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检索条件"主题词=Inference Algorithms"

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Hidden mode HMM using Bayesian network for modeling speaking rate fluctuation

Hidden mode HMM using Bayesian network for modeling speaking...

引用

IEEE Workshop on Automatic Speech Recognition and Understanding

作者： T. Shinozaki S. Furui Department of Computer Science Tokyo Institute of Technology Japan

One of the most important issues in spontaneous speech recognition is how to cope with the degradation of recognition accuracy due to speaking rate fluctuation within an utterance. This paper proposes an acoustic model for adjusting mixture weights and transition probabilities of the HMM for each frame according to the local speaking rate. The proposed model is implemented along with variants and conventional models using the Bayesian network framework. The proposed model has a hidden variable representing variation of the "mode" of the speaking rate and its value controls the parameters of the underlying HMM. Model training and maximum probability assignment of the variables are conducted using the EM/GEM and inference algorithms for Bayesian networks. Utterances from meetings and lectures are used for evaluation where Bayesian network-based acoustic models are used to rescore the utterance hypotheses obtained from a first-pass N-best list. In the experiments, the proposed model shows consistently higher performance than conventional models.

关键词： Hidden Markov models Bayesian methods Fluctuations Speech recognition Computer science Degradation inference algorithms Text recognition Acoustic testing Decoding

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On Geometric Structure of Quasi-Additive Learning algorithms

On Geometric Structure of Quasi-Additive Learning Algorithms

引用

International Joint Conference on Neural Networks (IJCNN)

作者： K. Ikeda Department of Systems Science Kyoto University Kyoto Japan

Quasi-additive (QA) algorithms are a kind of online learning algorithms having two parameter vectors: one is an accumulation of input vectors and the other is a weight vector for prediction associated with the former by a non-linear function. We show that the vectors have a dually-flat structure from the information-geometric point of view, which makes it easier to discuss the convergence properties of the algorithms, as presented here.

关键词： Information geometry Convergence Neural networks Nonlinear equations inference algorithms Information analysis Algorithm design and analysis Information theory Mathematical programming Physics

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Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets

Learning for Structured Prediction Using Approximate Subgrad...

引用

IEEE Conference on Computer Vision and Pattern Recognition

作者： Aurelien Lucchi Yunpeng Li Pascal Fua Computer Vision Laboratory EPFL

ISBN: (纸本)9781467364102

We propose a working set based approximate subgradient descent algorithm to minimize the margin-sensitive hinge loss arising from the soft constraints in max-margin learning frameworks, such as the structured SVM. We focus on the setting of general graphical models, such as loopy MRFs and CRFs commonly used in image segmentation, where exact inference is intractable and the most violated constraints can only be approximated, voiding the optimality guarantees of the structured SVM's cutting plane algorithm as well as reducing the robustness of existing sub gradient based methods. We show that the proposed method obtains better approximate subgradients through the use of working sets, leading to improved convergence properties and increased reliability. Furthermore, our method allows new constraints to be randomly sampled instead of computed using the more expensive approximate inference techniques such as belief propagation and graph cuts, which can be used to reduce learning time at only a small cost of performance. We demonstrate the strength of our method empirically on the segmentation of a new publicly available electron microscopy dataset as well as the popular MSRC data set and show state-of-the-art results.

关键词： Labeling Fasteners inference algorithms Approximation algorithms Training Image segmentation Convergence

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A Novel Dynamic Spectrum Access Strategy Applied to Cognitive Radio Network

A Novel Dynamic Spectrum Access Strategy Applied to Cognitiv...

引用

International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Xuchen Liu Wenzhu Zhang

This paper proposes a dynamic spectrum access (DSA) strategy in cognitive radio (CR) network. This strategy combines fuzzy inference and reinforcement learning theory to build knowledge on network status from the current state and past experience. Multiple assessment variables on environment performance and preference information are introduced to regulate decision-making behavior. The proposed aims at making optimal spectrum access action and obtaining long-term rewards on desired network-wide objectives. We adopt distribute DSA architecture in which cognitive radio network access points (AP) executive control strategy and provide CR network access for unlicensed users. Numerical results show that our algorithm can dramatically promote efficient use of spectrum resource compared to other spectrum access methods, and gain good rewards on the desirable objectives.

