Abstract is missing.
- A Survey of Modern Questions and Challenges in Feature ExtractionDmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar. 1-18 [doi]
- A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component AnalysisHassan Ashtiani, Ali Ghodsi. 19-29 [doi]
- Learning Sparse Metrics, One Feature at a TimeYuval Atzmon, Uri Shalit, Gal Chechik. 30-48 [doi]
- Stage-wise Training: An Improved Feature Learning Strategy for Deep ModelsElnaz Barshan, Paul W. Fieguth. 49-59 [doi]
- Learning Multi-channel Deep Feature Representations for Face RecognitionXue-wen Chen 0001, Melih S. Aslan, Kunlei Zhang, Thomas S. Huang. 60-71 [doi]
- Kernel Extraction via Voted Risk MinimizationCorinna Cortes, Prasoon Goyal, Vitaly Kuznetsov, Mehryar Mohri. 72-89 [doi]
- A Computationally Efficient Method for Estimating Semi Parametric Regression FunctionsXia Cui, Ying Lu, Heng Peng. 90-102 [doi]
- Spatiotemporal Feature Extraction with Data-Driven Koopman OperatorsDimitrios Giannakis, Joanna Slawinska, Zhizhen Zhao. 103-115 [doi]
- Convolutional Dictionary Learning through Tensor FactorizationFurong Huang, Animashree Anandkumar. 116-129 [doi]
- FEAST at Play: Feature ExtrAction using Score function TensorsMajid Janzamin, Hanie Sedghi, U. N. Niranjan, Animashree Anandkumar. 130-144 [doi]
- The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance PriorsMelih Kandemir, Fred A. Hamprecht. 145-159 [doi]
- Deep Clustered Convolutional KernelsMinyoung Kim, Luca Rigazio. 160-172 [doi]
- Theory and Algorithms for the Localized Setting of Learning KernelsYunwen Lei, Alexander Binder, Ürün Dogan, Marius Kloft. 173-195 [doi]
- Convergent Learning: Do different neural networks learn the same representations?Yixuan Li, Jason Yosinski, Jeff Clune, Hod Lipson, John E. Hopcroft. 196-212 [doi]
- Hierarchical Feature Extraction for Efficient Design of Microfluidic Flow PatternsKin Gwn Lore, Daniel Stoecklein, Michael Davies, Baskar Ganapathysubramanian, Soumik Sarkar. 213-225 [doi]
- Generalization Bounds for Supervised Dimensionality ReductionMehryar Mohri, Afshin Rostamizadeh, Dmitry Storcheus. 226-241 [doi]
- Modular Autoencoders for Ensemble Feature ExtractionHenry W. J. Reeve, Gavin Brown. 242-259 [doi]
- Minimum description length (MDL) regularization for online learningGil I. Shamir. 260-276 [doi]
- Covariance Selection in the Linear Mixed Effect ModeJonathan P. Williams, Ying Lu. 277-291 [doi]