single-index model

Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model ICLR 2025 Learning a Single Index Model from Anisotropic Data with Vanilla Stochastic Gradient Descent AISTATS 2025 Learning Single Index Models with Diffusion Priors ICML 2025 Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions COLT 2025 Mean-field analysis of polynomial-width two-layer neural network beyond finite time horizon COLT 2025 Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning ICML 2025 Near-optimal Active Regression of Single-Index Models ICLR 2025 Nonlinear transformers can perform inference-time feature learning ICML 2025 Phase transitions for the existence of unregularized M-estimators in single index models ICML 2025 Agnostic Active Learning of Single Index Models with Linear Sample Complexity COLT 2024 Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract) COLT 2024 Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors AAAI 2024 Enhancing Sufficient Dimension Reduction via Hellinger Correlation ICML 2024 Inference on High-dimensional Single-index Models with Streaming Data JMLR 2024 Learning sum of diverse features: computational hardness and efficient gradient-based training for ridge combinations COLT 2024 Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit NeurIPS 2024 Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context NeurIPS 2024 Pruning is Optimal for Learning Sparse Features in High-Dimensions COLT 2024 Robust group and simultaneous inferences for high-dimensional single index model NeurIPS 2024 Robustly Learning Single-Index Models via Alignment Sharpness ICML 2024 Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models NeurIPS 2024 Symmetric Single Index Learning ICLR 2024 Agnostically Learning Single-Index Models using Omnipredictors NeurIPS 2023 Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation ICML 2023 Gradient-Based Feature Learning under Structured Data NeurIPS 2023