关键词： Cognitive radio Decision making Learning Educational institutions inference algorithms Convergence Interference

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Incremental DCOP Search algorithms for Solving Dynamic DCOP Problems

Incremental DCOP Search Algorithms for Solving Dynamic DCOP ...

引用

IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： William Yeoh Pradeep Varakantham Xiaoxun Sun Sven Koenig Department of Computer Science New Mexico State University School of Information Systems Singapore Management University Google Inc Mountain View CA US Department of Computer Science University of Southern California

ISBN: (纸本)9781467396196

Distributed constraint optimization (DCOP) problems are well-suited for modeling multi-agent coordination problems. However, it only models static problems, which do not change over time. Consequently, researchers have introduced the Dynamic DCOP (DDCOP) model to model dynamic problems. In this paper, we make two key contributions: (a) a procedure to reason with the incremental changes in DDCOP problems and (b) an incremental pseudo-tree construction algorithm that can be used by DCOP algorithms such as any-space ADOPT and any-space BnB-ADOPT to solve DDCOP problems. Due to the incremental reasoning employed, our experimental results show that any-space ADOPT and any-space BnB-ADOPT are up to 42% and 38% faster, respectively, with the incremental procedure and the incremental pseudo-tree reconstruction algorithm than without them.

关键词： Search problems Heuristic algorithms Upper bound Computational modeling Context inference algorithms Computer science

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Comparative analysis of intelligent hybrid systems for detection of PIMA indian diabetes

Comparative analysis of intelligent hybrid systems for detec...

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： Rahul Kala Anupam Shukla Ritu Tiwari Department of Information Technology Indian Institute of Information Technology and Management Gwalior Madhya Pradesh India

The past few years have seen a lot of applications of Hybrid Soft Computing approaches that seem to have completely replaced the traditional uni-system approaches. The added abilities that come from the hybrid approaches motivate their use in every system. Bio-Medical Engineering is yet another field which has seen a major change in the past few years. We find various new approaches being applied to this field as well as many new models being proposed. At this juncture, we study the effectiveness of various new hybrid approaches in the field of Bio-medicals in this paper. PIMA Indian database has been used for this purpose from the UCI Machine Learning Repository. The basic aim is to compare the various hybrid approaches from the recent literature and compare their performances. We have chosen 3 major Hybrid Systems and standard Back Propagation Algorithm for this purpose. These are Adaptive Neuro Fuzzy inference Systems, Ensembles and Evolutionary Artificial Neural Networks. We also try to explain the results from our theoretical understanding of the individual Hybrid Systems.

关键词： Hybrid intelligent systems Diabetes Systems engineering and theory Databases Machine learning Machine learning algorithms inference algorithms Fuzzy neural networks Fuzzy systems Artificial neural networks

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Achieving Multitasking Robots in Multi-Robot Tasks

Achieving Multitasking Robots in Multi-Robot Tasks

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Winston Smith Yu Zhang School of Computing Informatics and Decision Systems Engineering Arizona State University

One simplifying assumption made in the existing and well-performing multi-robot systems is that the robots are single-tasking: each robot operates on a single task at any time. While this assumption is innocent to make in situations with sufficient resources such that robots can work independently, it becomes a restriction when they must share capabilities. In this paper, we consider multitasking robots with multi-robot tasks. Given a set of tasks, each achievable by a coalition of robots, our approach allows the coalitions to overlap by exploiting task synergies based on the physical constraints required to maintain these coalitions. The key contribution is a general and flexible framework that extends the current multi-robot systems to enable multitasking. The proposed approach is inspired by the information invariant theory, which orients around the equivalence of different information requirements. We map physical constraints to information requirements in our work, thereby allowing task synergies to be identified by reasoning about the relationships between such requirements. We show that our algorithm is sound and complete. Simulation results show its effectiveness under resource-constrained situations and in handling challenging scenarios in a realistic UAV simulator.

