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WhatsApp: +86 18221755073Abstract Large amounts of time-series data have become accessible due to the rapid development of Internet-of-Things technologies and the demand for extracting useful knowledge from these data is increasing. Toward this goal, time-series segmentation — dividing data into similar segments — is a promising method for understanding the mechanisms in time …
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WhatsApp: +86 18221755073Abstract Recommender systems play an important role in helping users discover items of interest from a large resource collection in various online services. Although current deep neural network-based collaborative filtering methods have achieved state-of-the-art performance in recommender systems, they still face a few major weaknesses. Most importantly, such deep …
WhatsApp: +86 18221755073Abstract We study the application of spectral clustering, prediction and visualization methods to graphs with negatively weighted edges. We show that several characteristic matrices of graphs can be extended to graphs with positively and negatively weighted edges, giving signed spectral clustering methods, signed graph kernels and network …
WhatsApp: +86 18221755073Abstract Deep neural network (DNN) has become an effective computational tool because of its superior performance in practice. However, the generalization of DNN still largely depends on the training data, no matter in quantity or quality. In this paper, we propose a knowledge instillation framework, named NeuKI, for feed-forward DNN, aiming to enhance learning performance …
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WhatsApp: +86 18221755073Abstract The mining of outliers (or anomaly detection) in large databases continues to remain an active area of research with many potential applications. Over the last several years many novel methods have been proposed to efficiently and accurately mine for outliers. In this paper we propose a unique approach to mine for sequential outliers using …
WhatsApp: +86 18221755073It is our great pleasure to welcome you to the 2016 SIAM International Conference on Data Mining. This year's research track continues its tradition of providing a forum for researchers, students, ...
WhatsApp: +86 18221755073In this paper, we present a method for constructing a feature-engineered random forest by transforming the features of a given data set using a set of diverse and randomized transforms. The transformed features are then used for creating splits at each node of a random forest. In particular, we use sum-product features because of their strong expressive power. …
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WhatsApp: +86 18221755073The SIAM Data Mining (SDM) conference invites submissions of high-quality research papers that present original results on data mining algorithms and their applications. Data mining is a core process within computing and statistics, aimed at discovering valuable knowledge from data.
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WhatsApp: +86 18221755073The 24,000-30,000 tpy capacity mine will return to the market following a year of modifications, Michael Greenfield reports.Thailand's SC Mining is preparing to bring into operation an …
WhatsApp: +86 18221755073A string is often provided with numerical scores (utilities) which quantify the importance, interest, profit, or risk of the letters occurring at every position of the string. For example, every DNA fragment produced by modern sequencing machines comes with a confidence score per position. Motivated by the abundance of strings with utilities, we …
WhatsApp: +86 18221755073Quick Facts. 5,130 active mining claims.; 43,567 closed mining claims.; Uranium and Other mines located in South Carolina. Listing claims originally filed between the 2020's and the 1870's.
WhatsApp: +86 18221755073A key challenge in the continual learning setting is to efficiently learn a sequence of tasks without forgetting how to perform previously learned tasks. Many existing approaches to this problem work by either retraining the model on previous tasks or by expanding the model to accommodate new tasks. However, these approaches typically suffer from increased storage …
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WhatsApp: +86 18221755073Abstract We propose a deep learning approach for discovering kernels tailored to identifying clusters over sample data. Our neural network produces sample embeddings that are motivated by and are at least as expressive as spectral clustering. Our training objective, based on the Hilbert Schmidt Independence Criterion, can be optimized via gradient adaptations on …
WhatsApp: +86 18221755073There are several types of surface mining done in South Carolina: open pit (i.e., granite, vermiculite), strip mines (i.e., sand, clay, gravel) and sand dredging from river bottoms. South …
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WhatsApp: +86 18221755073Abstract Time series shapelets are a recent promising concept in time series data mining. Shapelets are time series snippets that can be used to classify unlabeled time series. Shapelets not only provide interpretable results, which are useful for domain experts and developers alike, but shapelet-based classifiers have been shown by several independent …
WhatsApp: +86 18221755073Abstract Seeking outside funding is a critical task for many companies, but it is also challenging to identify the potential investors given the heterogeneity in size, interests, and expertise. In this work, we propose to tackle this problem via data-driven approaches. Towards this end, we first harvest relevant publicly available data about institutional investors and their …
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WhatsApp: +86 18221755073Origin and CompositionThe Mining Council, established with the enactment of Section 48-21-20 of the South Carolina Code of Laws 1976, as amended, resides in the office of the Governor and acts as an advisory body to the Governor in considering issues relating to mining. The Council considers appeals on decisions made by the South Carolina Department of Health and …
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