conftrace_

random matrix theory

63 papers

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RMT

Co-occurring keywords

neural network (6616) random matrix (28) principal component analysis (316) gaussian mixture model (389) spectral analysis (239) asymptotic analysis (86) tensor decomposition (375) neural tangent kernel (205) spectral method (204) implicit regularization (93)

Papers

EigenShield: Inference-Time, Model-Agnostic Jailbreaking Defense via Causal Subspace Filtering AAAI 2026
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers JMLR 2025
A Random Matrix Approach to Low-Multilinear-Rank Tensor Approximation JMLR 2025
Universality of Kernel Random Matrices and Kernel Regression in the Quadratic Regime JMLR 2025
Distributed Least Squares in Small Space via Sketching and Bias Reduction NIPS 2024
Understanding Inverse Scaling and Emergence in Multitask Representation Learning AISTATS 2024
Random Fully Connected Neural Networks as Perturbatively Solvable Hierarchies JMLR 2024
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization AISTATS 2024
Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting NIPS 2024
Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes AAAI 2024
Entrywise error bounds for low-rank approximations of kernel matrices NIPS 2024
Matrix Denoising with Doubly Heteroscedastic Noise: Fundamental Limits and Optimal Spectral Methods NIPS 2024
Towards Understanding and Reducing Graph Structural Noise for GNNs ICML 2023
Sharp Recovery Thresholds of Tensor PCA Spectral Algorithms NIPS 2023
PCA-based Multi-Task Learning: a Random Matrix Approach ICML 2023
SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning NIPS 2023
A Theory of Unsupervised Speech Recognition ACL 2023
Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption ICML 2023
Bayesian Extensive-Rank Matrix Factorization with Rotational Invariant Priors NIPS 2023
A Random Matrix Analysis of Data Stream Clustering: Coping With Limited Memory Resources ICML 2022
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training JMLR 2022
Information bottleneck theory of high-dimensional regression: relevancy, efficiency and optimality NIPS 2022
More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize ICML 2022
A Random Matrix Perspective on Random Tensors JMLR 2022
Node Feature Kernels Increase Graph Convolutional Network Robustness AISTATS 2022