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Optimization

14,207 papers

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Papers

Gradients Weights improve Regression and Classification JMLR 2016
Learning Using Anti-Training with Sacrificial Data JMLR 2016
A Bounded p-norm Approximation of Max-Convolution for Sub-Quadratic Bayesian Inference on Additive Factors JMLR 2016
Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares JMLR 2016
DSA: Decentralized Double Stochastic Averaging Gradient Algorithm JMLR 2016
Convergence of an Alternating Maximization Procedure JMLR 2016
StructED: Risk Minimization in Structured Prediction JMLR 2016
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics JMLR 2016
Iterative Regularization for Learning with Convex Loss Functions JMLR 2016
Model-free Variable Selection in Reproducing Kernel Hilbert Space JMLR 2016
Structure-Leveraged Methods in Breast Cancer Risk Prediction JMLR 2016
LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems JMLR 2016
L1-Regularized Least Squares for Support Recovery of High Dimensional Single Index Models with Gaussian Designs JMLR 2016
Rate Optimal Denoising of Simultaneously Sparse and Low Rank Matrices JMLR 2016
Convex Regression with Interpretable Sharp Partitions JMLR 2016
A Network That Learns Strassen Multiplication JMLR 2016
Revisiting the Nyström Method for Improved Large-scale Machine Learning JMLR 2016
Volumetric Spanners: An Efficient Exploration Basis for Learning JMLR 2016
The Constrained Dantzig Selector with Enhanced Consistency JMLR 2016
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation JMLR 2016
Kernel Estimation and Model Combination in A Bandit Problem with Covariates JMLR 2016
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights JMLR 2016
A General Framework for Constrained Bayesian Optimization using Information-based Search JMLR 2016
Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing JMLR 2016
Bounding the Search Space for Global Optimization of Neural Networks Learning Error: An Interval Analysis Approach JMLR 2016