ALT 2019

From ConfIDent
Deadlines
Metrics
Submitted Papers
78
Accepted Papers
37
Venue

Chicago, United States of America

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Topics

  • Design and analysis of learning algorithms.
  • Statistical and computational learning theory.
  • Online learning algorithms and theory.
  • Optimization methods for learning.
  • Unsupervised, semi-supervised, online and active learning.
  • Connections of learning with other mathematical fields.
  • Artificial neural networks, including deep learning.
  • High-dimensional and non-parametric statistics.
  • Learning with algebraic or combinatorial structure.
  • Bayesian methods in learning.
  • Planning and control, including reinforcement learning.
  • Learning with system constraints: e.g. privacy, memory or communication budget.
  • Learning from complex data: e.g., networks, time series, etc.
  • Interactions with statistical physics.
  • Learning in other settings: e.g. social, economic, and game-theoretic.
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