Machine learning for information retrieval: Neural networks
... cinctly identify relevant documents and reject irrelevant documents. Since it is often difficult to accomplish a successful searchat the initial try, it is customary to conduct searches iteratively and reformulate query statements based on evaluation of the previously retrieved documents. One method ...
... cinctly identify relevant documents and reject irrelevant documents. Since it is often difficult to accomplish a successful searchat the initial try, it is customary to conduct searches iteratively and reformulate query statements based on evaluation of the previously retrieved documents. One method ...
Machine Learning meets Knowledge Representation in the
... Clash is an obvious contradiction, e.g., A(x), :A(x) ...
... Clash is an obvious contradiction, e.g., A(x), :A(x) ...
Normative schemas
... technical problems have arisen in simulating particular cognitive abilities. Also many serious philosophical objections have been rised regarding possibility of overall algorithmization of cognitive processes (Penrose 2001, Searle 1980). All the above problems have not changed the fact, that science ...
... technical problems have arisen in simulating particular cognitive abilities. Also many serious philosophical objections have been rised regarding possibility of overall algorithmization of cognitive processes (Penrose 2001, Searle 1980). All the above problems have not changed the fact, that science ...
PVLV: The Primary Value and Learned Value
... The TD algorithm corrects this critical limitation of the Rescorla–Wagner algorithm by adopting a temporally extended prediction framework, where the objective is to predict future rewards not just present rewards. The consequence of this is that the ␦t at one point in time drives learning based on ...
... The TD algorithm corrects this critical limitation of the Rescorla–Wagner algorithm by adopting a temporally extended prediction framework, where the objective is to predict future rewards not just present rewards. The consequence of this is that the ␦t at one point in time drives learning based on ...
Lecture 11: Neural Nets
... Note that neural nets are inspired by the organisation of brain tissue, but the resemblance is not necessarily very close. Claims that a particular type of artificial neural net has been shown to demonstrate some property, and that this 'explains' the working of the human brain, should be treated ...
... Note that neural nets are inspired by the organisation of brain tissue, but the resemblance is not necessarily very close. Claims that a particular type of artificial neural net has been shown to demonstrate some property, and that this 'explains' the working of the human brain, should be treated ...
Reinforcement learning, conditioning, and the brain
... learning. The distinction between habits and goal-directed actions maps directly onto the distinction between modelfree and model-based reinforcement learning (Daw, Niv, & Dayan, 2005, 2006), as discussed in more detail below. In short, a full appreciation of modern ideas concerning classical condit ...
... learning. The distinction between habits and goal-directed actions maps directly onto the distinction between modelfree and model-based reinforcement learning (Daw, Niv, & Dayan, 2005, 2006), as discussed in more detail below. In short, a full appreciation of modern ideas concerning classical condit ...
Probabilistic graphical models in artificial intelligence
... 1. Introduction Although probabilistic methods are now fundamental for building intelligent systems, this has not always been the case. In the early years of artificial intelligence (years characterized by excessive enthusiasm), probability was not considered to be a basic tool. Researchers were mor ...
... 1. Introduction Although probabilistic methods are now fundamental for building intelligent systems, this has not always been the case. In the early years of artificial intelligence (years characterized by excessive enthusiasm), probability was not considered to be a basic tool. Researchers were mor ...
Effective and Efficient Microprocessor Design Space Exploration
... and the trained models are black-boxes that could not offer insights about how different design parameters affect the performance or energy of microprocessors. To circumvent these deficiencies of previous techniques, in this paper, we propose the COMT (Co-Training Model Tree) approach for the challe ...
... and the trained models are black-boxes that could not offer insights about how different design parameters affect the performance or energy of microprocessors. To circumvent these deficiencies of previous techniques, in this paper, we propose the COMT (Co-Training Model Tree) approach for the challe ...
sv-lncs
... determined by two basic issues. First, one must decide the search starting point (or points) which in turn influences the search direction. Search may start with an empty set and successively add features (i.e., forward), or start with a full set and successively remove features (i.e., backward), or ...
