Copertina

Top-$K$ ranking with a monotone adversary

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yang, Yuepeng, Chen, Antares, Orecchia, Lorenzo, Ma, Cong
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Information Theory Statistics Theory
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Random pairing MLE for estimation of item parameters in Rasch model
di: Yang, Yuepeng, et al.
Pubblicazione: (2024)

Sample efficient inductive matrix completion with noise and inexact side information
di: Yang, Yuepeng, et al.
Pubblicazione: (2026)

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices
di: Yang, Yuepeng, et al.
Pubblicazione: (2025)

Optimal tuning-free convex relaxation for noisy matrix completion
di: Yang, Yuepeng, et al.
Pubblicazione: (2022)

On the best approximation by finite Gaussian mixtures
di: Ma, Yun, et al.
Pubblicazione: (2024)

Orthogonal Approximate Message Passing with Optimal Spectral Initializations for Rectangular Spiked Matrix Models
di: Chen, Haohua, et al.
Pubblicazione: (2025)

Orthogonal Approximate Message Passing Algorithms for Rectangular Spiked Matrix Models with Rotationally Invariant Noise
di: Chen, Haohua, et al.
Pubblicazione: (2026)

On Observation Time for Recovering Latent Hawkes Networks
di: Linkerhägner, Jonas, et al.
Pubblicazione: (2026)

High-probability sample complexities for policy evaluation with linear function approximation
di: Li, Gen, et al.
Pubblicazione: (2023)

On damage of interpolation to adversarial robustness in regression
di: Peng, Jingfu, et al.
Pubblicazione: (2026)

The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
di: Shi, Laixi, et al.
Pubblicazione: (2023)

Generalization of LiNGAM that allows confounding
di: Suzuki, Joe, et al.
Pubblicazione: (2024)

Information-Theoretic Thresholds for the Alignments of Partially Correlated Graphs
di: Huang, Dong, et al.
Pubblicazione: (2024)

Breaking the Finite-Sample Barrier in Entropy Coupling
di: Asoodeh, Shahab, et al.
Pubblicazione: (2026)

Statistical Mean Estimation with Coded Relayed Observations
di: Ling, Yan Hao, et al.
Pubblicazione: (2025)

Optimal training-conditional regret for online conformal prediction
di: Liang, Jiadong, et al.
Pubblicazione: (2026)

Asymptotic Theory of Eigenvectors for Latent Embeddings with Generalized Laplacian Matrices
di: Fan, Jianqing, et al.
Pubblicazione: (2025)

Towards Faster Non-Asymptotic Convergence for Diffusion-Based Generative Models
di: Li, Gen, et al.
Pubblicazione: (2023)

Unifying AMP Algorithms for Rotationally-Invariant Models
di: Liu, Songbin, et al.
Pubblicazione: (2024)

Non-convex matrix sensing: Breaking the quadratic rank barrier in the sample complexity
di: Stöger, Dominik, et al.
Pubblicazione: (2024)

Assouad, Fano, and Le Cam with Interaction: A Unifying Lower Bound Framework and Characterization for Bandit Learnability
di: Chen, Fan, et al.
Pubblicazione: (2024)

A new pathway to generative artificial intelligence by minimizing the maximum entropy
di: Miotto, Mattia, 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)

Overfitting has a limitation: a model-independent generalization gap bound based on Rényi entropy
di: Suzuki, Atsushi, et al.
Pubblicazione: (2025)

Minimax rates of convergence for nonparametric regression under adversarial attacks
di: Peng, Jingfu, et al.
Pubblicazione: (2024)

Towards a mathematical theory for consistency training in diffusion models
di: Li, Gen, et al.
Pubblicazione: (2024)

Instance-Optimal Estimation with Multiple LLM Judges on a Budget
di: Lee, Junghyun, et al.
Pubblicazione: (2026)

Precise analysis of ridge interpolators under heavy correlations -- a Random Duality Theory view
di: Stojnic, Mihailo
Pubblicazione: (2024)

Fundamental limits of distributed covariance matrix estimation via a conditional strong data processing inequality
di: Rahmani, Mohammad Reza, et al.
Pubblicazione: (2025)

Information-Geometric Decomposition of Generalization Error in Unsupervised Learning
di: Kim, Gilhan
Pubblicazione: (2026)

Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
di: Zhou, Yuchen, et al.
Pubblicazione: (2023)

Fine-Grained Uncertainty Quantification via Collisions
di: Friedbaum, Jesse, et al.
Pubblicazione: (2024)

Efficient Unbiased Sparsification
di: Barnes, Leighton, et al.
Pubblicazione: (2024)

Minimax Optimality of Score-based Diffusion Models: Beyond the Density Lower Bound Assumptions
di: Zhang, Kaihong, et al.
Pubblicazione: (2024)

Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of $Φ$-Mutual Information
di: Liang, Jiaming, et al.
Pubblicazione: (2024)

Representatividad Muestral en la Incertidumbre Simétrica Multivariada para la Selección de Atributos
di: Sosa-Cabrera, Gustavo
Pubblicazione: (2024)

Fast Convergence of $Φ$-Divergence Along the Unadjusted Langevin Algorithm and Proximal Sampler
di: Mitra, Siddharth, et al.
Pubblicazione: (2024)

Sparse Max-Affine Regression
di: Kanj, Haitham, et al.
Pubblicazione: (2024)

Theoretical limits of descending $\ell_0$ sparse-regression ML algorithms
di: Stojnic, Mihailo
Pubblicazione: (2024)

Federated PCA and Estimation for Spiked Covariance Matrices: Optimal Rates and Efficient Algorithm
di: Li, Jingyang, et al.
Pubblicazione: (2024)