Search results for " Mach"

showing 10 items of 1388 documents

Identifying Causal Effects via Context-specific Independence Relations

2019

Causal effect identification considers whether an interventional probability distribution can be uniquely determined from a passively observed distribution in a given causal structure. If the generating system induces context-specific independence (CSI) relations, the existing identification procedures and criteria based on do-calculus are inherently incomplete. We show that deciding causal effect non-identifiability is NP-hard in the presence of CSIs. Motivated by this, we design a calculus and an automated search procedure for identifying causal effects in the presence of CSIs. The approach is provably sound and it includes standard do-calculus as a special case. With the approach we can …

FOS: Computer and information sciencescontext-specific independence relationsComputer Science - Machine LearningArtificial Intelligence (cs.AI)Computer Science - Artificial Intelligenceeducationkausaliteetticausal effect identification113 Computer and information sciencesMachine Learning (cs.LG)
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Study design in causal models

2012

The causal assumptions, the study design and the data are the elements required for scientific inference in empirical research. The research is adequately communicated only if all of these elements and their relations are described precisely. Causal models with design describe the study design and the missing data mechanism together with the causal structure and allow the direct application of causal calculus in the estimation of the causal effects. The flow of the study is visualized by ordering the nodes of the causal diagram in two dimensions by their causal order and the time of the observation. Conclusions whether a causal or observational relationship can be estimated from the collect…

FOS: Computer and information sciencesdesignstructural equation modelG.362A01 62-09 62F99 62D05 62P10 62K99 68T30graphical modelMachine Learning (stat.ML)G.2.2Statistics - ApplicationsG.3; G.2.2Methodology (stat.ME)missing dataStatistics - Machine LearningkausaliteettiApplications (stat.AP)epidemiologiaStatistics - Methodology
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Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer

2023

Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is based on convolutional neural networks which were trained to classify colorectal cancer tissue in hematoxylin-eosin stained samples into three classes: stroma, tumor and other. The models were trained using a data set that consists of 1343 whole slide images. Three different training setups were applied with a transfer learning approach using domain-specific data i.e. an external colorectal cancer histopathological data set. The three most accurate models were chosen as a classifie…

FOS: Computer and information sciencessmooth musclesvisionComputer Science - Machine LearningMultidisciplinaryComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern Recognitioncolorectal cancerforecastingennusteetneuroverkotsuolistosyövätneural networksQuantitative Biology - Quantitative MethodsMachine Learning (cs.LG)machine learningkoneoppiminenFOS: Biological sciencessyöpätauditcancers and neoplasmsmalignant tumorsQuantitative Methods (q-bio.QM)
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Low-Power Audio Keyword Spotting using Tsetlin Machines

2021

The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipe…

FOS: Computer and information sciencesspeech commandSound (cs.SD)Computer scienceSpeech recognition02 engineering and technologykeyword spottingMachine learningcomputer.software_genreComputer Science - SoundReduction (complexity)Audio and Speech Processing (eess.AS)020204 information systemsFOS: Electrical engineering electronic engineering information engineering0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringArtificial neural networkLearning automatabusiness.industrylearning automatalcsh:Applications of electric power020206 networking & telecommunicationslcsh:TK4001-4102Pipeline (software)Power (physics)machine learningTsetlin MachineMFCCKeyword spottingelectrical_electronic_engineeringScalabilityMemory footprintpervasive AI020201 artificial intelligence & image processingMel-frequency cepstrumArtificial intelligencebusinesscomputerartificial neural networkEfficient energy useElectrical Engineering and Systems Science - Audio and Speech Processing
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Balancing Profit, Risk, and Sustainability for Portfolio Management

2022

Author's accepted manuscript © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Stock portfolio optimization is the process of continuous reallocation of funds to a selection of stocks. This is a particularly well-suited problem for reinforcement learning, as daily rewards are compounding and objective functions may include more than just profit, e.g., risk and su…

FOS: Economics and businessFOS: Computer and information sciencesComputer Science - Machine LearningVDP::Teknologi: 500Artificial Intelligence (cs.AI)Portfolio Management (q-fin.PM)Computer Science - Artificial IntelligenceQuantitative Finance - Portfolio ManagementMachine Learning (cs.LG)
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Nanomanufacturing/Nanotechnology

