node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
2,094 | 3 | Title: Interpretation of Complex Scenes Using Bayesian Networks
Abstract: In most object recognition systems, interactions between objects in a scene are ignored and the best interpretation is considered to be the set of hypothesized objects that matches the greatest number of image features. We show how image interp... | [
2164
] | Validation |
2,095 | 2 | Title: A Practical Monte Carlo Implementation of Bayesian Learning
Abstract: | [
157,
2056,
2230
] | Train |
2,096 | 5 | Title: A Note on Scheduling Algorithms for Processors with Lookahead
Abstract: | [
2142
] | Validation |
2,097 | 3 | Title: Impediments to Universal Preference-Based Default Theories
Abstract: Research on nonmonotonic and default reasoning has identified several important criteria for preferring alternative default inferences. The theories of reasoning based on each of these criteria may uniformly be viewed as theories of rational ... | [
1994,
1995
] | Validation |
2,098 | 6 | Title: Predicting a binary sequence almost as well as the optimal biased coin
Abstract: We apply the exponential weight algorithm, introduced and Littlestone and Warmuth [17] and by Vovk [24] to the problem of predicting a binary sequence almost as well as the best biased coin. We first show that for the case of the ... | [
453,
2099,
2156
] | Validation |
2,099 | 6 | Title: Game Theory, On-line Prediction and Boosting
Abstract: We study the close connections between game theory, on-line prediction and boosting. After a brief review of game theory, we describe an algorithm for learning to play repeated games based on the on-line prediction methods of Littlestone and War-muth. The ... | [
453,
456,
569,
2098
] | Validation |
2,100 | 5 | Title: GURRR: A Global Unified Resource Requirements Representation
Abstract: When compiling for instruction level parallelism (ILP), the integration of the optimization phases can lead to an improvement in the quality of code generated. However, since several different representations of a program are used in the va... | [
1961,
2527
] | Train |
2,101 | 1 | Title: Evolving Control Structures with Automatically Defined Macros Evolving Control Structures with Automatically Defined Macros.
Abstract: When compiling for instruction level parallelism (ILP), the integration of the optimization phases can lead to an improvement in the quality of code generated. However, since ... | [
2470
] | Validation |
2,102 | 1 | Title: The Evolution of Communication Schemes Over Continuous Channels
Abstract: Many problems impede the design of multi-agent systems, not the least of which is the passing of information between agents. While others hand implement communication routes and semantics, we explore a method by which communication can e... | [
144,
189,
2664
] | Train |
2,103 | 1 | Title: The Evolution of Communication Schemes Over Continuous Channels
Abstract: As the field of Genetic Programming (GP) matures and its breadth of application increases, the need for parallel implementations becomes absolutely necessary. The transputer-based system presented in [Koza and Andre 1995] is one of the r... | [
415,
2334
] | Train |
2,104 | 1 | Title: A study of the effects of group formation on evolutionary search
Abstract: As the field of Genetic Programming (GP) matures and its breadth of application increases, the need for parallel implementations becomes absolutely necessary. The transputer-based system presented in [Koza and Andre 1995] is one of the ... | [
403,
2302
] | Train |
2,105 | 2 | Title: A study of the effects of group formation on evolutionary search
Abstract: Information Processing in Primate Retinal Cone Pathways: Experiments and Results | [
2621
] | Test |
2,106 | 5 | Title: Theoretical Modeling of Superscalar Processor Performance
Abstract: The current trace-driven simulation approach to determine superscalar processor performance is widely used but has some shortcomings. Modern benchmarks generate extremely long traces, resulting in problems with data storage, as well as very lo... | [
735,
1750,
2649
] | Validation |
2,107 | 2 | Title: Prediction of human mRNA donor and acceptor sites from the DNA sequence
Abstract: Artificial neural networks have been applied to the prediction of splice site location in human pre-mRNA. A joint prediction scheme where prediction of transition regions between introns and exons regulates a cutoff level for spl... | [
613,
1865,
1953,
2046,
2496,
2571,
2574
] | Test |
2,108 | 3 | Title: The Automated Mapping of Plans for Plan Recognition
