Contributions to Deep Learning Models - RiuNet
... Deep Learning is a new area of Machine Learning research which aims to create computational models that learn several representations of the data using deep architectures. These methods have become very popular over the last few years due to the remarkable results obtained in speech recognition, vis ...
... Deep Learning is a new area of Machine Learning research which aims to create computational models that learn several representations of the data using deep architectures. These methods have become very popular over the last few years due to the remarkable results obtained in speech recognition, vis ...
Package `FCNN4R`
... Description Provides an interface to kernel routines from the FCNN C++ library. FCNN is based on a completely new Artificial Neural Network representation that offers unmatched efficiency, modularity, and extensibility. FCNN4R provides standard teaching (backpropagation, Rprop, simulated annealing, ...
... Description Provides an interface to kernel routines from the FCNN C++ library. FCNN is based on a completely new Artificial Neural Network representation that offers unmatched efficiency, modularity, and extensibility. FCNN4R provides standard teaching (backpropagation, Rprop, simulated annealing, ...
Comparative Table of Cognitive Architectures (started
... HTM is a biologically constrained model of neocortex and thalamus. HTM models cortex related to sensory perception, learning to infer and predict from high dimensional sensory data. The model starts with a hierarchy of memory nodes. Each node learns to pool spatial pattern using temporal contiguity ...
... HTM is a biologically constrained model of neocortex and thalamus. HTM models cortex related to sensory perception, learning to infer and predict from high dimensional sensory data. The model starts with a hierarchy of memory nodes. Each node learns to pool spatial pattern using temporal contiguity ...
Artificial Intelligence
... engineering. In the courses I teach, my students develop small rule-based and frame-based expert systems, design a fuzzy system, explore artificial neural networks, and implement a simple problem as a genetic algorithm. They use expert system shells (Leonardo, XpertRule, Level5 Object and Visual Rul ...
... engineering. In the courses I teach, my students develop small rule-based and frame-based expert systems, design a fuzzy system, explore artificial neural networks, and implement a simple problem as a genetic algorithm. They use expert system shells (Leonardo, XpertRule, Level5 Object and Visual Rul ...
Video Game Pathfinding and Improvements to Discrete Search on Grid-based Maps
... successfully navigate the game environment. Pathfinding is an essential component of any agent navigation system. Pathfinding is, at the simplest level, a search technique for finding a route between two points in an environment. The real-time multi-agent nature of video games places extremely tight ...
... successfully navigate the game environment. Pathfinding is an essential component of any agent navigation system. Pathfinding is, at the simplest level, a search technique for finding a route between two points in an environment. The real-time multi-agent nature of video games places extremely tight ...
artificial intelligence (luger, 6th, 2008)
... Intelligence is too complex to be described by any single theory; instead, researchers are constructing a hierarchy of theories that characterize it at multiple levels of abstraction. At the lowest levels of this hierarchy, neural networks, genetic algorithms and other forms of emergent computation ...
... Intelligence is too complex to be described by any single theory; instead, researchers are constructing a hierarchy of theories that characterize it at multiple levels of abstraction. At the lowest levels of this hierarchy, neural networks, genetic algorithms and other forms of emergent computation ...
Artificial Intelligence Illuminated
... The book assumes very little knowledge of computer science, but does assume some familiarity with basic concepts of algorithms and computer systems. Data structures such as trees, graphs, and stacks are explained briefly in this book, but if you do not already have some familiarity with these concep ...
... The book assumes very little knowledge of computer science, but does assume some familiarity with basic concepts of algorithms and computer systems. Data structures such as trees, graphs, and stacks are explained briefly in this book, but if you do not already have some familiarity with these concep ...
Aalborg Universitet
... This thesis is about decision theoretic troubleshooting (or simply troubleshooting) which in many ways can be seen as an exact science for "detection". However, at the core of decision theoretic troubleshooting is not only the goal of arriving at the true diagnosis or conclusion of a given problem, ...
... This thesis is about decision theoretic troubleshooting (or simply troubleshooting) which in many ways can be seen as an exact science for "detection". However, at the core of decision theoretic troubleshooting is not only the goal of arriving at the true diagnosis or conclusion of a given problem, ...
Biologically Inspired Modular Neural Networks
... Artificial intelligence is the study of intelligent behavior and how computer programs can be made to exhibit such behavior. There are two categories of artificial intelligence from the computational point of view. One is based on symbolism, and the other is based on connectionism. In the former app ...
