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检索条件"主题词=Inference algorithms"

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An algorithm of extracting fuzzy rules directly from numerical examples by using FNN

An algorithm of extracting fuzzy rules directly from numeric...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Lili Rong Zhongtuo Wang Institute of Systems Engineering Dalian University of Technology Dalian China

ISBN: (纸本)0780332806

In this paper, a general method to obtain fuzzy rules directly from numerical data is proposed. The membership function of antecedent part and consequent part is determined by calculating the variance and expectation of the examples. The extraction of fuzzy rules is done by using a fuzzy neural network. The algorithm has two parts. The first part is to determine the optimal number of fuzzy rules. The second part is to improve the accuracy of the inference system. The structure of the FNN is different from previous methods. In the rule layer, there are three counters in each node in order to calculate the maximum degree and the probability of the rule. The output of the node and the weight connecting to the next layer depend on the contents of these counters. From these counters, we can obtain the useful fuzzy rules. The backpropagation learning method is used to improve the accuracy of the system. Finally, through a simulation example, the effectiveness of the proposed algorithm is verified.

关键词： Fuzzy neural networks Fuzzy control Data mining Counting circuits Fuzzy systems Learning systems inference algorithms Probability Joining processes Systems engineering and theory

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Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers

Influence-Driven Data Poisoning in Graph-Based Semi-Supervis...

引用

AI Engineering - Software Engineering for AI (WAIN), IEEE/ACM Workshop on

作者： Adriano Franci Maxime Cordy Martin Gubri Mike Papadakis Yves Le Traon SnT Universit&#x00E9 de Luxembourg Luxembourg

ISBN: (纸本)9781665452069

Graph-based Semi-Supervised Learning (GSSL) is a practical solution to learn from a limited amount of labelled data together with a vast amount of unlabelled data. However, due to their reliance on the known labels to infer the unknown labels, these algorithms are sensitive to data quality. It is therefore essential to study the potential threats related to the labelled data, more specifically, label poisoning. In this paper, we propose a novel data poisoning method which efficiently approximates the result of label inference to identify the inputs which, if poisoned, would produce the highest number of incorrectly inferred labels. We extensively evaluate our approach on three classification problems under 24 different experimental settings each. Compared to the state of the art, our influence-driven attack produces an average increase of error rate 50% higher, while being faster by multiple orders of magnitude. Moreover, our method can inform engineers of inputs that deserve investigation (relabelling them) before training the learning model. We show that relabelling one-third of the poisoned inputs (selected based on their influence) reduces the poisoning effect by 50%. ACM Reference Format: Adriano Franci, Maxime Cordy, Martin Gubri, Mike Papadakis, and Yves Le Traon. 2022. Influence-Driven Data Poisoning in Graph-Based Semi-Supervised Classifiers. In 1st Conference on AI Engineering - Software Engineering for AI (CAIN’22), May 16–24, 2022, Pittsburgh, PA, USA. ACM, New York, NY, USA, 11 pages. https://***/10.1145/3522664.3528606

关键词： Measurement Training Error analysis Data integrity Semisupervised learning Approximation algorithms inference algorithms

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A first-order theory of types and polymorphism in logic programming

A first-order theory of types and polymorphism in logic prog...

引用

Annual Symposium on Logic in Computer Science

作者： M. Kifer J. Wu Department of Computer Science SUNY at Stony Brook Stony Brook NY USA

A logic called typed predicate calculus (TPC) that gives declarative meaning to logic programs with type declarations and type inference is introduced. The proper interaction between parametric and inclusion varieties of polymorphism is achieved through a construct called type dependency, which is analogous to implication types but yields more natural and succinct specifications. Unlike other proposals where typing has extra-logical status, in TPC the notion of type-correctness has precise model-theoretic meaning that is independent of any specific type-checking or type-inference procedure. Moreover, many different approaches to typing that were proposed in the past can be studied and compared within the framework of TPC. Another novel feature of TPC is its reflexivity with respect to type declarations; in TPC, these declarations can be queried the same way as any other data. Type reflexivity is useful for browsing knowledge bases and, potentially, for debugging logic programs.< >

关键词： Logic programming Computer science Proposals Debugging Protection Jacobian matrices Program processors inference algorithms

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Detection of Pill Intake Associated Gestures using Smart Wearables and Machine Learning

Detection of Pill Intake Associated Gestures using Smart Wea...