Abstract: To coordinate with other agents in its environment, an agent needs models of what the other agents are trying to do. When communication is impossible or expensive, this information must be acquired indirectly via plan recognition. Typical approaches... | [
1172,
1898,
2140
] | Train |
2,109 | 2 | Title: Local quartet splits of a binary tree infer all quartet splits via one dyadic inference
Abstract: DIMACS Technical Report 96-43 DIMACS is a partnership of Rutgers University, Princeton University, AT&T Research, Bellcore, and Bell Laboratories. DIMACS is an NSF Science and Technology Center, funded under contrac... | [
2185
] | Train |
2,110 | 6 | Title: Constructing Big Trees from Short Sequences
Abstract: The construction of evolutionary trees is a fundamental problem in biology, and yet methods for reconstructing evolutionary trees are not reliable when it comes to inferring accurate topologies of large divergent evolutionary trees from realistic length seq... | [
299,
1827
] | Train |
2,111 | 1 | Title: Artificial Life as Theoretical Biology: How to do real science with computer simulation
Abstract: Artificial Life (A-Life) research offers, among other things, a new style of computer simulation for understanding biological systems and processes. But most current A-Life work does not show enough methodological... | [
2047,
2302
] | Train |
2,112 | 2 | Title: Approximation from shift-invariant subspaces of L
Abstract: A complete characterization is given of closed shift-invariant subspaces of L 2 (IR d ) which provide a specified approximation order. When such a space is principal (i.e., generated by a single function), then this characterization is in terms of the... | [
365,
2572
] | Train |
2,113 | 6 | Title: Learning Model Bias minimum number of examples requred to learn a single task, and O(a
Abstract: In this paper the problem of learning appropriate domain-specific bias is addressed. It is shown that this can be achieved by learning many related tasks from the same domain, and a theorem is given bounding the numb... | [
2586,
2623
] | Train |
2,114 | 3 | Title: Probabilistic Principal Component Analysis
Abstract: Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined throug... | [
1923,
1928,
2124
] | Validation |
2,115 | 3 | Title: Modeling Belief in Dynamic Systems. Part I: Foundations
Abstract: Belief change is a fundamental problem in AI: Agents constantly have to update their beliefs to accommodate new observations. In recent years, there has been much work on axiomatic characterizations of belief change. We claim that a better under... | [
276,
2000
] | Train |
2,116 | 1 | Title: Differential Evolution A simple and efficient adaptive scheme for global optimization over continuous spaces
Abstract: A new heuristic approach for minimizing possibly nonlinear and non differentiable continuous space functions is presented. By means of an extensive testbed, which includes the De Jong function... | [
163,
1775,
2125
] | Train |
2,117 | 2 | Title: Stimulus specificity in perceptual learning: a consequence of experiments that are also stimulus specific? Keywords:
Abstract: A new heuristic approach for minimizing possibly nonlinear and non differentiable continuous space functions is presented. By means of an extensive testbed, which includes the De Jong fu... | [
2639
] | Test |
2,118 | 4 | Title: On Step-Size and Bias in Temporal-Difference Learning
Abstract: We present results for three new algorithms for setting the step-size parameters, ff and , of temporal-difference learning methods such as TD(). The overall task is that of learning to predict the outcome of an unknown Markov chain based on repeat... | [
565,
2442
] | Train |
2,119 | 2 | Title: Gas Identification System using Graded Temperature Sensor and Neural Net Interpretation
Abstract: We present results for three new algorithms for setting the step-size parameters, ff and , of temporal-difference learning methods such as TD(). The overall task is that of learning to predict the outcome of an un... | [
2154
] | Train |
2,120 | 2 | Title: PUSH-PULL SHUNTING MODEL OF GANGLION CELLS Simulations of X and Y retinal ganglion cell behavior
Abstract: We present results for three new algorithms for setting the step-size parameters, ff and , of temporal-difference learning methods such as TD(). The overall task is that of learning to predict the outcome o... | [
1798
] | Test |
2,121 | 2 | Title: Testing for Gaussianity and Non Linearity in the sustained portion of musical sounds.
