Accelerated Information Gradient flow. - Yifei Wang 005; Wuchen Li (CoRR, 2019)

Information Newton's flow: second-order optimization method in probability space. - Yifei Wang 005; Wuchen Li (CoRR, 2020)

Adaptive Newton Sketch: Linear-time Optimization with Quadratic Convergence and Effective Hessian Dimensionality. - Jonathan Lacotte; Yifei Wang 005; Mert Pilanci (ICML, 2021)

Search Direction Correction with Normalized Gradient Makes First-Order Methods Faster. - Yifei Wang 005; Zeyu Jia; Zaiwen Wen (SIAM J. Sci. Comput., 2021)

The Hidden Convex Optimization Landscape of Regularized Two-Layer ReLU Networks: an Exact Characterization of Optimal Solutions. - Yifei Wang 005; Jonathan Lacotte; Mert Pilanci (ICLR, 2022)

The Convex Geometry of Backpropagation: Neural Network Gradient Flows Converge to Extreme Points of the Dual Convex Program. - Yifei Wang 005; Mert Pilanci (ICLR, 2022)

Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits. - Yifei Wang 005; Tavor Z. Baharav; Yanjun Han; Jiantao Jiao; David Tse (NeurIPS, 2022)

A stochastic Stein Variational Newton method. - Alex Leviyev; Joshua Chen; Yifei Wang 005; Omar Ghattas; Aaron Zimmerman (CoRR, 2022)

ReLU Neural Networks Learn the Simplest Models: Neural Isometry and Exact Recovery. - Yifei Wang 005; Yixuan Hua; Emmanuel J. Candès; Mert Pilanci (CoRR, 2022)

Beyond the Best: Estimating Distribution Functionals in Infinite-Armed Bandits. - Yifei Wang 005; Tavor Z. Baharav; Yanjun Han; Jiantao Jiao; David Tse (CoRR, 2022)

Projected Wasserstein Gradient Descent for High-Dimensional Bayesian Inference. - Yifei Wang 005; Peng Chen; Wuchen Li (SIAM/ASA J. Uncertain. Quantification, 2022)

Parallel Deep Neural Networks Have Zero Duality Gap. - Yifei Wang 005; Tolga Ergen; Mert Pilanci (ICLR, 2023)

Polynomial-Time Solutions for ReLU Network Training: A Complexity Classification via Max-Cut and Zonotopes. - Yifei Wang 005; Mert Pilanci (CoRR, 2023)

A Decomposition Augmented Lagrangian Method for Low-Rank Semidefinite Programming. - Yifei Wang 005; Kangkang Deng; Haoyang Liu; Zaiwen Wen (SIAM J. Optim., 2023)

Sketching the Krylov subspace: faster computation of the entire ridge regularization path. - Yifei Wang 005; Mert Pilanci (J. Supercomput., 2023)

A Circuit Approach to Constructing Blockchains on Blockchains. - Ertem Nusret Tas; David Tse; Yifei Wang 005 (AFT, 2024)

A Library of Mirrors: Deep Neural Nets in Low Dimensions are Convex Lasso Models with Reflection Features. - Emi Zeger; Yifei Wang 005; Aaron Mishkin; Tolga Ergen; Emmanuel J. Candès; Mert Pilanci (CoRR, 2024)

Randomized Geometric Algebra Methods for Convex Neural Networks. - Yifei Wang 005; Sungyoon Kim; Paul Chu; Indu Subramaniam; Mert Pilanci (CoRR, 2024)

Optimal Neural Network Approximation of Wasserstein Gradient Direction via Convex Optimization. - Yifei Wang 005; Peng Chen; Mert Pilanci; Wuchen Li (SIAM J. Math. Data Sci., 2024)

Correction to: Sketching the Krylov subspace: faster computation of the entire ridge regularization path. - Yifei Wang 005; Mert Pilanci (J. Supercomput., 2024)

Overparameterized ReLU Neural Networks Learn the Simplest Model: Neural Isometry and Phase Transitions. - Yifei Wang 005; Yixuan Hua; Emmanuel J. Candès; Mert Pilanci (IEEE Trans. Inf. Theory, 2025)