Bin Yu

24 catalog papers. Name-matched publications do not establish a verified researcher identity.

Graduate School of Business, Columbia University, New York, New York 10027

Publications

• Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Instability, Computational Efficiency and Statistical Accuracy — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
• Revisiting minimum description length complexity in overparameterized models — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients — Journal of Machine Learning Research 2020 (name-matched, not ORCID-linked)
• Unique Sharp Local Minimum in L1-minimization Complete Dictionary Learning — Journal of Machine Learning Research 2020 (name-matched, not ORCID-linked)
• Log-concave sampling: Metropolis-Hastings algorithms are fast — Journal of Machine Learning Research 2019 (name-matched, not ORCID-linked)
• Fast MCMC Sampling Algorithms on Polytopes — Journal of Machine Learning Research 2018 (name-matched, not ORCID-linked)
• Local Identifiability of $\ell_1$-minimization Dictionary Learning: a Sufficient and Almost Necessary Condition — Journal of Machine Learning Research 2017 (name-matched, not ORCID-linked)
• Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs — Journal of Machine Learning Research 2015 (name-matched, not ORCID-linked)
• A Statistical Perspective on Algorithmic Leveraging — Journal of Machine Learning Research 2015 (name-matched, not ORCID-linked)
• Early Stopping and Non-parametric Regression: An Optimal Data-dependent Stopping Rule — Journal of Machine Learning Research 2014 (name-matched, not ORCID-linked)
• The shuffle estimator for explainable variance in fMRI experiments — The Annals of Applied Statistics 2013 (name-matched, not ORCID-linked)
• Supervised Feature Selection in Graphs with Path Coding Penalties and Network Flows — Journal of Machine Learning Research 2013 (name-matched, not ORCID-linked)
• Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming — Journal of Machine Learning Research 2012 (name-matched, not ORCID-linked)
• Spectral clustering and the high-dimensional stochastic blockmodel — The Annals of Statistics 2011 (name-matched, not ORCID-linked)
• Leo Breiman (1929–2005) — The Annals of Applied Statistics 2010 (name-matched, not ORCID-linked)
• Restricted Eigenvalue Properties for Correlated Gaussian Designs — Journal of Machine Learning Research 2010 (name-matched, not ORCID-linked)
• Lasso-type recovery of sparse representations for high-dimensional data — The Annals of Statistics 2009 (name-matched, not ORCID-linked)
• Stagewise Lasso — Journal of Machine Learning Research 2007 (name-matched, not ORCID-linked)
• On Model Selection Consistency of Lasso — Journal of Machine Learning Research 2006 (name-matched, not ORCID-linked)
• Sparse Boosting — Journal of Machine Learning Research 2006 (name-matched, not ORCID-linked)
• Boosting with early stopping: Convergence and consistency — The Annals of Statistics 2005 (name-matched, not ORCID-linked)
• Large Sample Properties of Weighted Monte Carlo Estimators — Operations Research 2005 (name-matched, not ORCID-linked)