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Showing 1 to 6 of 6 for “"model discovery"”.

  1. Structural Model Discovery in Temporal Event Data Streams

    … construction and modification of behavior models. Our focus is to introduce the research area of behavior analysis, the challenges faced by this field, current approaches available, and present a new analysis approach: Interactive Relevance Search and Modeling (IRSM). More intelligent ways …

    vt Repository record for Structural Model Discovery in Temporal Event Data Streams (opens in a new tab)

  2. Artificial intelligence-assisted data analysis with BayesDB

    … missing data or errors from black-box predictive models that are difficult to understand or explain in terms of the model's inputs. This thesis explores the applicability of BayesDB, a probabilistic programming platform for data analysis, to three common problems in data analysis: (i) modeling …

    mit Repository record for Artificial intelligence-assisted data analysis with BayesDB (opens in a new tab)

  3. A Holistic Paradigm for Large Scale Schema Matching

    … matchings by viewing schema matching as hidden model discovery. Then, to deal with complex matchings, we further develop the DCM framework by abstracting schema matching as correlation mining. Further, to automate the entire matching process, we incorporate the DCM framework with automatically …

    uiuc Repository record for A Holistic Paradigm for Large Scale Schema Matching (opens in a new tab)

  4. From data to dynamics: discovering governing equations from data

    … at discovering governing laws and reduced models from data, many challenges still remain. In this work, we focus on the discovery of nonlinear dynamical systems models from data. We present several methods based on the sparse identification of nonlinear dynamics (SINDy) algorithm. These …

    washington Repository record for From data to dynamics: discovering governing equations from data (opens in a new tab)

  5. Taming TinyML: deep learning inference at computational extremes

    The advanced data modelling capabilities of neural networks allowed deep learning to become a cornerstone of many applications of artificial intelligence (AI). AI can be brought into our environments by deploying neural models to ubiquitous Internet-of-Things (IoT), wearable and embedded devices to …

    cambridge Repository record for Taming TinyML: deep learning inference at computational extremes (opens in a new tab)

  6. Análisis de eventos para evaluar competencias en experiencias de aprendizaje basadas en serious games

    … interacciones realizadas, permitiendo descubrir modelos para analizar el comportamiento de los estudiantes en procesos secuenciales. Finalmente, las técnicas de process mining proporcionaron un apoyo automatizado para evaluar las competencias desarrolladas durante la experiencia de juego.

    cadiz Repository record for Análisis de eventos para evaluar competencias en experiencias de aprendizaje basadas en serious games (opens in a new tab)