... Artificial intelligence is the study of intelligent behavior and how computer programs can be made to exhibit such behavior. There are two categories of artificial intelligence from the computational point of view. One is based on symbolism, and the other is based on connectionism. In the former app ...
AgenaRisk
... Boer, R., S. Plevritis, et al. (2004). "Diversity of model approaches for breast cancer screening: a review of model assumptions by the Cancer Intervention and Surveillance Network (CISNET) Breast Cancer Groups." Stat Methods Med Res ...
... Boer, R., S. Plevritis, et al. (2004). "Diversity of model approaches for breast cancer screening: a review of model assumptions by the Cancer Intervention and Surveillance Network (CISNET) Breast Cancer Groups." Stat Methods Med Res ...
Speeding Up Problem-Solving by Abstraction: A Graph
... first, because it would have prevented us from executing the experiments on different CPUs; secondly, because it proved extremely sensitive to low-level programming details of no significance to the algorithms themselves; and finally, because our implementation is designed for flexibility (it is an ...
... first, because it would have prevented us from executing the experiments on different CPUs; secondly, because it proved extremely sensitive to low-level programming details of no significance to the algorithms themselves; and finally, because our implementation is designed for flexibility (it is an ...
Deep learning in neural networks: An overview
... real-valued activations. Input neurons get activated through sensors perceiving the environment, other neurons get activated through weighted connections from previously active neurons (details in Section 2). Some neurons may influence the environment by triggering actions. Learning or credit assign ...
... real-valued activations. Input neurons get activated through sensors perceiving the environment, other neurons get activated through weighted connections from previously active neurons (details in Section 2). Some neurons may influence the environment by triggering actions. Learning or credit assign ...
On the realization of asymmetric high radix signed digital
... This paper presents the asymmetric high-radix signed-digit (AHSD) number system using NN [4, 5]. The idea of AHSD is not new. A particular AHSD number system was introduced by others research paper “the radix-r stored-borrow” number system. Researchers earlier works have focused on binary stored-bor ...
... This paper presents the asymmetric high-radix signed-digit (AHSD) number system using NN [4, 5]. The idea of AHSD is not new. A particular AHSD number system was introduced by others research paper “the radix-r stored-borrow” number system. Researchers earlier works have focused on binary stored-bor ...
Inconsistent Heuristics in Theory and Practice
... expansion again. This phenomenon is known as node re-expansion. A* with an inconsistent heuristic may perform an exponential number of node re-expansions [32]. We present insights into this phenomenon, showing that the exponential time behavior only appears in contrived graphs where edge weights and ...
... expansion again. This phenomenon is known as node re-expansion. A* with an inconsistent heuristic may perform an exponential number of node re-expansions [32]. We present insights into this phenomenon, showing that the exponential time behavior only appears in contrived graphs where edge weights and ...
ABSTRACT HYBRID CAUSAL LOGIC Title:
... supported by an organization of people in charge of its operation, is at the cross-section of these environments. In order to develop a more comprehensive risk model for these systems, an important step is to extend the modeling capabilities of the conventional Probabilistic Risk Assessment methodol ...
... supported by an organization of people in charge of its operation, is at the cross-section of these environments. In order to develop a more comprehensive risk model for these systems, an important step is to extend the modeling capabilities of the conventional Probabilistic Risk Assessment methodol ...
PDF (Recognizing and Discovering Activities of Daily Living in Smart
... Designing a comprehensive activity recognition system that works on a real-world setting is extremely challenging because of the difficulty for computers to process the complex nature of the human behaviors. In the first part of this thesis we present a novel supervised approach to improve the activ ...
... Designing a comprehensive activity recognition system that works on a real-world setting is extremely challenging because of the difficulty for computers to process the complex nature of the human behaviors. In the first part of this thesis we present a novel supervised approach to improve the activ ...
Reservoir properties from well logs using neural networks
... porosity, permeability, partial fluid saturation and for identifying lithofacies from wireline and measurement while drilling (MWD) logs. The method is much more robust and accurate than a single network and the multiple linear regression method. The basic unit of a committee machine is a multilayer ...
... porosity, permeability, partial fluid saturation and for identifying lithofacies from wireline and measurement while drilling (MWD) logs. The method is much more robust and accurate than a single network and the multiple linear regression method. The basic unit of a committee machine is a multilayer ...