Abstract: Higher order spectra of a signal contain information about the non Gaussian and non Linear properties of the system that created it. Since the non linearity in musical signal usually originate in the excitation sign... | [
2212
] | Test |
2,122 | 0 | Title: Preparing Case Retrieval Nets for Distributed Processing
Abstract: In this paper, we discuss two approaches of applying the memory model of Case Retrieval Nets to applications where a distributed processing of information is required. For this, we distinguish two types of such applications, namely (a) the case... | [
66,
75,
1854,
1855,
1864
] | Validation |
2,123 | 0 | Title: Justification Structures for Document Reuse
Abstract: Document drafting|an important problem-solving task of professionals in a wide variety of fields|typifies a design task requiring complex adaptation for case reuse. This paper proposes a framework for document reuse based on an explicit representation of th... | [
649,
2482
] | Train |
2,124 | 2 | Title: A Hierarchical Latent Variable Model for Data Visualization
Abstract: Visualization has proven to be a powerful and widely-applicable tool for the analysis and interpretation of multi-variate data. Most visualization algorithms aim to find a projection from the data space down to a two-dimensional visualizatio... | [
74,
1928,
2114
] | Train |
2,125 | 2 | Title: On the Usage of Differential Evolution for Function Optimization Differential Evolution (DE) has recently proven
Abstract: assumed unless otherwise stated. Basically, DE generates new parameter vectors by adding the weighted difference between two population vectors to a third vector. If the resulting vector yie... | [
2116
] | Train |
2,126 | 5 | Title: Applying ILP to Diterpene Structure Elucidation from 13 C NMR Spectra
Abstract: We present a novel application of ILP to the problem of diterpene structure elucidation from 13 C NMR spectra. Diterpenes are organic compounds of low molecular weight that are based on a skeleton of 20 carbon atoms. They are of si... | [
426,
2213,
2339,
2426,
2591
] | Train |
2,127 | 3 | Title: NAIVE BAYESIAN LEARNING Adapted from
Abstract: We present a novel application of ILP to the problem of diterpene structure elucidation from 13 C NMR spectra. Diterpenes are organic compounds of low molecular weight that are based on a skeleton of 20 carbon atoms. They are of significant chemical and commercia... | [
1329,
2338
] | Train |
2,128 | 0 | Title: Intelligent Model Selection for Hillclimbing Search in Computer-Aided Design
Abstract: Models of physical systems can differ according to computational cost, accuracy and precision, among other things. Depending on the problem solving task at hand, different models will be appropriate. Several investigators ha... | [
2030,
2479
] | Train |
2,129 | 2 | Title: Fast Pruning Using Principal Components
Abstract: We present a new algorithm for eliminating excess parameters and improving network generalization after supervised training. The method, "Principal Components Pruning (PCP)", is based on principal component analysis of the node activations of successive layers ... | [
2454
] | Train |
2,130 | 1 | Title: Intelligent Gradient-Based Search of Incompletely Defined Design Spaces
Abstract: Gradient-based numerical optimization of complex engineering designs offers the promise of rapidly producing better designs. However, such methods generally assume that the objective function and constraint functions are continuo... | [
2030
] | Validation |
2,131 | 0 | Title: Learning Prototype-Selection Rules for Case-Based Iterative Design seen as a case-based reasoning system [4], in
Abstract: The first step for most case-based design systems is to select an initial prototype from a database of previous designs. The retrieved prototype is then modified to tailor it to the given go... | [
1892,
2030,
2319
] | Validation |
2,132 | 5 | Title: Combining Data Mining and Machine Learning for Effective User Profiling
Abstract: This paper describes the automatic design of methods for detecting fraudulent behavior. Much of the design is accomplished using a series of machine learning methods. In particular, we combine data mining and constructive inducti... | [
382,
1837
] | Validation |
2,133 | 1 | Title: Genetic Programming Bloat with Dynamic Fitness
Abstract: Technical Report: CSRP-97-29, 3 December 1997 Abstract In artificial evolution individuals which perform as their parents are usually rewarded identically to their parents. We note that Nature is more dynamic and there may be a penalty to pay for doing t... | [
1925,
2199,
2206
] | Train |
2,134 | 6 | Title: Learning to Classify Sensor Data inductive bias, supervised Bayesian learning, minimum description length.
