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Regression

5,004 papers

Papers per year

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Papers

Learning Linear Dynamical Systems via Spectral Filtering NIPS 2017
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes NIPS 2017
Convolutional Gaussian Processes NIPS 2017
Best Response Regression NIPS 2017
Elementary Symmetric Polynomials for Optimal Experimental Design NIPS 2017
Maximum Margin Interval Trees NIPS 2017
Group Additive Structure Identification for Kernel Nonparametric Regression NIPS 2017
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks NIPS 2017
Spectral Mixture Kernels for Multi-Output Gaussian Processes NIPS 2017
On Quadratic Convergence of DC Proximal Newton Algorithm in Nonconvex Sparse Learning NIPS 2017
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition NIPS 2017
Deep Lattice Networks and Partial Monotonic Functions NIPS 2017
Action Centered Contextual Bandits NIPS 2017
Cost efficient gradient boosting NIPS 2017
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models NIPS 2017
Unbiased estimates for linear regression via volume sampling NIPS 2017
A Sharp Error Analysis for the Fused Lasso, with Application to Approximate Changepoint Screening NIPS 2017
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation NIPS 2017
A Screening Rule for l1-Regularized Ising Model Estimation NIPS 2017
Sobolev Training for Neural Networks NIPS 2017
Group Sparse Additive Machine NIPS 2017
Nonparametric Online Regression while Learning the Metric NIPS 2017
Accelerated Stochastic Greedy Coordinate Descent by Soft Thresholding Projection onto Simplex NIPS 2017
Multiresolution Kernel Approximation for Gaussian Process Regression NIPS 2017
Deep Multi-task Gaussian Processes for Survival Analysis with Competing Risks NIPS 2017