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Papers

Papers that changed AI, with a plain-language explainer for each.

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  1. 1995

    Support-vector networks

    Machine Learning

    Corinna Cortes and Vladimir Vapnik's 1995 paper presents a learning machine for two-group classification that maps inputs nonlinearly into a high-dimensional feature space, constructs a linear decision surface, and extends earlier work from separable to non-separable data.

    Research historyDeep learningData & datasets

  2. 1993

    Building a Large Annotated Corpus of English: The Penn Treebank

    Computational Linguistics

    A 1993 journal article by Mitchell P. Marcus, Beatrice Santorini and Mary Ann Marcinkiewicz describing the Penn Treebank: over one million words of Wall Street Journal text annotated with syntactic bracketing, built as a resource for work on English sentence structure.

    Large language modelsResearch historyData & datasets

  3. 1992

    A Training Algorithm for Optimal Margin Classifiers

    Published in 1992, this paper by Boser, Guyon and Vapnik presents a training algorithm that maximizes the margin between training patterns and the decision boundary, with experiments on optical character recognition.[^1]

    Research historyDeep learningData & datasets

  4. 1992

    Q-learning

    Machine Learning

    A 1992 technical note by Watkins and Dayan that set out Q-learning, an incremental and computationally light way for an agent to learn optimal action values, and proved it converges to the optimum with probability 1.

    Research historyDeep learningData & datasets

  5. 1948

    A Mathematical Theory of Communication

    Bell System Technical Journal 27

    C. E. Shannon's 1948 paper set out a mathematical framework for communication, defining information in bits, channel capacity, and entropy, and treating messages statistically while setting aside semantic meaning.

    Research historyData & datasetsScience