... determined by two basic issues. First, one must decide the search starting point (or points) which in turn influences the search direction. Search may start with an empty set and successively add features (i.e., forward), or start with a full set and successively remove features (i.e., backward), or ...
1pp
... • However, real-world tasks are not well-defined. For example, the web ranking task is to output the 10 most pages relevant to a user’s query. What does ”relevant” mean? • Our strategy is not to develop algorithms for solving real-world tasks directly, but rather to convert them via a process calle ...
... • However, real-world tasks are not well-defined. For example, the web ranking task is to output the 10 most pages relevant to a user’s query. What does ”relevant” mean? • Our strategy is not to develop algorithms for solving real-world tasks directly, but rather to convert them via a process calle ...
Levels of Organization in General Intelligence
... Is either introspection or evolutionary argument relevant to AI? To what extent can truths about humans be used to predict truths about AIs, and to what extent does knowledge about humans enable us to create AI designs? If the sole purpose of AI as a research field is to test theories about human co ...
... Is either introspection or evolutionary argument relevant to AI? To what extent can truths about humans be used to predict truths about AIs, and to what extent does knowledge about humans enable us to create AI designs? If the sole purpose of AI as a research field is to test theories about human co ...
Can Word Probabilities from LDA be Simply Added up to Represent
... modeling. LDA topic model provides topic proportions as a vector representation of document. We investigated an alternative way of document representation by summing up word probabilities from LDA topic model. The new representation is compared with the topic proportion representation as input of a ...
... modeling. LDA topic model provides topic proportions as a vector representation of document. We investigated an alternative way of document representation by summing up word probabilities from LDA topic model. The new representation is compared with the topic proportion representation as input of a ...
Class Library Implementation of an Open Architecture Knowledge
... article analyzes the structure of such a class library that supports the rapid prototyping of a wide range of systems including collaborative networking, shared documents, hypermedia, machine learning, knowledge acquisition and knowledge representation, and various combinations of these technologies ...
... article analyzes the structure of such a class library that supports the rapid prototyping of a wide range of systems including collaborative networking, shared documents, hypermedia, machine learning, knowledge acquisition and knowledge representation, and various combinations of these technologies ...
Main Areas of AI
... • If computers are intelligent what civil rights should be given to computers? • If computers can perform most of our work; what should the human beings do? • Only those things that can be represented in computers are important. • It is fun to play with computers. ...
... • If computers are intelligent what civil rights should be given to computers? • If computers can perform most of our work; what should the human beings do? • Only those things that can be represented in computers are important. • It is fun to play with computers. ...
TagSpace: Semantic Embeddings from Hashtags
... Neural networks in general have also been applied to part-of-speech tagging, chunking, named entity recognition (Collobert et al., 2011; Turian et al., 2010), and sentiment detection (Socher et al., 2013). All these tasks involve predicting a limited (2-30) number of labels. In this work, we make us ...
... Neural networks in general have also been applied to part-of-speech tagging, chunking, named entity recognition (Collobert et al., 2011; Turian et al., 2010), and sentiment detection (Socher et al., 2013). All these tasks involve predicting a limited (2-30) number of labels. In this work, we make us ...
Multi-objective optimization of support vector machines
... step-size through a wide range of values and the performance of every combination is measured. Because of its computational complexity, grid-search is only suitable for the adjustment of very few parameters. Further, the choice of the discretization of the search space may be crucial. Perhaps the mo ...
... step-size through a wide range of values and the performance of every combination is measured. Because of its computational complexity, grid-search is only suitable for the adjustment of very few parameters. Further, the choice of the discretization of the search space may be crucial. Perhaps the mo ...
An Overview of Some Recent Developments in Bayesian Problem
... theory for designing agents capable of reasoning and acting under conditions of uncertainty. This normativity is expressed in the form of a representation theorem stating that if an agent’s preferences obey a set of intuitively appealing constraints, then there exists a probability function P and a ...
... theory for designing agents capable of reasoning and acting under conditions of uncertainty. This normativity is expressed in the form of a representation theorem stating that if an agent’s preferences obey a set of intuitively appealing constraints, then there exists a probability function P and a ...
