kernel methods

Nonparametric Estimation of Multi-View Latent Variable Models ICML 2014 Optimizing Over Radial Kernels on Compact Manifolds CVPR 2014 Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels ICML 2014 Robust and Efficient Kernel Hyperparameter Paths with Guarantees ICML 2014 Saddle Points and Accelerated Perceptron Algorithms ICML 2014 Scalable Kernel Methods via Doubly Stochastic Gradients NeurIPS 2014 Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning NeurIPS 2014 Simultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction CVPR 2014 Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space NeurIPS 2014 Spectral Clustering with Jensen-type Kernels and their Multi-point Extensions CVPR 2014 Subspace Embeddings for the Polynomial Kernel NeurIPS 2014 The Complexity of Learning Halfspaces using Generalized Linear Methods COLT 2014 The limits of squared Euclidean distance regularization NeurIPS 2014 To go deep or wide in learning? AISTATS 2014 Unsupervised One-Class Learning for Automatic Outlier Removal CVPR 2014 Video Motion Segmentation Using New Adaptive Manifold Denoising Model CVPR 2014 A Framework for Shape Analysis via Hilbert Space Embedding ICCV 2013 A Generalized Kernel Approach to Structured Output Learning ICML 2013 A Kernel Test for Three-Variable Interactions NeurIPS 2013 An Adaptive Descriptor Design for Object Recognition in the Wild ICCV 2013 Analyzing the Harmonic Structure in Graph-Based Learning NeurIPS 2013 Approximate Inference in Continuous Determinantal Processes NeurIPS 2013 A Randomized Mirror Descent Algorithm for Large Scale Multiple Kernel Learning ICML 2013 B-test: A Non-parametric, Low Variance Kernel Two-sample Test NeurIPS 2013 Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment ICML 2013