positive semidefinite matrix

A Quantum Information Theoretic Approach to Tractable Probabilistic Models UAI 2025 A Scalable Frank-Wolfe-Based Algorithm for the Max-Cut SDP ICML 2023 Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery AISTATS 2023 Statistical Analysis of Karcher Means for Random Restricted PSD Matrices AISTATS 2023 Convexity Certificates from Hessians NeurIPS 2022 Conic Descent and its Application to Memory-efficient Optimization over Positive Semidefinite Matrices NeurIPS 2020 Determinantal Reinforcement Learning AAAI 2019 Exact sampling of determinantal point processes with sublinear time preprocessing NeurIPS 2019 On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem AAAI 2019 Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering ICML 2018 Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data NeurIPS 2017 Global Convergence of Non-Convex Gradient Descent for Computing Matrix Squareroot AISTATS 2017 Optimal Dictionary for Least Squares Representation JMLR 2017 Faster Projection-free Convex Optimization over the Spectrahedron NeurIPS 2016 Efficient Output Kernel Learning for Multiple Tasks NeurIPS 2015 Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices NeurIPS 2015 Altitude Training: Strong Bounds for Single-Layer Dropout NeurIPS 2014 Deterministic Symmetric Positive Semidefinite Matrix Completion NeurIPS 2014 Robust Inverse Covariance Estimation under Noisy Measurements ICML 2014 Positive Semidefinite Metric Learning Using Boosting-like Algorithms JMLR 2012 Regression on Fixed-Rank Positive Semidefinite Matrices: A Riemannian Approach JMLR 2011 Low-Rank Kernel Learning with Bregman Matrix Divergences JMLR 2009 Positive Semidefinite Metric Learning with Boosting NeurIPS 2009 PSDBoost: Matrix-Generation Linear Programming for Positive Semidefinite Matrices Learning NeurIPS 2008 Euclidean Embedding of Co-occurrence Data JMLR 2007