45 citations · 171 across the 35 of their papers we have counts for
40 papers
Linear Last-Iterate Convergence Rates for Optimistic Learning in Harmonic Games
John Lazarsfeld, Anas Barakat, Jacob Abernethy +4
We prove that the last iterate of Optimistic Follow-The-Regularized-Leader (OFTRL) converges at a linear rate to a Nash equilibrium in multiplayer harmonic games. Our result holds…
Next-token functional estimation
Milind Nakul, Vidya Muthukumar, Ashwin Pananjady
Suppose we observe the first points of a sequence of random variables having length , and wish to estimate a functional of the unobserved final point and the empirical mea…
Recovery of latent inner products from an anisotropic Gaussian random geometric graph
Cheng Mao, Vidya Muthukumar
We study the problem of recovering latent inner products from a random geometric graph with anisotropic Gaussian latent points. More precisely, for an i.i.d. sample $x_1, \dots, x_…
SGD Provably Prioritizes a Shortcut Spurious Feature in the XOR Model
Tyler LaBonte, Vidya Muthukumar
Neural networks are known to be susceptible to over-reliance on spurious correlations. However, the precise mechanism by which models exploit shortcut features is not fully underst…
How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
Kuo-Wei Lai, Guanghui Wang, Molei Tao +1
Overparameterized ML models, including neural networks, typically induce underdetermined training objectives with multiple global minima. The implicit bias refers to the limiting g…
On the Unreasonable Effectiveness of Last-layer Retraining
John C. Hill, Tyler LaBonte, Xinchen Zhang +1
Last-layer retraining (LLR) methods -- wherein the last layer of a neural network is reinitialized and retrained on a held-out set following ERM training -- have garnered interest…