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    advanceddataanalytics.net advanceddataanalytics.net

    A collection of 8,547 posts


    advanceddataanalytics.net advanceddataanalytics.net 2021-03-02 03:21

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    Graph Dynamical Network Understanding the dynamical processes that govern the performance of functional materials is essential for the...

    Michael Laux
    M Michael Laux
    3 min read
    advanceddataanalytics.net advanceddataanalytics.net 2021-02-28 09:03

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    Decentralized Simultaneous Perturbation Stochastic Approximations, with Constant Sensitivity Parameters (DSPG) In this paper, we present an...

    Michael Laux
    M Michael Laux
    3 min read
    advanceddataanalytics.net advanceddataanalytics.net 2021-02-27 11:05

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    Conditional t-SNE (ct-SNE) Dimensionality reduction and manifold learning methods such as t-Distributed Stochastic Neighbor Embedding...

    Michael Laux
    M Michael Laux
    3 min read
    advanceddataanalytics.net advanceddataanalytics.net 2021-02-26 03:21

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    funHDDC General procedure for clustering functional data which adapts the efficient clustering method HDDC, originally proposed in the...

    Michael Laux
    M Michael Laux
    3 min read
    advanceddataanalytics.net advanceddataanalytics.net 2021-02-24 13:07

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    L1-Norm Kernel PCA We present the first model and algorithm for L1-norm kernel PCA. While L2-norm kernel PCA has been widely studied, there...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-24 11:05

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    L2-Nonexpansive Neural Network This paper proposes a class of well-conditioned neural networks in which a unit amount of change in the inputs causes at most a unit amount of change in the outputs or any of the internal...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-23 05:23

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    ART Transfer learning aims to solve the data sparsity for a target domain by applying information of the source domain. Given a sequence (e.g. a natural language sentence), the transfer learning, usually enabled by...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-21 11:05

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    Ridge Regularized Linear Models (RRLM) Ridge regularized linear models (RRLMs), such as ridge regression and the SVM, are a popular group of methods that are used in conjunction with coefficient hypothesis testing to...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-20 11:05

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    Hyperbolic Bayesian Personalized Ranking (HyperBPR) Many well-established recommender systems are based on representation learning in Euclidean space. In these models, matching functions such as the Euclidean distance...

    Michael Laux
    M Michael Laux
    2 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-19 13:07

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    Beta Regression How should we one perform a regression analysis in which the dependent variable is restricted to the standard unit interval such as rates and proportions? Ferrari and Cribari-Neto, 2004 proposed a...

    Michael Laux
    M Michael Laux
    4 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-18 05:23

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    Layered Tree-Based Pipeline Optimization Tool (Layered TPOT) With the demand for machine learning increasing, so does the demand for tools which make it easier to use. Automated machine learning (AutoML) tools have been...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-17 03:21

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    Zeno++ We propose Zeno++, a new robust asynchronous synchronous Stochastic Gradient Descent~(SGD) under a general Byzantine failure model with unbounded number of Byzantine workers. … TensorFlow Ranking (TF-Ranking)...

    Michael Laux
    M Michael Laux
    2 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-16 09:03

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    QuickSel Estimating the selectivity of a query is a key step in almost any cost-based query optimizer. Most of today’s databases rely on histograms or samples that are periodically refreshed by re-scanning the data as...

    Michael Laux
    M Michael Laux
    4 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-15 07:01

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    AutoSpearman The interpretation of defect models heavily relies on software metrics that are used to construct them. However, such software metrics are often correlated to defect models. Prior work often uses feature...

    Michael Laux
    M Michael Laux
    4 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-14 05:23

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    People + AI Research (PAIR) The past few years have seen rapid advances in machine learning, with new technologies achieving dramatic improvements in technical performance. But we can go beyond optimizing objective...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-12 13:07

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    LAHA Extreme multi-label text classification (XMTC) aims at tagging a document with most relevant labels from an extremely large-scale label set. It is a challenging problem especially for the tail labels because there...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-12 03:21

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    Bach2Bach A model of music needs to have the ability to recall past details and have a clear, coherent understanding of musical structure. Detailed in the paper is a deep reinforcement learning architecture that...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-10 13:07

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    Control Toolbox (CT) We introduce the Control Toolbox (CT), an open-source C++ library for efficient modelling, control, estimation, trajectory optimization and model predictive control. The CT is applicable to a broad...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-09 11:05

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    Staleness Most distributed machine learning (ML) systems store a copy of the model parameters locally on each machine to minimize network communication. In practice, in order to reduce synchronization waiting time,...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-08 05:23

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    SocialGCN Collaborative Filtering (CF) is one of the most successful approaches for recommender systems. With the emergence of online social networks, social recommendation has become a popular research direction. Most...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-06 11:05

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    Author Rank Author Rank is a new aspect of Google’s search algorithm that will score online content creators. Similar to SEO rankings for sites and pages, authors will now have an associated ranking based on a few...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-06 03:21

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    Accuracy Booster Convolution Neural Networks (CNN) have been extremely successful in solving intensive computer vision tasks. The convolutional filters used in CNNs have played a major role in this success, by...

    Michael Laux
    M Michael Laux
    4 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-05 03:21

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    Learning to Auto Weight (LAW) Example weighting algorithm is an effective solution to the training bias problem. However, typical methods are usually limited to human knowledge and require laborious tuning of...

    Michael Laux
    M Michael Laux
    2 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-04 01:19

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    iFair People are rated and ranked, towards algorithmic decision making in an increasing number of applications, typically based on machine learning. Research on how to incorporate fairness into such tasks has...

    Michael Laux
    M Michael Laux
    3 min read
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    advanceddataanalytics.net advanceddataanalytics.net 2021-02-02 03:21

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    Generative Actor Critic (GAC) We identify a fundamental problem in policy gradient-based methods in continuous control. As policy gradient methods require the agent’s underlying probability distribution, they limit...

    Michael Laux
    M Michael Laux
    3 min read
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