Jiaxi Ying

13 papers · 2019–2025 · 6 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🗺️ Taxonomy Completionist (23) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🧬 Topic Evolution 🏆 Grand Slam 🏆 Keyword Champion (4) 🗃️ Keyword Collector (66) 💎 Century Club · Bronze 🔥 Unstoppable · Bronze

Venues

NeurIPS (7) ICML (2) AAAI (1) AISTATS (1) ICLR (1) JMLR (1)

Top co-authors

Daniel Palomar (7) Jose Vinicius de Miranda Cardoso (6) Daniel P. Palomar (4) Jian-Feng CAI (3) Xiwen WANG (2) Sandeep Kumar (2) José Vinícius de M. Cardoso (2) Runhao Shi (1) Ruixue WEN (1) José Vinı́cius De Miranda Cardoso (1)

Research topics

Mathematics & Optimization (12) Mathematics (11) Machine Learning (9) Optimization (9) Core Methods (7) Optimization & Theory (5) Bayesian & Probabilistic (3) Learning Types (1)

Keywords

precision matrix estimation (4) gaussian graphical model (4) precision matrix (2) spectral constraint (2) graphical model (2) graph laplacian (2) graph learning (2) total positivity (2) graph structure (1) sparse pca (1) sparse estimation (1) sparse inverse covariance (1) sparse optimization (1) maximum likelihood estimation (1) graph clustering (1) gaussian markov random field (1) laplacian matrix (1) projected gradient descent (1) graphical lasso (1) side information (1)

Papers

Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity ICML 2025 Adaptive Passive-Aggressive Framework for Online Regression with Side Information NeurIPS 2024 A Fast and Provable Algorithm for Sparse Phase Retrieval ICLR 2024 Adaptive Estimation of Graphical Models under Total Positivity ICML 2023 Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity NeurIPS 2023 Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition NeurIPS 2023 Efficient Algorithms for General Isotone Optimization AAAI 2022 Learning Bipartite Graphs: Heavy Tails and Multiple Components NeurIPS 2022 Graphical Models in Heavy-Tailed Markets NeurIPS 2021 Minimax Estimation of Laplacian Constrained Precision Matrices AISTATS 2021 A Unified Framework for Structured Graph Learning via Spectral Constraints JMLR 2020 Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model NeurIPS 2020 Structured Graph Learning Via Laplacian Spectral Constraints NeurIPS 2019