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Author: D’yang Eng

  • Paper Review: A Quantum‐Inspired Classical Algorithm for Recommendation Systems

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    by

    D’yang Eng
    in

    1. What problem does this paper aim to solve? This paper aims to solve the problem of whether the exponential speedup claimed by the Kerenidis-Prakash (KP) quantum recommendation algorithm for online recommendation systems is truly exclusive to quantum computing or if a similar speedup can be achieved classically. Specifically, the paper addresses: In summary:The paper seeks to determine whether the quantum…

  • Paper Review: Quantum Recommendation Systems

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    by

    D’yang Eng
    in

    1. What problem does this paper aim to solve? The Kerenidis & Prakash (2017) paper aims to solve the problem of efficiently providing personalized recommendations from extremely large user-item preference datasets, by leveraging quantum algorithms to reduce the computational complexity from polynomial (in the size of the data) to polylogarithmic time (), under the key assumption of…

  • Word Embeddings

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    by

    D’yang Eng
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    Introduction Word embeddings are numerical representations of words in a continuous vector space, by learning the distribution of words in text. They capture both semantic and syntactic relationships between words, making them suitable for various downstream Natural Language Processing (NLP) tasks. Typically, words with similar meanings are mapped to nearby points in the vector spaces.…