NeurIPS(NIPS) 2015 论文列表Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, FE 2015, co-located with the 29th Annual Conference on Neural Information Processing Systems (NIPS 2015), Montreal, Canada, December 11-12, 2015. |
Covariance Selection in the Linear Mixed Effect Mode.
Minimum description length (MDL) regularization for online learning.
Modular Autoencoders for Ensemble Feature Extraction.
Generalization Bounds for Supervised Dimensionality Reduction.
Hierarchical Feature Extraction for Efficient Design of Microfluidic Flow Patterns.
Convergent Learning: Do different neural networks learn the same representations?
Theory and Algorithms for the Localized Setting of Learning Kernels.
Deep Clustered Convolutional Kernels.
The Deep Feed-Forward Gaussian Process: An Effective Generalization to Covariance Priors.
FEAST at Play: Feature ExtrAction using Score function Tensors.
Convolutional Dictionary Learning through Tensor Factorization.
Spatiotemporal Feature Extraction with Data-Driven Koopman Operators.
A Computationally Efficient Method for Estimating Semi Parametric Regression Functions.
Kernel Extraction via Voted Risk Minimization.
Learning Multi-channel Deep Feature Representations for Face Recognition.
Stage-wise Training: An Improved Feature Learning Strategy for Deep Models.
Learning Sparse Metrics, One Feature at a Time.
A Dimension-Independent Generalization Bound for Kernel Supervised Principal Component Analysis.
A Survey of Modern Questions and Challenges in Feature Extraction.