Abstract: | [
2644
] | Train |
2,135 | 2 | Title: Learning Polynomial Functions by Feature Construction
Abstract: We present a method for learning higher-order polynomial functions from examples using linear regression and feature construction. Regression is used on a set of training instances to produce a weight vector for a linear function over the feature ... | [
134,
2012,
2023,
2333,
2583
] | Test |
2,136 | 3 | Title: Bayesian Experimental Design: A Review
Abstract: Non Bayesian experimental design for linear models has been reviewed by Stein-berg and Hunter (1984) and in the recent book by Pukelsheim (1993); Ford, Kitsos and Titterington (1989) reviewed non Bayesian design for nonlinear models. Bayesian design for both lin... | [
2148
] | Train |
2,137 | 0 | Title: Search-based Class Discretization
Abstract: We present a methodology that enables the use of classification algorithms on regression tasks. We implement this method in system RECLA that transforms a regression problem into a classification one and then uses an existent classification system to solve this new p... | [
430,
431,
2508
] | Train |
2,138 | 3 | Title: A Nonparametric Bayesian Approach to Modelling Nonlinear Time Series
Abstract: The Bayesian multivariate adaptive regression spline (BMARS) methodology of Denison et al. (1997) is extended to cope with nonlinear time series and financial datasets. The nonlinear time series model is closely related to the adapt... | [
1718,
2285
] | Train |
2,139 | 1 | Title: Evolving Teamwork and Coordination with Genetic Programming
Abstract: Some problems can be solved only by multi-agent teams. In using genetic programming to produce such teams, one faces several design decisions. First, there are questions of team diversity and of breeding strategy. In one commonly used scheme... | [
995,
2220,
2226
] | Test |
2,140 | 3 | Title: Sonderforschungsbereich 314 K unstliche Intelligenz Wissensbasierte Systeme KI-Labor am Lehrstuhl f ur Informatik IV Numerical
Abstract: Some problems can be solved only by multi-agent teams. In using genetic programming to produce such teams, one faces several design decisions. First, there are questions of tea... | [
623,
1268,
1898,
2108,
2292
] | Train |
2,141 | 6 | Title: Fast and Simple Algorithms for Perfect Phylogeny and Triangulating Colored Graphs
Abstract: This paper presents an O((r n=m) m rnm) algorithm for determining whether a set of n species has a perfect phylogeny, where m is the number of characters used to describe a species and r is the maximum number of states ... | [
2418,
2511
] | Test |
2,142 | 5 | Title: Run-time versus Compile-time Instruction Scheduling in Superscalar (RISC) Processors: Performance and Tradeoffs
Abstract: The RISC revolution has spurred the development of processors with increasing levels of instruction level parallelism (ILP). In order to realize the full potential of these processors, mult... | [
2096
] | Train |
2,143 | 2 | Title: MULTIPLE SCALES OF BRAIN-MIND INTERACTIONS
Abstract: Posner and Raichle's Images of Mind is an excellent educational book and very well written. Some aws as a scientific publication are: (a) the accuracy of the linear subtraction method used in PET is subject to scrutiny by further research at finer spatial-te... | [
2181
] | Train |
2,144 | 3 | Title: UNIVERSAL FORMULAS FOR TREATMENT EFFECTS FROM NONCOMPLIANCE DATA
Abstract: This paper establishes formulas that can be used to bound the actual treatment effect in any experimental study in which treatment assignment is random but subject compliance is imperfect. These formulas provide the tightest bounds on t... | [
1326,
1894
] | Train |
2,145 | 6 | Title: Exploration in Machine Learning
Abstract: Most researchers in machine learning have built their learning systems under the assumption that some external entity would do all the work of furnishing the learning experiences. Recently, however, investigators in several subfields of machine learning have designed s... | [
2408
] | Validation |
2,146 | 6 | Title: On Learning Read-k-Satisfy-j DNF
Abstract: We study the learnability of Read-k-Satisfy-j (RkSj) DNF formulas. These are boolean formulas in disjunctive normal form (DNF), in which the maximum number of occurrences of a variable is bounded by k, and the number of terms satisfied by any assignment is at most j. ... | [
