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Related Experiment Videos

Query by transduction.

Shen-Shyang Ho1, Harry Wechsler

  • 1NASA Jet Propulsion Laboratory, Pasadena, CA 91109, USA. sho@jpl.nasa.gov

IEEE Transactions on Pattern Analysis and Machine Intelligence
|July 12, 2008
PubMed
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This study introduces Query-by-Transduction (QBT), a new active learning algorithm for stream-based settings. QBT effectively queries labels using transduction, outperforming other methods in classification tasks.

Area of Science:

  • Machine Learning
  • Statistical Learning Theory
  • Data Mining

Background:

  • Growing interest in transductive inference for machine learning applications.
  • Active learning is crucial for efficient data labeling in stream-based environments.
  • Existing active learning methods may not fully leverage transductive principles.

Purpose of the Study:

  • To extend transductive inference to active learning within a stream-based setting.
  • To propose and evaluate a novel active learning algorithm named Query-by-Transduction (QBT).

Main Methods:

  • Introduced Query-by-Transduction (QBT), an active learning algorithm utilizing p-values from transduction.
  • Established theoretical connections between QBT, Query-by-Committee (QBC), Bayesian testing, KL-divergence, and Shannon information.

Related Experiment Videos

  • Empirically validated QBT on binary and multi-class classification tasks using Support Vector Machines (SVM).

    • Main Results:

    • Demonstrated the feasibility and utility of QBT across various classification problems.
    • QBT achieved favorable mean generalization performance compared to random sampling and other active learning strategies.
    • Experimental results confirmed QBT's effectiveness in the stream-based active learning context.

    Conclusions:

    • QBT offers a novel and effective approach to active learning in stream-based scenarios.
    • The algorithm leverages transduction principles to efficiently query informative labels.
    • QBT shows competitive or superior performance against established active learning methods.