2008

This chapter provides comprehensive knowledge regarding the fabrication of nanoproducts and element of micro-electromechanical systems using various techniques and processes. Both well-established techniques, such as nanomachining (ultra-precision) and new trends in improving nanoprocesses taking into account AFM, laser beam machining, electron beam machining processes are overviewed. The background of nanomachining processes, including typical machining operations such as turning, milling and grinding and different construction materials (metallic and nonmetallic), is outlined. The physical mechanisms responsible for the transition from brittle to ductile regime machining are explained. Mo…

FabricationNanomanufacturingElectron beam machiningMachiningAtomic force microscopyComputer scienceSystem of measurementLaser beam machiningNanotechnologyGrinding
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Audio-video people recognition system for an intelligent environment

2011

In this paper an audio-video system for intelligent environments with the capability to recognize people is presented. Users are tracked inside the environment and their positions and activities can be logged. Users identities are assessed through a multimodal approach by detecting and recognizing voices and faces through the different cameras and microphones installed in the environment. This approach has been chosen in order to create a flexible and cheap but reliable system, implemented using consumer electronics. Voice features are extracted by a short time cepstrum analysis, and face features are extracted using the eigenfaces technique. The recognition task is solved using the same Su…

Face featureSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryComputer scienceIntelligent environmentPeople recognitionFeature extractionReliable systemSet-up phaseSingle sensorFacial recognition systemSelection principleSupport vector machineSoftwareEigenfaceMulti-modal approachMiddlewareCepstrumLearning ruleIntelligent environmentCepstrum analysiComputer visionArtificial intelligenceEigenfacebusiness
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Good Old-Fashioned Artificial Consciousness and the Intermediate Level Fallacy

2018

Recently, there has been considerable interest and effort to the possibility to design and implement conscious robots, i.e., the chance that a robot may have subjective experiences. However, typical approaches as the global workspace, information integration, enaction, cognitive mechanisms, embodiment, i.e., the Good Old-Fashioned Artificial Consciousness, henceforth, GOFAC, share the same conceptual framework. In this paper, we discuss GOFAC's basic tenets and their implication for AI and Robotics. In particular, we point out the intermediate level fallacy as the central issue affecting GOFAC. Finally, we outline a possible alternative conceptual framework towards robot consciousness.

Fallacyartificial consciousnessComputer sciencemedia_common.quotation_subjectlcsh:Mechanical engineering and machinerymachine consciousnessArtificial consciousness050105 experimental psychologylcsh:QA75.5-76.95Enactivism03 medical and health sciences0302 clinical medicineArtificial IntelligenceHypothesis and Theory0501 psychology and cognitive scienceslcsh:TJ1-1570media_commonrobot consciousness; machine consciousness; artificial consciousness; synthetic phenomenology; robot self-awarenessrobot consciousneartificial consciousneCognitive scienceSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniRobotics and AIIntegrated information theory05 social sciencesHard problem of consciousnessComputer Science Applicationsrobot self-awarenessConceptual frameworkRobotlcsh:Electronic computers. Computer scienceConsciousnessrobot consciousnesssynthetic phenomenologymachine consciousne030217 neurology & neurosurgeryFrontiers in Robotics and AI
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Replica all'attacco di Heinrich Leo

2015

Prima traduzione italiana del saggio con cui Ranke reagisce alla critica di Henrich Leo, storico di formazione hegeliana. Si tratta di una polemica rimasta simbolicamente rilevante come confronto diretto tra due modi opposti di intendere le possibilità scientifiche della storiografia. Importante anche per quanto riguarda la storia della ricezione tedesca ottocentesca di Machiavelli.

Filosofia della storia storiografia empirica idee/Idea MachiavelliSettore M-FIL/06 - Storia Della Filosofia
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Power flow management controller within a grid connected photovoltaic based active generator as a finite state machine using hierarchical approach wi…

2020

Abstract Grid integration of photovoltaic (PV) system with a hybrid energy storage can help not only in increasing more penetration of PV system into the network but also in improving the power system dynamics and control in addition to helping the demand side management. In this work, a PV system with a hybrid energy storage including a battery array and a super capacitor bank is going to work as an active generator with innovative load management and power flow control strategies for managing the active power demand locally considering the grid constraints. This work proposes an architecture for a PV based active generator, which can provide active power in controlled manner while maintai…

Finite-state machine060102 archaeologyRenewable Energy Sustainability and the EnvironmentComputer sciencebusiness.industry020209 energyPhotovoltaic systemElectrical engineering06 humanities and the arts02 engineering and technologyAC powerGridElectric power systemLoad management0202 electrical engineering electronic engineering information engineering0601 history and archaeologyVoltage droopbusinessEmbodied energyRenewable Energy
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