Person Movement Prediction Using Neural Networks
... The input layer: If we use a global predictor the network’s input data consists of two codes: the code of the person and the code of the last rooms visited by that person. If we treat each person separately with his/her own predictor, the input data only consists of the codes of the last visited roo ...
... The input layer: If we use a global predictor the network’s input data consists of two codes: the code of the person and the code of the last rooms visited by that person. If we treat each person separately with his/her own predictor, the input data only consists of the codes of the last visited roo ...
Dropout as a Bayesian Approximation: Representing Model
... Standard deep learning tools for regression and classification do not capture model uncertainty. In classification, predictive probabilities obtained at the end of the pipeline (the softmax output) are often erroneously interpreted as model confidence. A model can be uncertain in its predictions eve ...
... Standard deep learning tools for regression and classification do not capture model uncertainty. In classification, predictive probabilities obtained at the end of the pipeline (the softmax output) are often erroneously interpreted as model confidence. A model can be uncertain in its predictions eve ...
Integrated cognitive architectures: a survey | SpringerLink
... monitor hand movement. The visual buffers in this model include both the dorsal ‘where’ path of visual system and the ventral ‘what’ system. The dorsal ‘where’ system is important for locating the object, while the ventral ‘what’ system tracks visual objects and their identities. The various buffers ...
... monitor hand movement. The visual buffers in this model include both the dorsal ‘where’ path of visual system and the ventral ‘what’ system. The dorsal ‘where’ system is important for locating the object, while the ventral ‘what’ system tracks visual objects and their identities. The various buffers ...
Learning Action Models for Multi-Agent Planning
... might interfere with φi ’s action. Creating action models for these agents by hand is difficult and time-consuming due to the complex interactions among agents. Our objective is to explore learning algorithms that can automatically learn action models in multi-agent environments that can then be fed ...
... might interfere with φi ’s action. Creating action models for these agents by hand is difficult and time-consuming due to the complex interactions among agents. Our objective is to explore learning algorithms that can automatically learn action models in multi-agent environments that can then be fed ...
Hybrid Inductive Machine Learning: An Overview of CLIP Algorithms
... (characterization) learning. In theory, it is possible to transform a supervised machine learning algorithm into an unsupervised one (Langley, 1996) by running the supervised algorithm as many times as there are features describing the examples, each time with a different feature playing the role of ...
... (characterization) learning. In theory, it is possible to transform a supervised machine learning algorithm into an unsupervised one (Langley, 1996) by running the supervised algorithm as many times as there are features describing the examples, each time with a different feature playing the role of ...
FeUdal Networks for Hierarchical Reinforcement
... mains a major challenge for these methods, especially in environments with sparse reward signals, such as the infamous Montezuma’s Revenge ATARI game. It is symptomatic that the standard approach on the ATARI benchmark suite (Bellemare et al., 2012) is to use an actionrepeat heuristic, where each ac ...
... mains a major challenge for these methods, especially in environments with sparse reward signals, such as the infamous Montezuma’s Revenge ATARI game. It is symptomatic that the standard approach on the ATARI benchmark suite (Bellemare et al., 2012) is to use an actionrepeat heuristic, where each ac ...
AutoTutor: A tutor with dialogue in natural language
... NLD is feasible when the shared knowledge (i.e., common ground) between the tutor and the learner is low or moderate rather than high. If the common ground is high, then both dialogue participants (i.e., the computer tutor and the learner) will be expecting a more precise degree of mutual understand ...
... NLD is feasible when the shared knowledge (i.e., common ground) between the tutor and the learner is low or moderate rather than high. If the common ground is high, then both dialogue participants (i.e., the computer tutor and the learner) will be expecting a more precise degree of mutual understand ...
PDF
... The Actor/Critic architecture is by no means the only solution to the credit assignment problem – it is certainly not the most efficient solution or computationally sound option (see Sutton and Barto, 1998 for a variety of other reinforcement learning algorithms). However, converging behavioral, ana ...
... The Actor/Critic architecture is by no means the only solution to the credit assignment problem – it is certainly not the most efficient solution or computationally sound option (see Sutton and Barto, 1998 for a variety of other reinforcement learning algorithms). However, converging behavioral, ana ...