638,
1003,
1004,
1897,
2182
] | Test |
2,147 | 2 | Title: Extraction of Facial Features for Recognition using Neural Networks
Abstract: | [
2019,
2498,
2499
] | Train |
2,148 | 3 | Title: Bayesian Design for the Normal Linear Model with Unknown Error Variance
Abstract: Most of the Bayesian theory of optimal experimental design, for the normal linear model, has been developed under the restrictive assumption that the variance is known. In special cases, insensitivity of specific design criteria ... | [
2136
] | Validation |
2,149 | 5 | Title: Scheduling and Mapping: Software Pipelining in the Presence of Structural Hazards proposed formulation and a
Abstract: Recently, software pipelining methods based on an ILP (Integer Linear Programming) framework have been successfully applied to derive rate-optimal schedules for architectures involving clean pip... | [
1955,
2188,
2190,
2194
] | Train |
2,150 | 4 | Title: Multi-time Models for Temporally Abstract Planning
Abstract: Planning and learning at multiple levels of temporal abstraction is a key problem for artificial intelligence. In this paper we summarize an approach to this problem based on the mathematical framework of Markov decision processes and reinforcement l... | [
1192,
1954,
2179,
2183,
2222,
2305
] | Test |
2,151 | 0 | Title: A Yardstick for the Evaluation of Case-Based Classifiers
Abstract: This paper proposes that the generalisation capabilities of a case-based reasoning system can be evaluated by comparison with a `rote-learning' algorithm which uses a very simple generalisation strategy. Two such algorithms are defined, and exp... | [
1109,
1584,
2037,
2342
] | Validation |
2,152 | 1 | Title: Cellular Encoding for Interactive Evolutionary Robotics
Abstract: Research in robotics programming is divided in two camps. The direct hand programmming approach uses an explicit model or a behavioral model ( subsumption architecture). The machine learning community uses neural network and/or genetic algorithm... | [
1277,
2429
] | Test |
2,153 | 3 | Title: Rates of convergence of the Hastings and Metropolis algorithms
Abstract: We apply recent results in Markov chain theory to Hastings and Metropolis algorithms with either independent or symmetric candidate distributions, and provide necessary and sufficient conditions for the algorithms to converge at a geometr... | [
115,
889,
1713,
1716,
1977,
1982,
1992,
2002,
2008,
2022,
2025,
2219,
2318,
2699
] | Train |
2,154 | 2 | Title: Olfaction Metal Oxide Semiconductor Gas Sensors and Neural Networks
Abstract: We apply recent results in Markov chain theory to Hastings and Metropolis algorithms with either independent or symmetric candidate distributions, and provide necessary and sufficient conditions for the algorithms to converge at a ge... | [
2119
] | Test |
2,155 | 2 | Title: Cognitive Computation (Extended Abstract)
Abstract: Cognitive computation is discussed as a discipline that links together neurobiology, cognitive psychology and artificial intelligence. | [
591,
2467
] | Train |
2,156 | 6 | Title: WORST CASE PREDICTION OVER SEQUENCES UNDER LOG LOSS
Abstract: We consider the game of sequentially assigning probabilities to future data based on past observations under logarithmic loss. We are not making probabilistic assumptions about the generation of the data, but consider a situation where a player trie... | [
453,
2098
] | Train |
2,157 | 0 | Title: Similarity Metrics: A Formal Unification of Cardinal and Non-Cardinal Similarity Measures
Abstract: In [9] we introduced a formal framework for constructing ordinal similarity measures, and suggested how this might also be applied to cardinal measures. In this paper we will place this approach in a more genera... | [
66,
288,
2565
] | Train |
2,158 | 5 | Title: Learning Recursion with Iterative Bootstrap Induction (Extended Abstract)
Abstract: In this paper we are concerned with the problem of inducing recursive Horn clauses from small sets of training examples. The method of iterative bootstrap induction is presented. In the first step, the system generates simple c... | [
1498,
2449
] | Validation |
2,159 | 3 | Title: Wavelet Shrinkage: Asymptopia?
