Jagannath, Aukosh

10 publications

TMLR 2025 An Elementary Concentration Bound for Gibbs Measures Arising in Statistical Learning Theory Kelly Ramsay, Aukosh Jagannath, Shojaeddin Chenouri

JMLR 2025 Differentially Private Multivariate Medians Kelly Ramsay, Aukosh Jagannath, Shoja'eddin Chenouri

ICML 2025 Provable Benefits of Unsupervised Pre-Training and Transfer Learning via Single-Index Models Taj Jones-Mccormick, Aukosh Jagannath, Subhabrata Sen

ICLR 2024 High-Dimensional SGD Aligns with Emerging Outlier Eigenspaces Gerard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath

ICLR 2023 Effects of Graph Convolutions in Multi-Layer Networks Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

JMLR 2023 Graph Attention Retrospective Kimon Fountoulakis, Amit Levi, Shenghao Yang, Aseem Baranwal, Aukosh Jagannath

NeurIPS 2023 Optimality of Message-Passing Architectures for Sparse Graphs Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

NeurIPS 2022 High-Dimensional Limit Theorems for SGD: Effective Dynamics and Critical Scaling Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath

ICML 2021 Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath

JMLR 2021 Online Stochastic Gradient Descent on Non-Convex Losses from High-Dimensional Inference Gerard Ben Arous, Reza Gheissari, Aukosh Jagannath