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Showing 1 to 15 of 15 for “"Streaming algorithms"”.

  1. New directions in streaming algorithms

    … One such model is captured by the notion of streaming algorithms: given a sequence of N items, the goal is to compute the value of a given function of the input items by a small number of passes and using a sublinear amount of space in N. Streaming algorithms have applications in many areas …

    mit Repository record for New directions in streaming algorithms (opens in a new tab)

  2. Faster streaming algorithms for low-rank matrix approximations

    … number of applications. We present new algorithms for generating such approximations in a streaming fashion that expand upon recently discovered matrix sketching techniques. We test our approaches on real and synthetic data to explore runtime and accuracy performance. We apply our …

    mit Repository record for Faster streaming algorithms for low-rank matrix approximations (opens in a new tab)

  3. Variational inference for non-stationary distributions

    … Bayes and Stochastic Variational Inference into streaming algorithms and try to identify if any of them work with non-stationary distributions. I conclude that Kalman Variational Bayes can do as good as any other algorithm for stationary distributions, and tracks non-stationary distributions …

    mit Repository record for Variational inference for non-stationary distributions (opens in a new tab)

  4. Sublinear algorithms for massive data problems

    In this thesis, we present algorithms and prove lower bounds for fundamental computational problems in the models that address massive data sets. The models include streaming algorithms, sublinear time algorithms, property testing algorithms, sublinear query time algorithms with preprocessing, or …

    mit Repository record for Sublinear algorithms for massive data problems (opens in a new tab)

  5. Statistical Estimation from Dependent and Adversarial Data

    … these scenarios and describe polynomial-time algorithms to solve them. For (1), I will define the learning problem as a problem of learning Ising models and present algorithms to learning Ising models under different contexts. For (2), I will use the formulation of adversarial streaming

    mit Repository record for Statistical Estimation from Dependent and Adversarial Data (opens in a new tab)

  6. Detecting exploit patterns from network packet streams

    … been any significant attempt, so far, to design algorithms with provable guarantees for detecting exploit patterns from network traffic packets. In this work, we develop and apply data streaming algorithms to detect exploit patterns from network packet streams.</p> <p>In network intrusion …

    iastate Repository record for Detecting exploit patterns from network packet streams (opens in a new tab)

  7. Sparse recovery and Fourier sampling

    … has a wide variety of applications such as streaming algorithms, image acquisition, and disease testing. A particularly important subclass of sparse recovery is the sparse Fourier transform, which considers the computation of a discrete Fourier transform when the output is sparse. …

    mit Repository record for Sparse recovery and Fourier sampling (opens in a new tab)

  8. Scalable video transportation using look ahead scheduling

    This thesis introduces many video streaming algorithms and techniques to improve the performance of scalable video dissemination over a packet network. As the quality of visual content in a best-effort network is susceptible to average bandwidth availability, packet loss, packet delay and packet …

    essex Repository record for Scalable video transportation using look ahead scheduling (opens in a new tab)

  9. Efficient and private distance approximation in the communication and streaming models

    … in two closely related models - the streaming model and the two-party communication model. In the streaming model, a massive data stream is presented in an arbitrary order to a randomized algorithm that tries to approximate certain statistics of tile data with only a few (usually one) …

    mit Repository record for Efficient and private distance approximation in the communication and streaming models (opens in a new tab)

  10. Pseudo-determinism

    A curious property of randomized algorithms for search problems is that on different executions on the same input, the algorithm may return different outputs due to differences in the internal randomness used by the algorithm. We would like to understand how we can construct randomized algorithms

    mit Repository record for Pseudo-determinism (opens in a new tab)

  11. Sketching and streaming high-dimensional vectors

    … given just one pass over the data, a so-called streaming algorithm. Sketching and streaming have found numerous applications in network traffic monitoring, data mining, trend detection, sensor networks, and databases. In this thesis, I describe several new contributions in the area of sketching …

    mit Repository record for Sketching and streaming high-dimensional vectors (opens in a new tab)

  12. Compiler techniques for scalable performance of stream programs on multicore architectures

    … of data, and it is a natural expression of algorithms in the areas of audio, video, digital signal processing, networking, and encryption. Streaming computation is represented as a graph of independent computation nodes that communicate explicitly over data channels. Our techniques operate …

    mit Repository record for Compiler techniques for scalable performance of stream programs on multicore architectures (opens in a new tab)

  13. Estimating Frequency Distributions in Data Streams

    Streaming algorithms allow for space-efficient processing of massive datasets. The distribution of the frequencies of items in a large dataset is often used to characterize that data: e.g., the data is heavy-tailed, the data follows a power law, or there are many elements that only appear only once …

    mit Repository record for Estimating Frequency Distributions in Data Streams (opens in a new tab)

  14. Streaming Random Forests

    … and financial applications. Data-stream mining algorithms incorporate special provisions to meet the requirements of stream-management systems, that is stream algorithms must be online and incremental, processing each data record only once (or few times); adaptive to distribution changes; and …

    queens Repository record for Streaming Random Forests (opens in a new tab)

  15. Semantics and efficient evaluation of partial tree-pattern queries on XML

    … continuously in the form of a stream. Existing algorithms cannot be used directly or indirectly to efficiently compute PTPQs in either mode. Initially, the problem of efficiently evaluating partial path queries in the inverted lists model has been addressed. Partial path queries form a subclass …

    njit Repository record for Semantics and efficient evaluation of partial tree-pattern queries on XML (opens in a new tab)