引用

International Symposium on Computational Intelligence and Informatics

作者： Dacian Avramoni Roxana Virlan Lucian Prodan Alexandru Iovanovici Department of Computer and Information Technology Politehnica University Timisoara

ISBN: (纸本)9798350398830

Gesture identification represents one way of monitoring adherence to medical treatment for cognitive-impaired individuals, dementia-related conditions being severely dependent on precise medication. This paper proposes a gesture identification algorithm used to detect the pill ingestion, that runs on an inexpensive smart wearable device. We use techniques pertaining to supervised machine learning and the data set is processed with the Keras framework. Data collected is represented by acceleration values supplied by the wearable and is proceed on the wearable device itself, showing high accuracy results in identifying the pill intake gesture. The trained model is deployed in a resource constrained embedded device and the inferences is carried locally onto the device.

关键词： Training Machine learning algorithms Wearable computers Medical treatment Machine learning inference algorithms Object recognition

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Multi-Level Fuzzy Score Fusion for Client Specific Linear Discriminant Analysis Based Face Authentication System

Multi-Level Fuzzy Score Fusion for Client Specific Linear Di...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Babak Rezaei Rowshan Marzuki Bin Khalid Rubiyah Yusof Center for Artificial Intelligence and Robotics (CAIRO) University Technology of Malaysia Kuala Lumpur Malaysia

A client specific linear discriminant analysis (CSLDA) based face authentication system has been developed with multi-level fuzzy score fusion. The CSLDA method provides two measures for authentication: distance to the client (Client Score) and distance to the mean of impostors (Impostor Score). A two-level multi-sample score fusion method has been proposed. A fuzzy inference module has also been developed to combine the scores of the CSLDA in the first level. The performance of fuzzy inference score fusion is then compared with several existing fusion methods and the conventional CSLDA face authentication system (without score fusion). Overall, the proposed fusion methods improve the performance of the algorithm and are more robust to variability of the inputs. Evaluation experiments were carried out with two different databases (AT&T and BANCA) where each contains face images of 40 subjects. Experimental results showed that the proposed multi-level fuzzy score fusion method improves the performance of the CSLDA based face authentication system compared to the other fusion techniques examined in this work.

关键词： Fuzzy systems Linear discriminant analysis Authentication Principal component analysis Fusion power generation Biometrics inference algorithms Testing Internet Artificial intelligence

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Latent time-frequency component analysis: A novel pitch-based approach for singing voice separation

Latent time-frequency component analysis: A novel pitch-base...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Xiu Zhang Wei Li Bilei Zhu School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China SAP Labs Shanghai China

Monaural singing voice separation has aroused considerable attention. Many pitch-based methods have been proposed to address this task, but generally have limited performance. The most crucial difficulties lie in the inaccurate judgment on voiced pitches and the failed recognition on unvoiced singing sounds. In this paper, we propose a novel algorithm based on the latent component analysis of time-frequency representation to overcome these difficulties. Specifically, the time-frequency (T-F) representations of the song are firstly decomposed into components, and each component approximately originates from a single sound source. We then construct non-overlapping T-F segments with these components, to complete the omitted useful singing voice information. Extensive experiments on the MIR-1K public dataset shows the effectiveness of the proposed algorithm.

