Corpus ID: 219530932

Deep Goal-Oriented Clustering

  title={Deep Goal-Oriented Clustering},
  author={Yifeng Shi and Christopher M. Bender and J. Oliva and M. Niethammer},
  • Yifeng Shi, Christopher M. Bender, +1 author M. Niethammer
  • Published 2020
  • Computer Science, Mathematics
  • ArXiv
  • Clustering and prediction are two primary tasks in the fields of unsupervised and supervised learning, respectively. Although much of the recent advances in machine learning have been centered around those two tasks, the interdependent, mutually beneficial relationship between them is rarely explored. One could reasonably expect appropriately clustering the data would aid the downstream prediction task and, conversely, a better prediction performance for the downstream task could potentially… CONTINUE READING


    Publications referenced by this paper.
    Auto-Encoding Variational Bayes
    • 9,147
    • Highly Influential
    • PDF
    Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering
    • 211
    • Highly Influential
    • PDF
    Auto-encoding variational bayes. CoRR, abs/1312
    • 2014
    Avoiding common pitfalls when clustering biological data
    • 64
    • PDF
    Classtering: Joint Classification and Clustering with Mixture of Factor Analysers
    • 3
    • PDF
    Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm
    • 6
    • PDF
    Clustering with Instance-Level Constraints
    • 604
    • PDF
    Deep Clustering for Unsupervised Learning of Visual Features
    • 441
    • PDF
    Deep Spectral Clustering Learning
    • 70
    • PDF
    Distance Metric Learning with Application to Clustering with Side-Information
    • 2,830
    • PDF