Dialectic proof procedures for assumption
... The notation A ` α encapsulates the essence of an argument, by focusing attention on its set of assumptions A and its conclusion α. Not only does this notation ignore the internal structure of the argument, namely the inference rules used to generate it, but it ignores the fact that there can be sev ...
... The notation A ` α encapsulates the essence of an argument, by focusing attention on its set of assumptions A and its conclusion α. Not only does this notation ignore the internal structure of the argument, namely the inference rules used to generate it, but it ignores the fact that there can be sev ...
Perceiving and Reasoning about a Changing World1
... about both persistence and change, using knowledge of causal processes. Building an artificial agent that is able to perform these cognitive feats is no less difficult than solving the philosophical problem of our knowledge of the external world. In fact, the best way to solve the engineering proble ...
... about both persistence and change, using knowledge of causal processes. Building an artificial agent that is able to perform these cognitive feats is no less difficult than solving the philosophical problem of our knowledge of the external world. In fact, the best way to solve the engineering proble ...
Logical Foundations for Belief Representation WILLIAM J.
... result of a (conscious) decision, or it might be merely accidental (a “behavior”). In the former case, it would be the end result of a chain of reasoning (a “plan”) that would include beliefs. An AI system (perhaps an intelligent robot) that would be capable of performing actions, or even a system t ...
... result of a (conscious) decision, or it might be merely accidental (a “behavior”). In the former case, it would be the end result of a chain of reasoning (a “plan”) that would include beliefs. An AI system (perhaps an intelligent robot) that would be capable of performing actions, or even a system t ...
Program Share and Design S. 19,
... apparent in the final artifact. Viewed from a procedural perspective, a program consists of a set of roles connected by linear order; this is the way a serial computer views a program. Viewed from a functional perspective, a program consists of a set of actions connected by data and control flow dep ...
... apparent in the final artifact. Viewed from a procedural perspective, a program consists of a set of roles connected by linear order; this is the way a serial computer views a program. Viewed from a functional perspective, a program consists of a set of actions connected by data and control flow dep ...
Dialectic proof procedures for assumption
... top-most level of constructive proof procedures, using logic program transformation techniques [31]. This top-most level generates defences incrementally, without showing how to construct them by means of a dialogue between a proponent and an opponent. In this paper we derive our (full) proof proced ...
... top-most level of constructive proof procedures, using logic program transformation techniques [31]. This top-most level generates defences incrementally, without showing how to construct them by means of a dialogue between a proponent and an opponent. In this paper we derive our (full) proof proced ...
Bayesian AI Introduction - Australasian Bayesian Network Modelling
... Definition (Markov Condition) There are no direct dependencies in the system being modeled which are not explicitly shown via arcs. ...
... Definition (Markov Condition) There are no direct dependencies in the system being modeled which are not explicitly shown via arcs. ...
Modeling Affection Mechanisms using Deep and Self
... Interaction Corpus, which contains interactions from different human-human and human-robot scenarios. The first of our models, named Cross-channel Convolution Neural Network (CCCNN), uses deep neural networks to learn how to represent and recognize spontaneous and multimodal audio-visual expressions ...
... Interaction Corpus, which contains interactions from different human-human and human-robot scenarios. The first of our models, named Cross-channel Convolution Neural Network (CCCNN), uses deep neural networks to learn how to represent and recognize spontaneous and multimodal audio-visual expressions ...
The Role of Temporal Structure in Human Vision
... Smith, Howell, & Stanley, 1982). Or consider another, slightly more complicated stimulus sequence, where a stimulus appears for 100 msec at one location, disappears very briefly, and then reappears for 100 msec at another, nearby location. If the two events occur within 20 msec or so of one another, ...
... Smith, Howell, & Stanley, 1982). Or consider another, slightly more complicated stimulus sequence, where a stimulus appears for 100 msec at one location, disappears very briefly, and then reappears for 100 msec at another, nearby location. If the two events occur within 20 msec or so of one another, ...
Hierarchical temporal memory
Hierarchical temporal memory (HTM) is an online machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world.Jeff Hawkins states that HTM does not present any new idea or theory, but combines existing ideas to mimic the neocortex with a simple design that provides a large range of capabilities. HTM combines and extends approaches used in Sparse distributed memory, Bayesian networks, spatial and temporal clustering algorithms, while using a tree-shaped hierarchy of nodes that is common in neural networks.