Abstract: Considerable effort has been directed recently to develop asymptotically minimax methods in problems of recovering infinite-dimensional objects (curves, densities, spectral densities, images) from noisy data. A rich and complex body of work has evolved, with nearly- or ... | [
1910,
2081,
2661
] | Test |
2,160 | 3 | Title: group, and despite having just 337 subjects, the study strongly supports Identification of causal effects
Abstract: Figure 8a and Figure 8b show the prior distribution over f(-CR ) that follows from the flat prior and the skewed prior, respectively. Figure 8c and Figure 8d show the posterior distribution p(f (-C... | [
1747,
2434
] | Train |
2,161 | 3 | Title: On The Foundation Of Structural Equation Models or
Abstract: When Can We Give Causal Interpretation Abstract The assumptions underlying statistical estimation are of fundamentally different character from the causal assumptions that underly structural equation models (SEM). The differences have been blurred th... | [
1326,
2167
] | Train |
2,162 | 2 | Title: Incremental Class Learning approach and its application to Handwritten Digit Recognition
Abstract: Incremental Class Learning (ICL) provides a feasible framework for the development of scalable learning systems. Instead of learning a complex problem at once, ICL focuses on learning subproblems incrementally, o... | [
745,
2586,
2599
] | Validation |
2,163 | 5 | Title: Speculative Hedge: Regulating Compile-Time Speculation Against Profile Variations code performance in the presence of execution
Abstract: Path-oriented scheduling methods, such as trace scheduling and hyperblock scheduling, use speculation to extract instruction-level parallelism from control-intensive programs.... | [
1849
] | Test |
2,164 | 3 | Title: Efficient Inference in Bayes Networks As A Combinatorial Optimization Problem
Abstract: A number of exact algorithms have been developed to perform probabilistic inference in Bayesian belief networks in recent years. The techniques used in these algorithms are closely related to network structures and some of ... | [
5,
515,
1749,
2094,
2521
] | Train |
2,165 | 1 | Title: Auto-teaching: networks that develop their own teaching input
Abstract: Backpropagation learning (Rumelhart, Hinton and Williams, 1986) is a useful research tool but it has a number of undesiderable features such as having the experimenter decide from outside what should be learned. We describe a number of sim... | [
129,
538,
745,
1143,
2193,
2363
] | Train |
2,166 | 3 | Title: Probabilistic evaluation of counterfactual queries
Abstract: To appear in the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, WA, July 31 August 4, 1994. Technical Report R-213-A April, 1994 Abstract Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?... | [
260,
772,
776,
971,
1527,
2167,
2524
] | Train |
2,167 | 3 | Title: Counterfactuals and Policy Analysis in Structural Models
Abstract: Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is important to fault diagnosis, planning, determination of liability, and policy analysis. We present a method for evaluating counter-factuals when the unde... | [
772,
2088,
2161,
2166
] | Train |
2,168 | 6 | Title: Malicious Membership Queries and Exceptions
Abstract: Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is important to fault diagnosis, planning, determination of liability, and policy analysis. We present a method for evaluating counter-factuals when the underlying causal... | [
1363,
2350
] | Train |
2,169 | 3 | Title: Theory Refinement on Bayesian Networks
Abstract: Theory refinement is the task of updating a domain theory in the light of new cases, to be done automatically or with some expert assistance. The problem of theory refinement under uncertainty is reviewed here in the context of Bayesian statistics, a theory of b... | [
1290,
2420
] | Test |
2,170 | 1 | Title: Generalist and Specialist Behavior Due to Individual Energy Extracting Abilities.