关键词： Simulation Conferences Multitasking Cognition inference algorithms Multi-robot systems Object recognition

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Efficient processing of MRFs for unconstrained-pose face recognition

Efficient processing of MRFs for unconstrained-pose face rec...

引用

IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS)

作者： Shervin Rahimzadeh Arashloo Josef Kittler Department of electrical engineering Urmia university Urmia Iran CVSSP University of Surrey Guildford Surrey UK

The paper addresses the problem of pose-invariant recognition of faces via an MRF matching model. Unlike previous costly matching approaches, the proposed algorithm employs effective techniques to reduce the MRF inference time. To this end, processing is done in a parallel fashion on a GPU employing a dual decomposition framework. The optimisation is further accelerated taking a multi-resolution approach based on the Renormalisation Group Theory (RGT) along with efficient methods for message passing and the incremental subgradient approach. For the graph construction, Daisy features are used as node attributes exhibiting high cross-pose invariance, while high discriminatory capability in the classification stage is obtained via multi-scale LBP histograms. The experimental evaluation of the method is performed via extensive tests on the databases of XM2VTS, FERET and LFW in verification, identification and the unseen pair-matching paradigms. The proposed approach achieves state-of-the-art performance in pose-invariant recognition of faces and performs as well or better than the existing methods in the unconstrained settings of the challenging LFW database using a single feature for classification.

关键词： Face Face recognition Databases Graphics processing units Vectors inference algorithms Message passing

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An Intelligent Switching Controller for A Plug-in Hybrid Electric Vehicle- A comparative analysis

An Intelligent Switching Controller for A Plug-in Hybrid Ele...

引用

Smart Electronics and Communication (ICOSEC), International Conference on

作者： K. Sai Dileep Kumar Reddy M. Lokesh Reddy Diddi Ramakrishna K. Sireesha Department of Electrical and Electronics Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bangalore India

ISBN: (数字)9798331504403

ISBN: (纸本)9798331504410

This research study explores a variety of control strategies that utilise advanced technologies to regulate hybrid electric vehicles (HEVs). A controller that can adaptively switch between different modes has been designed and simulated using the MATLAB/Simulink ${ }^{\circledR}$ platform for Hybrid Electric Vehicles (HEVs).The simulation results of Fuzzy-tuned proportional integral derivative (F-PID) and Genetic Algorithm (GA) tuned PID controllers are systematically evaluated, and a comparative study of fuzzy-PID and GA-PID is presented.

关键词： Simulation Switches Control systems inference algorithms Combustion Hybrid electric vehicles MATLAB Engines Genetic algorithms

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Fuzzy logic extends a general purpose instruction set

Fuzzy logic extends a general purpose instruction set

引用

Northcon

作者： J.M. Sibigtroth Motorola Inc. Austin TX USA

By extending the general purpose instruction set of the CPU12 to include four new fuzzy logic instructions, the 16-bit MC68HC12 gains more than an order of magnitude improvement in execution speed for a fuzzy inference program compared to the 8-bit MCS8HC11. Coding is also dramatically simplified by reducing a 250 byte program to about 50 bytes. At the same time, re-use of existing logic in the CPU allows these additions without increasing the die size (and thus cost) of the MCU. The general purpose instruction set provides the means for programming non-fuzzy portions of the embedded control application as well as large portions of the inference program itself. This makes it possible for the fuzzy instructions to be focused on the portions of the fuzzy algorithm where they can produce the most benefits. Any of the specialized fuzzy instructions can be replaced by an alternate algorithm coded with traditional general purpose instructions. This provides a great deal of flexibility not found in hardware approaches.

关键词： Fuzzy sets Fuzzy logic inference algorithms Application software Hardware Workstations Fuzzy control Table lookup Control systems Software performance

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