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ICML 2013

TechTalks from event: ICML 2013

July 20th: Please note that we are doing a quality check and we will be uploading the missing videos and talks with poor audio in next few days.

Track C: Clustering

  • A Local Algorithm for Finding Well-Connected Clusters Authors: Silvio Lattanzi; Vahab Mirrokni; Zeyuan Allen Zhu
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  • Monochromatic Bi-Clustering Authors: Sharon Wulff; Ruth Urner; Shai Ben-David
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  • Constrained fractional set programs and their application in local clustering and community detection Authors: Thomas B
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  • Graph Clustering: Big Clusters and Small Clusters Authors: Yudong Chen; Nir Ailon; Huan Xu
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  • Strict Monotonicity of Sum of Squares Error and Normalized Cut in the Lattice of Clusterings Authors: Nicola Rebagliati
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  • Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space Authors: Javler Almingol ; Luis Montesano; Manuel Lopes
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  • Precision-recall space to correct external indices for biclustering Authors: Blaise Hanczar; Mohamed Nadif
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  • Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion Authors: Jinfeng Yi; Rong Jin; Qi Qian; Anil Jain
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  • All Sessions
    • Tutorials
    • Plenary talks
    • Session
    • Track B: Feature Learning
    • Track B: Optimization and Integration
    • Track C: General SVM and Decision Tree Methods
    • Track C: Vision
    • Track D: Spectral Learning and Tensors
    • Track D: Learning Theory II
    • Deep Learning 1
    • Track A: Online Learning 2
    • Track A: Crowd Sourcing and Large Scale Learning
    • Compressed Sensing 1
    • Track B: Structured Labeling
    • Track B: Kernel Methods
    • Reinforcement Learning 1
    • Track C: Dimensionality Reduction
    • Track D: Learning Theory 3
    • Social Networks
    • Track D: Statistical Methods
    • Track C: Matrix Factorization
    • Deep Learning 2
    • Track A: Nearest Neighbor and Metric Learning
    • Compressed Sensing 2
    • Track B: General Methods
    • Reinforcement learning 2
    • Track C: Transfer Learning
    • Topic Modeling 1
    • Track D: Statistical Learning and Inference
    • Deep Learning and Neuroscience
    • Track B: Optimization
    • Compressed Sensing 3
    • Track C: Clustering
    • Reinforcement Learning and Time Series
    • Track D: Learning Theory 1
    • Topic Modeling 2
    • Track A: Invited Orals
    • Track A: Online Learning 1
    • Track A: Dimensionality Reduction and Semi-Supervised Learning

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  • Publish:1 Event, 295 Videos, 0 slideshow.
  • About:ICML 2013
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