Cover Image

Recommendations with Sparse Comparison Data: Provably Fast Convergence for Nonconvex Matrix Factorization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sankagiri, Suryanarayana, Etesami, Jalal, Grossglauser, Matthias
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Recycling History: Efficient Recommendations from Contextual Dueling Bandits
by: Sankagiri, Suryanarayana, et al.
Published: (2025)

Ranking Items from Discrete Ratings: The Cost of Unknown User Thresholds
by: Villemaud, Oscar, et al.
Published: (2025)

Measuring IIA Violations in Similarity Choices with Bayesian Models
by: Corrêa, Hugo Sales, et al.
Published: (2025)

Learning Nonlinear Factor Models with Unknown Monotone Links from Incomplete and Noisy Data
by: Chao, Yutong, et al.
Published: (2026)

Optimal Experiments for Partial Causal Effect Identification
by: Maringgele, Tobias, et al.
Published: (2026)

Online Mixture of Experts: No-Regret Learning for Optimal Collective Decision-Making
by: Liu, Larkin, et al.
Published: (2025)

Graph Learning Is Suboptimal in Causal Bandits
by: Shahverdikondori, Mohammad, et al.
Published: (2025)

Confounded Budgeted Causal Bandits
by: Jamshidi, Fateme, et al.
Published: (2024)

Active Context Selection Improves Simple Regret in Contextual Bandits
by: Shahverdikondori, Mohammad, et al.
Published: (2026)

Global Convergence to Nash Equilibrium in Nonconvex General-Sum Games under the $n$-Sided PL Condition
by: Chao, Yutong, et al.
Published: (2026)

Parameter identification in linear non-Gaussian causal models under general confounding
by: Tramontano, Daniele, et al.
Published: (2024)

Matrix Completion with Graph Information: A Provable Nonconvex Optimization Approach
by: Wang, Yao, et al.
Published: (2025)

Fast Proxy Experiment Design for Causal Effect Identification
by: Elahi, Sepehr, et al.
Published: (2024)

Pricing for Routing and Flow-Control in Payment Channel Networks
by: Sankagiri, Suryanarayana, et al.
Published: (2025)

The Benefits of Diversity: Combining Comparisons and Ratings for Efficient Scoring
by: Fageot, Julien, et al.
Published: (2026)

Provably Convergent Subgraph-wise Sampling for Fast GNN Training
by: Wang, Jie, et al.
Published: (2023)

Accelerating Matrix Factorization by Dynamic Pruning for Fast Recommendation
by: Wu, Yining, et al.
Published: (2024)

LMC: Fast Training of GNNs via Subgraph Sampling with Provable Convergence
by: Shi, Zhihao, et al.
Published: (2023)

Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization
by: Zhang, Gavin, et al.
Published: (2025)

Faster Convergence of Local SGD for Over-Parameterized Models
by: Qin, Tiancheng, et al.
Published: (2022)

Hierarchical Linkage Clustering Beyond Binary Trees and Ultrametrics
by: Dreveton, Maximilien, et al.
Published: (2025)

Optimal Graph Clustering without Edge Density Signals
by: Dreveton, Maximilien, et al.
Published: (2025)

Hierarchical Reinforcement Learning with Targeted Causal Interventions
by: Khorasani, Sadegh, et al.
Published: (2025)

Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
by: Azar, Eyar, et al.
Published: (2024)

On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
by: Zhou, Dongruo, et al.
Published: (2018)

Causal Effect Identification in a Sub-Population with Latent Variables
by: Abouei, Amir Mohammad, et al.
Published: (2024)

Why the Metric Backbone Preserves Community Structure
by: Dreveton, Maximilien, et al.
Published: (2024)

Convergence of Alternating Gradient Descent for Matrix Factorization
by: Ward, Rachel, et al.
Published: (2023)

Convergence and Recovery Guarantees of Unsupervised Neural Networks for Inverse Problems
by: Buskulic, Nathan, et al.
Published: (2023)

Provably Convergent Federated Trilevel Learning
by: Jiao, Yang, et al.
Published: (2023)

Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives
by: Oikonomidis, Konstantinos, et al.
Published: (2026)

Improved Convergence Rates of Muon Optimizer for Nonconvex Optimization
by: Nagashima, Shuntaro, et al.
Published: (2026)

Fast and Provable Nonconvex Robust Matrix Completion
by: Fu, Yichen, et al.
Published: (2026)

Fusing Rewards and Preferences in Reinforcement Learning
by: Khorasani, Sadegh, et al.
Published: (2025)

When Does Bottom-up Beat Top-down in Hierarchical Community Detection?
by: Dreveton, Maximilien, et al.
Published: (2023)

Provable Acceleration of Nesterov's Accelerated Gradient for Rectangular Matrix Factorization and Linear Neural Networks
by: Xu, Zhenghao, et al.
Published: (2024)

Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
by: Luo, Yuetian, et al.
Published: (2021)

Transformers Provably Learn Sparse XOR with Polylogarithmic Parameters
by: Han, Yaomengxi, et al.
Published: (2025)

Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings
by: Markou, Evan, et al.
Published: (2025)

Learning Provably Improves the Convergence of Gradient Descent
by: Song, Qingyu, et al.
Published: (2025)