Abstract: The emergence of generalist and specialist behavior in populations of neural networks is studied. Energy extracting ability is included as a property of an organism. In artificial life simulations with organisms living ... | [
1325,
2237
] | Train |
2,171 | 5 | Title: K unstliche Intelligenz Grdt: Enhancing Model-Based Learning for Its Application in Robot Navigation
Abstract: The emergence of generalist and specialist behavior in populations of neural networks is studied. Energy extracting ability is included as a property of an organism. In artificial life simulations wit... | [
344,
638,
2031,
2032
] | Test |
2,172 | 6 | Title: Tractability of Theory Patching
Abstract: In this paper we consider the problem of theory patching, in which we are given a domain theory, some of whose components are indicated to be possibly flawed, and a set of labeled training examples for the domain concept. The theory patching problem is to revise only t... | [
136,
159,
2692
] | Train |
2,173 | 1 | Title: Adapting Control Strategies for Situated Autonomous Agents
Abstract: This paper studies how to balance evolutionary design and human expertise in order to best design situated autonomous agents which can learn specific tasks. A genetic algorithm designs control circuits to learn simple behaviors, and given con... | [
163,
636,
846,
2204
] | Test |
2,174 | 4 | Title: The Role of the Trainer in Reinforcement Learning
Abstract: In this paper we propose a threestage incremental approach to the development of autonomous agents. We discuss some issues about the characteristics which differentiate reinforcement programs (RPs), and define the trainer as a particular kind of RP. W... | [
636,
764,
1573,
2687
] | Train |
2,175 | 1 | Title: The Troubling Aspects of a Building Block Hypothesis for Genetic Programming
Abstract: In this paper we carefully formulate a Schema Theorem for Genetic Programming (GP) using a schema definition that accounts for the variable length and the non-homologous nature of GP's representation. In a manner similar to ... | [
120,
163,
1009,
1257,
1362,
1696,
1719,
1745,
1940,
2087,
2206,
2249,
2250,
2259,
2361
] | Train |
2,176 | 2 | Title: An Analytical Framework for Local Feedforward Networks
Abstract: Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are referred to as spatially local networks. To understand these properties,... | [
1914,
2535
] | Test |
2,177 | 1 | Title: Analyzing Social Network Structures in the Iterated Prisoner's Dilemma with Choice and Refusal
Abstract: University of Wisconsin-Madison, Department of Computer Sciences Technical Report CS-TR-94-1259 Abstract The Iterated Prisoner's Dilemma with Choice and Refusal (IPD/CR) [46] is an extension of the Iterated... | [
163,
1883
] | Test |
2,178 | 2 | Title: Statistical Mechanics of Nonlinear Nonequilibrium Financial Markets: Applications to Optimized Trading
Abstract: A paradigm of statistical mechanics of financial markets (SMFM) using nonlinear nonequilibrium algorithms, first published in L. Ingber, Mathematical Modelling, 5, 343-361 (1984), is fit to multi-va... | [
1788,
1793,
1794,
1795,
2082,
2181,
2545,
2582
] | Train |
2,179 | 4 | Title: Scaling Reinforcement Learning Algorithms by Learning Variable Temporal Resolution Models
Abstract: The close connection between reinforcement learning (RL) algorithms and dynamic programming algorithms has fueled research on RL within the machine learning community. Yet, despite increased theoretical understa... | [
321,
2150,
2183
] | Validation |
2,180 | 6 | Title: Oblivious Decision Trees, Graphs, and Top-Down Pruning
Abstract: We describe a supervised learning algorithm, EODG, that uses mutual information to build an oblivious decision tree. The tree is then converted to an Oblivious read-Once Decision Graph (OODG) by merging nodes at the same level of the tree. For do... | [
1500,
2577
] | Validation |
2,181 | 2 | Title: Statistical mechanics of neocortical interactions: Training and testing canonical momenta indicators of EEG
Abstract: A series of papers has developed a statistical mechanics of neocortical interactions (SMNI), deriving aggregate behavior of experimentally observed columns of neurons from statistical electrica... | [
