Convex Optimization

SAdam: A Variant of Adam for Strongly Convex Functions ICLR 2020 Scalable Calibration of Affinity Matrices from Incomplete Observations ACML 2020 Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance COLT 2019 Efficiently testing local optimality and escaping saddles for ReLU networks ICLR 2019 Non-Convex Matrix Completion and Related Problems via Strong Duality JMLR 2019 Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs IJCAI 2018 Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification ACML 2018 Learning RBM with a DC programming Approach ACML 2017 Adaptive Averaging in Accelerated Descent Dynamics NeurIPS 2016 An equivalence between high dimensional Bayes optimal inference and M-estimation NeurIPS 2016 Convex Two-Layer Modeling with Latent Structure NeurIPS 2016 Dimension-Free Iteration Complexity of Finite Sum Optimization Problems NeurIPS 2016 MetaGrad: Multiple Learning Rates in Online Learning NeurIPS 2016 Optimal Black-Box Reductions Between Optimization Objectives NeurIPS 2016 A Universal Primal-Dual Convex Optimization Framework NeurIPS 2015 Collaboratively Learning Preferences from Ordinal Data NeurIPS 2015 Communication Complexity of Distributed Convex Learning and Optimization NeurIPS 2015 Convergence rates of sub-sampled Newton methods NeurIPS 2015 Efficient Non-greedy Optimization of Decision Trees NeurIPS 2015 Fast Rates for Exp-concave Empirical Risk Minimization NeurIPS 2015 Spectral Norm Regularization of Orthonormal Representations for Graph Transduction NeurIPS 2015 Top-k Multiclass SVM NeurIPS 2015 Approximating Hierarchical MV-sets for Hierarchical Clustering NeurIPS 2014 Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings NeurIPS 2014 Convex Deep Learning via Normalized Kernels NeurIPS 2014