Kernel Methods

Fast Prediction for Large-Scale Kernel Machines NeurIPS 2014 Human Action Recognition Based on Context-Dependent Graph Kernels CVPR 2014 Kernel Mean Estimation and Stein Effect ICML 2014 Kernel Mean Estimation via Spectral Filtering NeurIPS 2014 Latent Support Measure Machines for Bag-of-Words Data Classification NeurIPS 2014 Learning with Fredholm Kernels NeurIPS 2014 Localized Data Fusion for Kernel k-Means Clustering with Application to Cancer Biology NeurIPS 2014 Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces NeurIPS 2014 Margins, Kernels and Non-linear Smoothed Perceptrons ICML 2014 Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection ICML 2014 Memory Efficient Kernel Approximation ICML 2014 Nonlinear Information-Theoretic Compressive Measurement Design ICML 2014 On a Theory of Nonparametric Pairwise Similarity for Clustering: Connecting Clustering to Classification NeurIPS 2014 On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection ICML 2014 Optimizing Over Radial Kernels on Compact Manifolds CVPR 2014 Quantized Kernel Learning for Feature Matching NeurIPS 2014 Robust and Efficient Kernel Hyperparameter Paths with Guarantees ICML 2014 Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space NeurIPS 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