivalence queries. In particular, we show that a single k-ary recursive constant-depth determinate clause is learnable. Two-... | [
344,
2329,
2424
] | Train |
2,590 | 3 | Title: Backfitting in Smoothing Spline ANOVA
Abstract: A scheme to compute smoothing spline ANOVA estimates for large data sets with a (near) tensor-product structure is proposed. Such data sets are common in spatial-temporal analysis and image analysis. This scheme combines backfitting algorithm with iterative imput... | [
388,
420,
519,
2421
] | Test |
2,591 | 5 | Title: Lookahead and Discretization in ILP
Abstract: We present and evaluate two methods for improving the performance of ILP systems. One of them is discretization of numerical attributes, based on Fayyad and Irani's text [9], but adapted and extended in such a way that it can cope with some aspects of discretizatio... | [
2126,
2253,
2427,
2431
] | Test |
2,592 | 3 | Title: FILTERING VIA SIMULATION: AUXILIARY PARTICLE FILTERS
Abstract: This paper analyses the recently suggested particle approach to filtering time series. We suggest that the algorithm is not robust to outliers for two reasons: the design of the simulators and the use of the discrete support to represent the sequen... | [
99,
1852
] | Test |
2,593 | 0 | Title: Induction of Condensed Determinations
Abstract: In this paper we suggest determinations as a representation of knowledge that should be easy to understand. We briefly review determinations, which can be displayed in a tabular format, and their use in prediction, which involves a simple matching process. We des... | [
430,
634,
2342
] | Train |
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