1788,
1793,
1795,
2143,
2178
] | Validation |
2,182 | 6 | Title: Weakly Learning DNF and Characterizing Statistical Query Learning Using Fourier Analysis
Abstract: We present new results, both positive and negative, on the well-studied problem of learning disjunctive normal form (DNF) expressions. We first prove that an algorithm due to Kushilevitz and Mansour [16] can be u... | [
591,
1003,
1748,
1835,
1897,
2011,
2146,
2633
] | Test |
2,183 | 4 | Title: Multi-time Models for Temporally
Abstract: Planning Abstract Planning and learning at multiple levels of temporal abstraction is a key problem for artificial intelligence. In this paper we summarize an approach to this problem based on the mathematical framework of Markov decision processes and reinforcement l... | [
1954,
2150,
2179,
2305
] | Train |
2,184 | 0 | Title: AN ARCHITECTURE FOR GOAL-DRIVEN EXPLANATION
Abstract: In complex and changing environments explanation must be a a dynamic and goal-driven process. This paper discusses an evolving system implementing a novel model of explanation generation | Goal-Driven Interactive Explanation | that models explanation as a g... | [
2398
] | Validation |
2,185 | 2 | Title: of nucleotide sites needed to accurately reconstruct large evolutionary trees 1
Abstract: DIMACS Technical Report 96-19 July 1996 | [
2109
] | Test |
2,186 | 2 | Title: A REMARK ON ROBUST STABILIZATION OF GENERAL ASYMPTOTICALLY CONTROLLABLE SYSTEMS
Abstract: It was shown recently by Clarke, Ledyaev, Sontag and Subbotin that any asymptotically controllable system can be stabilized by means of a certain type of discontinuous feedback. The feedback laws constructed in that work ... | [
2321
] | Test |
2,187 | 2 | Title: "UNIVERSAL" CONSTRUCTION OF ARTSTEIN'S THEOREM ON NONLINEAR STABILIZATION 1
Abstract: Report SYCON-89-03 ABSTRACT This note presents an explicit proof of the theorem -due to Artstein- which states that the existence of a smooth control-Lyapunov function implies smooth stabilizability. More- over, the result is... | [
531,
2314,
2321
] | Test |
2,188 | 5 | Title: Improving Software Pipelining With Unroll-and-Jam
Abstract: In this paper, we demonstrate how unroll-and-jam can significantly improve the initiation interval in a software-pipelined loop. Improvements in the initiation interval of greater than 40% are common, while dramatic improvements of a factor of 5 are p... | [
2149,
2189,
2190,
2194
] | Validation |
2,189 | 5 | Title: Stage Scheduling: A Technique to Reduce the Register Requirements of a Modulo Schedule
Abstract: Modulo scheduling is an efficient technique for exploiting instruction level parallelism in a variety of loops, resulting in high performance code but increased register requirements. We present a set of low comput... | [
2188,
2190,
2194,
2365
] | Train |
2,190 | 5 | Title: Minimum Register Requirements for a Modulo Schedule
Abstract: Modulo scheduling is an efficient technique for exploiting instruction level parallelism in a variety of loops, resulting in high performance code but increased register requirements. We present a combined approach that schedules the loop operations... | [
1955,
2149,
2188,
2189,
2194,
2365
] | Validation |
2,191 | 2 | Reference: [Tex89] <institution> Texas Instruments. </institution> <note> TMS320C30 C Compiler Reference Guide, 1989. Document Title: SPRU034A. </note>
Abstract: The design and implementation of software for the Ring Array Processor (RAP), a high performance parallel computer, involved development for three hardware pl... | [
362,
2275
] | Validation |
2,192 | 1 | Title: #1 Robust Feature Selection Algorithms
Abstract: Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive control, and machine learning. Our experience with traditional feature selection algori... | [
177,
1743
] | Train |
2,193 | 1 | Title: Growing neural networks
Abstract: Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive control, and machine learning. Our experience with traditional feature selection algorithms in the dom... | [
129,
538,
2165
] | Train |
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