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math.ST2026
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_…
stat.ML2026
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…
stat.ML2026
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…