Copertina

High-Dimensional Statistics: Reflections on Progress and Open Problems

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Maleki, Arian, Sen, Subhabrata, Balakrishnan, Sivaraman, Zuber, Verena, Gao, Chao, Dudeja, Rishabh, Thrampoulidis, Christos, Zhang, Anru, Su, Weijie, Klusowski, Jason M., Loh, Po-Ling, Shojaie, Ali
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Statistics Theory Computation Methodology Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

High-Dimensional Asymptotics of Differentially Private PCA
di: Yun, Youngjoo, et al.
Pubblicazione: (2025)

Statistical-Computational Trade-offs in Tensor PCA and Related Problems via Communication Complexity
di: Dudeja, Rishabh, et al.
Pubblicazione: (2022)

Stability Bounds for Smooth Optimal Transport Maps and their Statistical Implications
di: Balakrishnan, Sivaraman, et al.
Pubblicazione: (2025)

Implicit Optimization Bias of Next-Token Prediction in Linear Models
di: Thrampoulidis, Christos
Pubblicazione: (2024)

Statistical Inference for Optimal Transport Maps: Recent Advances and Perspectives
di: Balakrishnan, Sivaraman, et al.
Pubblicazione: (2025)

Exact Coordinate Descent for High-Dimensional Regularized Huber Regression
di: Kim, Younghoon, et al.
Pubblicazione: (2025)

Optimality of Approximate Message Passing Algorithms for Spiked Matrix Models with Rotationally Invariant Noise
di: Dudeja, Rishabh, et al.
Pubblicazione: (2024)

On Differentially Private U Statistics
di: Chaudhuri, Kamalika, et al.
Pubblicazione: (2024)

Memory capacity of two layer neural networks with smooth activations
di: Madden, Liam, et al.
Pubblicazione: (2023)

Why Loss Re-weighting Works If You Stop Early: Training Dynamics of Unconstrained Features
di: Zhao, Yize, et al.
Pubblicazione: (2026)

Geometry of Semantics in Next-Token Prediction: How Optimization Implicitly Organizes Linguistic Representations
di: Zhao, Yize, et al.
Pubblicazione: (2025)

Supervised Contrastive Representation Learning: Landscape Analysis with Unconstrained Features
di: Behnia, Tina, et al.
Pubblicazione: (2024)

Statistical-Computational Trade-offs for Recursive Adaptive Partitioning Estimators
di: Tan, Yan Shuo, et al.
Pubblicazione: (2024)

Statistical inference on qualitative differences in the magnitude of an effect
di: Aaron Hudson, et al.
Pubblicazione: (2024)

Differentially Private Synthetic Data with Private Density Estimation
di: Bojkovic, Nikolija, et al.
Pubblicazione: (2024)

Sharp Trade-Offs in High-Dimensional Inference via 2-Level SLOPE
di: Bu, Zhiqi, et al.
Pubblicazione: (2025)

Classification Imbalance as Transfer Learning
di: Xia, Eric, et al.
Pubblicazione: (2026)

Stochastic Gradient Descent for Nonparametric Additive Regression
di: Chen, Xin, et al.
Pubblicazione: (2024)

A Note on Rounding Matchings in General Graphs
di: Dudeja, Aditi
Pubblicazione: (2024)

Advantage Shaping as Surrogate Reward Maximization: Unifying Pass@K Policy Gradients
di: Thrampoulidis, Christos, et al.
Pubblicazione: (2025)

Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
di: Deng, Wenlong, et al.
Pubblicazione: (2023)

Memorization Capacity of Multi-Head Attention in Transformers
di: Mahdavi, Sadegh, et al.
Pubblicazione: (2023)

Facts in Stats: Impacts of Pretraining Diversity on Language Model Generalization
di: Behnia, Tina, et al.
Pubblicazione: (2025)

Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods
di: Taheri, Hossein, et al.
Pubblicazione: (2024)

Next-token prediction capacity: general upper bounds and a lower bound for transformers
di: Madden, Liam, et al.
Pubblicazione: (2024)

Implicit Bias of Spectral Descent and Muon on Multiclass Separable Data
di: Fan, Chen, et al.
Pubblicazione: (2025)

Implicit Bias and Fast Convergence Rates for Self-attention
di: Vasudeva, Bhavya, et al.
Pubblicazione: (2024)

Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining
di: Stromberg, Nathan, et al.
Pubblicazione: (2025)

On the Benefits of Accelerated Optimization in Robust and Private Estimation
di: Marchis, Laurentiu Andrei, et al.
Pubblicazione: (2025)

Statistical Inference for Low-Rank Tensors: Heteroskedasticity, Subgaussianity, and Applications
di: Agterberg, Joshua, et al.
Pubblicazione: (2024)

ShakyPrepend: A Multi-Group Learner with Improved Sample Complexity
di: Zhang, Lujing, et al.
Pubblicazione: (2026)

Robust Universal Inference For Misspecified Models
di: Park, Beomjo, et al.
Pubblicazione: (2023)

Testing Random Effects for Binomial Data
di: Kania, Lucas, et al.
Pubblicazione: (2025)

Sharp Convergence Rates for Matching Pursuit
di: Klusowski, Jason M., et al.
Pubblicazione: (2023)

A cute proof that makes $e$ natural
di: Loh, Po-Shen
Pubblicazione: (2025)

Diagonalizing the Softmax: Hadamard Initialization for Tractable Cross-Entropy Dynamics
di: Garrod, Connall, et al.
Pubblicazione: (2025)

The Sample Complexity of Simple Binary Hypothesis Testing
di: Pensia, Ankit, et al.
Pubblicazione: (2024)

A Friendly Tutorial on Mean-Field Spin Glass Techniques for Non-Physicists
di: Montanari, Andrea, et al.
Pubblicazione: (2022)

Causal effect estimation under network interference with mean-field methods
di: Bhattacharya, Sohom, et al.
Pubblicazione: (2024)

De-Preferential Attachment Random Graphs
di: Bandyopadhyay, Antar, et al.
Pubblicazione: (2025)