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Fast Kernel Classifiers With Online And Active Learning
 JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... Very high dimensional learning systems become theoretically possible when training examples are abundant. The computing cost then becomes the limiting factor. Any efficient learning algorithm should at least take a brief look at each example. But should all examples be given equal attention? This ..."
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Cited by 153 (18 self)
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Very high dimensional learning systems become theoretically possible when training examples are abundant. The computing cost then becomes the limiting factor. Any efficient learning algorithm should at least take a brief look at each example. But should all examples be given equal attention
Algorithms for Sequential Decision Making
, 1996
"... Sequential decision making is a fundamental task faced by any intelligent agent in an extended interaction with its environment; it is the act of answering the question "What should I do now?" In this thesis, I show how to answer this question when "now" is one of a finite set of ..."
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Cited by 213 (8 self)
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of states, "do" is one of a finite set of actions, "should" is maximize a longrun measure of reward, and "I" is an automated planning or learning system (agent). In particular,
What Should a Classifier System Learn?
"... We consider the issue of how a classifier system should learn to represent a Boolean function. We identify four properties which may be desirable of a representation; that it be complete, accurate, minimal and nonoverlapping, and distinguish variations on two of these properties for the XCS system. ..."
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Cited by 9 (3 self)
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We consider the issue of how a classifier system should learn to represent a Boolean function. We identify four properties which may be desirable of a representation; that it be complete, accurate, minimal and nonoverlapping, and distinguish variations on two of these properties for the XCS system
Behavioral theories and the neurophysiology of reward,
 Annu. Rev. Psychol.
, 2006
"... ■ Abstract The functions of rewards are based primarily on their effects on behavior and are less directly governed by the physics and chemistry of input events as in sensory systems. Therefore, the investigation of neural mechanisms underlying reward functions requires behavioral theories that can ..."
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Cited by 187 (0 self)
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emotional states of anger, fear, and panic. NEUROPHYSIOLOGY OF REWARD BASED ON ANIMAL LEARNING THEORY Primary Reward Neurons responding to liquid or food rewards are found in a number of brain structures, such as orbitofrontal, premotor and prefrontal cortex, striatum, amygdala, and dopamine neurons
Efficient Memorybased Learning for Robot Control
, 1990
"... This dissertation is about the application of machine learning to robot control. A system which has no initial model of the robot/world dynamics should be able to construct such a model using data received through its sensorsan approach which is formalized here as the $AB (StateActionBehaviour) ..."
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Cited by 120 (3 self)
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This dissertation is about the application of machine learning to robot control. A system which has no initial model of the robot/world dynamics should be able to construct such a model using data received through its sensorsan approach which is formalized here as the $AB (StateAction
Schema Design and Implementation of the GraspRelated Mirror Neuron System
 BIOLOGICAL CYBERNETICS
, 2002
"... Mirror neurons within a monkey's premotor area F5 fire not only when the monkey performs a certain class of actions but also when the monkey observes another monkey (or the experimenter) perform a similar action. It has thus been argued that these neurons are crucial for understanding of action ..."
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Cited by 110 (8 self)
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multijoint 3D kinematics simulator, and a learning neural network, respectively). With this implementation we show how the mirror system may learn to recognize actions already in the repertoire of the F5 canonical neurons. We show that the connectivity pattern of mirror neuron circuitry can be established
Hyperheuristics and Classifier Systems for . . .
, 2005
"... This paper presents a method for combining concepts of Hyperheuristics and Learning Classifier Systems for solving 2D Cutting Stock Problems. The idea behind Hyperheuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. To be worthwhile, such combi ..."
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, such combination should outperform the single heuristics. In this paper, the Hyperheuristic is formed using a XCStype Learning Classifier System which learns a solution procedure when solving individual problems. The XCS evolves a behavior model which determines the possible actions (selection and placement
Whom You Know Matters: Venture Capital Networks and Investment Performance,
 Journal of Finance
, 2007
"... Abstract Many financial markets are characterized by strong relationships and networks, rather than arm'slength, spotmarket transactions. We examine the performance consequences of this organizational choice in the context of relationships established when VCs syndicate portfolio company inv ..."
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Cited by 138 (8 self)
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focus on how each measure captures a slightly different aspect of a VC's economic role in the network. 3 See Wasserman and Faust (1997) for a detailed review of network analysis methods. 4 For tractability, the graph excludes biotechfocused VC firms that have no syndication relationships during
doi:10.1112/jlms/jdm031 CELLULARIZATION OF CLASSIFYING SPACES AND FUSION PROPERTIES OF FINITE GROUPS
"... One way to understand the mod p homotopy theory of classifying spaces of finite groups is to compute their BZ/pcellularization. In the easiest cases this is a classifying space of a finite group (always a finite pgroup). If not, we show that it has infinitely many nontrivial homotopy groups. More ..."
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One way to understand the mod p homotopy theory of classifying spaces of finite groups is to compute their BZ/pcellularization. In the easiest cases this is a classifying space of a finite group (always a finite pgroup). If not, we show that it has infinitely many nontrivial homotopy groups
Materials for an exploratory theory of the network society.
 The British Journal of Sociology
, 2000
"... ABSTRACT This article aims at proposing some elements for a grounded theor y of the network society. The network society is the social structure characteristic of the Information Age, as tentatively identi ed by empirical, crosscultural investigation. It permeates most societies in the world, in v ..."
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Cited by 122 (0 self)
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organizational forms, rooted in a different social logic. In this sense, they tend to assert the predominance of social morphology over social action. Let me clarify the meaning of this statement by entering into the heart of the argument, that is, by examining how speci cally the introduction of information 16
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