关键词： Time-frequency analysis Speech Speech processing inference algorithms Matrix decomposition Accuracy Algorithm design and analysis

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Online tuning scheme for generalized predictive controller via simulation-optimization

Online tuning scheme for generalized predictive controller v...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Shaoyuan Li Guoning Du Institute of Automation Shanghai JiaoTong University Shanghai China

From the process control point of view, it is difficult to find out the optimal parameters for the control system based on the single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. First, M control actions are obtained by an unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints can then be calculated and the global satisfactory degree is obtained by fuzzy inference. Moreover, the weighting coefficient /spl lambda/ in the cost function is tuned using simulation-optimization according to the fuzzy criteria.

关键词： Fuzzy control Predictive control Prediction algorithms inference algorithms Process control Optimal control Control systems Performance analysis Decision making Cost function

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Poster: Using Consensus to Automatically Infer Post-conditions

Poster: Using Consensus to Automatically Infer Post-conditio...

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International Conference on Software Engineering - Companion, ICSE, Companion

作者： Jingyi Su Mohd Arafat Robert Dyer Bowling Green State University Bowling Green Ohio

Formal behavioral specifications help ensure the correctness of programs. Writing such specifications by hand however is time-consuming and requires substantial expertise. Previous studies have shown how to use a notion of consensus to automatically infer preconditions for APIs by using a large set of projects. In this work, we propose a similar idea of consensus to automatically infer post-conditions for popular APIs. We propose two new algorithms for mining potential post-conditions from API client code. The first algorithm looks for guarded post-conditions that test the value returned from the API and throws an exception. The second algorithm looks for values flowing from the API to another API with already known preconditions, which recommends them as post-conditions of the first API.

关键词： inference algorithms Software engineering Target tracking Writing Specification languages Collective intelligence Libraries

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Optimizing Multiple Consumer-specific Objectives in End-to-End Ensemble Machine Learning Serving

Optimizing Multiple Consumer-specific Objectives in End-to-E...

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IEEE International Conference on Utility and Cloud Computing (UCC)

作者： Minh-Tri Nguyen Hong-Linh Truong Paolo Arcaini Fuyuki Ishikawa Department of Computer Science Aalto University Espoo Finland National Institute of Informatics Tokyo Japan

ISBN: (数字)9798350367201

ISBN: (纸本)9798350367218

Optimizing the quality of machine learning (ML) services for individual consumers with specific objectives is crucial for improving consumer satisfaction. In this context, end-to-end ensemble ML serving (EEMLS) faces many challenges in selecting and deploying ensembles of ML models on diverse resources across the edge-cloud continuum. This paper provides a method for evaluating the runtime performance of inference services via consumer-defined metrics. We enable ML consumers to define high-level metrics and consider consumer satisfaction in estimating service costs. Moreover, we introduce a time-efficient ensemble selection algorithm to optimize the EEMLS with intricate trade-offs between service quality and costs. Our intensive experiments demonstrate that the algorithm can be executed periodically despite the extensive search space, enabling dedicated optimization for individual consumers in dynamic contexts.

关键词： Costs Machine learning algorithms Runtime Heuristic algorithms Customer satisfaction Machine learning inference algorithms Resource management Reliability Optimization

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Edge detection techniques using fuzzy thresholding

Edge detection techniques using fuzzy thresholding

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World Congress on Information and Communication Technologies (WICT)

作者： Mehul Thakkar Hitesh Shah A. C. R. E. Indian Institute of Technology New Vallabh Vidyanagar Gujarat India G. H. Patel College of Engineering and Technology Vallabh Vidyanagar Gujarat India

Edge detection is forefront of image processing algorithms. There are problems associated with different edge detectors. Thresholding is critical problem in edge detection. The paper represents three different methods of fuzzy based thresholding and resulted adaptive threshold is used in edge detection algorithm. Simulation results shows fuzzy thresholding based edge detection gives better results than conventional methods.

关键词： Image edge detection Detectors Brightness Fuzzy reasoning Fuzzy systems Histograms inference algorithms

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