Vidya Muthukumar

1. A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning
   2021/09/06 by Yehuda Dar, Dar, Yehuda, Vidya Muthukumar +4 · 2 voices · 3 citations
   Computer Science · Engineering · #Neural Networks and Applications #Face and Expression Recognition #Sparse and Compressive Sensing Techniques
2. Towards Last-layer Retraining for Group Robustness with Fewer Annotations
   2023/09/15 by Tyler LaBonte, Vidya Muthukumar, LaBonte, Tyler +3 · 7 citations
   Computer Science · #Domain Adaptation and Few-Shot Learning #Advanced Neural Network Applications #Multimodal Machine Learning Applications
3. Harmless interpolation in regression and classification with structured\n features
   2021/11/09 by Andrew D. McRae, Santhosh Karnik, McRae, Andrew D. +6 · 4 citations
   Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST) #Stochastic Gradient Optimization Techniques
4. New Equivalences Between Interpolation and SVMs: Kernels and Structured Features
   2023/05/03 by Chiraag Kaushik, Kaushik, Chiraag, Andrew D. McRae +5 · 1 citation
   Computer Science · #46E22 #62H30 #62J07 #68Q32 #FOS: Computer and information sciences #Face and Expression Recognition #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
5. Recovery of latent inner products from an anisotropic Gaussian random geometric graph
   2026/07/26 by Cheng Mao, Vidya Muthukumar
   #math.ST #stat.ML #stat.TH