Event: Conferences » Other » 27th Annual Conference on Learning Theory (COLT), Barcelona 2014 27th Annual Conference on Learning Theory (COLT), Barcelona 2014

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COLT 2014 - Barcelona   

27th Annual Conference on Learning Theory (COLT), Barcelona 2014

The conference strongly supports a broad definition of learning theory, including, but not limited to:

• Design and analysis of learning algorithms and their generalization ability
• Computational complexity of learning
• Optimization procedures for learning
• Unsupervised, semi-supervised learning, and clustering
• Online learning
• Interactive learning
• Kernel Methods
• High dimensional and non-parametric empirical inference, including sparsity methods
• Planning and control, including reinforcement learning
• Learning with additional constraints: E.g. privacy, time or memory budget, communication
• Learning in other settings: E.g. social, economic, and game-theoretic
• Analysis of learning in related fields: natural language processing, neuroscience, bioinformatics, privacy and security, machine vision, data mining, information retrieval.

Additional information can be found at COLT 2014 home page.

Categories

Invited Speakers

Unsupervised Learning; Dictionary Learning; Latent Variable Models

Concentration

Unsupervised Learning; Dictionary Learning; Latent Variable Models II

Statistical Learning Theory

Unsupervised Learning; Mixture Models

Online Learning

Statistical and Online Learning

Learning with Partial Feedback

Computational Learning Theory/Algorithmic Results

Computational Learning Theory/Lower Bounds

Learning with Partial Feedback

Statistical Learning Theory

Sequential Learning

Reviews and comments:

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Comment2 Adam, February 14, 2022 at 11:41 a.m.:

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Comment4 Devin Harmon, May 19, 2022 at 11:37 a.m.:

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