- Logarithmic Time Online Multiclass prediction
- Space-Time Local Embeddings
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- Active Learning from Weak and Strong Labelers
- Locally Non-linear Embeddings for Extreme Multi-label Learning
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- Teaching Machines to Read and Comprehend
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- Large-Scale Bayesian Multi-Label Learning via Positive Labels Only
- A class of network models recoverable by spectral clustering
- From random walks to distances on unweighted graphs
- Semi-supervised Learning with Ladder Network
- Embedding Inference for Structured Multilabel Prediction
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