Aukosh Jagannath

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 21

Top Topics

Optimization Problems

Linear Separability

Top Venues

J. Mach. Learn. Res.

Publications

Gérard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath
High-dimensional SGD aligns with emerging outlier eigenspaces. ICLR (2024)
David Gamarnik, Aukosh Jagannath, Alexander S. Wein
Hardness of Random Optimization Problems for Boolean Circuits, Low-Degree Polynomials, and Langevin Dynamics. SIAM J. Comput. 53 (1) (2024)
Gérard Ben Arous, Reza Gheissari, Jiaoyang Huang, Aukosh Jagannath
High-dimensional SGD aligns with emerging outlier eigenspaces. CoRR (2023)
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Optimality of Message-Passing Architectures for Sparse Graphs. NeurIPS (2023)
Aseem Baranwal, Aukosh Jagannath, Kimon Fountoulakis
Optimality of Message-Passing Architectures for Sparse Graphs. CoRR (2023)
Reza Gheissari, Aukosh Jagannath, Yiming Xu
Finding planted cliques using Markov chain Monte Carlo. CoRR (2023)
Kimon Fountoulakis, Amit Levi, Shenghao Yang, Aseem Baranwal, Aukosh Jagannath
Graph Attention Retrospective. J. Mach. Learn. Res. 24 (2023)
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Effects of Graph Convolutions in Multi-layer Networks. ICLR (2023)
Kelly Ramsay, Aukosh Jagannath, Shoja'eddin Chenouri
Concentration of the exponential mechanism and differentially private multivariate medians. CoRR (2022)
Gérard Ben Arous, Reza Gheissari, Aukosh Jagannath
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling. NeurIPS (2022)
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Effects of Graph Convolutions in Deep Networks. CoRR (2022)
Kimon Fountoulakis, Amit Levi, Shenghao Yang, Aseem Baranwal, Aukosh Jagannath
Graph Attention Retrospective. CoRR (2022)
Gérard Ben Arous, Reza Gheissari, Aukosh Jagannath
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling. CoRR (2022)
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization. ICML (2021)
Gérard Ben Arous, Reza Gheissari, Aukosh Jagannath
Online stochastic gradient descent on non-convex losses from high-dimensional inference. J. Mach. Learn. Res. 22 (2021)
Aseem Baranwal, Kimon Fountoulakis, Aukosh Jagannath
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization. CoRR (2021)
David Gamarnik, Aukosh Jagannath, Alexander S. Wein
Circuit Lower Bounds for the p-Spin Optimization Problem. CoRR (2021)
Gérard Ben Arous, Reza Gheissari, Aukosh Jagannath
A classification for the performance of online SGD for high-dimensional inference. CoRR (2020)
David Gamarnik, Aukosh Jagannath, Alexander S. Wein
Low-Degree Hardness of Random Optimization Problems. CoRR (2020)
David Gamarnik, Aukosh Jagannath, Alexander S. Wein
Low-Degree Hardness of Random Optimization Problems. FOCS (2020)
David Gamarnik, Aukosh Jagannath, Subhabrata Sen
The Overlap Gap Property in Principal Submatrix Recovery. CoRR (2019)
Steven Heilman, Aukosh Jagannath, Assaf Naor
. Discret. Comput. Geom. 50 (2) (2013)
Steven Heilman, Aukosh Jagannath, Assaf Naor
. STOC (2012)
Steven Heilman, Aukosh Jagannath, Assaf Naor
Solution of the propeller conjecture in $\R^3$ CoRR (2011)