Copertina

Near-Optimal Real-Time Personalization with Simple Transformers

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	An, Lin, Li, Andrew A., Nemala, Vaisnavi, Visotsky, Gabriel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Optimization and Control Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model
di: An, Lin, et al.
Pubblicazione: (2024)

Perseus: A Simple and Optimal High-Order Method for Variational Inequalities
di: Lin, Tianyi, et al.
Pubblicazione: (2022)

A Simple, Optimal and Efficient Algorithm for Online Exp-Concave Optimization
di: Wang, Yi-Han, et al.
Pubblicazione: (2025)

ROOT-SGD: Sharp Nonasymptotics and Near-Optimal Asymptotics in a Single Algorithm
di: Li, Chris Junchi, et al.
Pubblicazione: (2020)

Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
di: Lowy, Andrew, et al.
Pubblicazione: (2025)

A Data-Driven Real-Time Optimal Power Flow Algorithm Using Local Feedback
di: Liang, Heng, et al.
Pubblicazione: (2025)

Near-Optimal Algorithms for Group Distributionally Robust Optimization and Beyond
di: Soma, Tasuku, et al.
Pubblicazione: (2022)

Corruption-Tolerant Asynchronous Q-Learning with Near-Optimal Rates
di: Maity, Sreejeet, et al.
Pubblicazione: (2025)

Near-Optimal Decentralized Stochastic Nonconvex Optimization with Heavy-Tailed Noise
di: Wang, Menglian, et al.
Pubblicazione: (2026)

Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity
di: Zhou, Qihao, et al.
Pubblicazione: (2024)

An Optimal Control Approach To Transformer Training
di: Akman, Kağan, et al.
Pubblicazione: (2026)

Near-Optimal Distributed Linear-Quadratic Regulator for Networked Systems
di: Shin, Sungho, et al.
Pubblicazione: (2022)

Policy Gradient Converges to the Globally Optimal Policy for Nearly Linear-Quadratic Regulators
di: Han, Yinbin, et al.
Pubblicazione: (2023)

Nearly Optimal Linear Convergence of Stochastic Primal-Dual Methods for Linear Programming
di: Lu, Haihao, et al.
Pubblicazione: (2021)

Near-Optimal Primal-Dual Algorithm for Learning Linear Mixture CMDPs with Adversarial Rewards
di: Yu, Kihyun, et al.
Pubblicazione: (2026)

A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization
di: Dagréou, Mathieu, et al.
Pubblicazione: (2023)

A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
di: Zhao, Heyang, et al.
Pubblicazione: (2023)

A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
di: Gong, Xiaochuan, et al.
Pubblicazione: (2024)

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
di: Kitamura, Toshinori, et al.
Pubblicazione: (2024)

A Simple Finite-Time Analysis of TD Learning with Linear Function Approximation
di: Mitra, Aritra
Pubblicazione: (2024)

Near-Optimal Convergence of Accelerated Gradient Methods under Generalized and $(L_0, L_1)$-Smoothness
di: Tyurin, Alexander
Pubblicazione: (2025)

A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
di: Wang, Bokun, et al.
Pubblicazione: (2023)

Near-Optimal Solutions of Constrained Learning Problems
di: Elenter, Juan, et al.
Pubblicazione: (2024)

Stochastic Approximation with Block Coordinate Optimal Stepsizes
di: Jiang, Tao, et al.
Pubblicazione: (2025)

Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Dataset
di: Boero, Ignacio, et al.
Pubblicazione: (2025)

Optimal Rates for Robust Stochastic Convex Optimization
di: Gao, Changyu, et al.
Pubblicazione: (2024)

Understanding the training of infinitely deep and wide ResNets with Conditional Optimal Transport
di: Barboni, Raphaël, et al.
Pubblicazione: (2024)

S-CFE: Simple Counterfactual Explanations
di: Sadiku, Shpresim, et al.
Pubblicazione: (2024)

Near-Linear Time Projection onto the $\ell_{1,\infty}$ Ball; Application to Sparse Autoencoders
di: Perez, Guillaume, et al.
Pubblicazione: (2023)

Accelerated Gradient Tracking over Time-varying Graphs for Decentralized Optimization
di: Li, Huan, et al.
Pubblicazione: (2021)

Mutual Information Optimal Control of Discrete-Time Linear Systems
di: Enami, Shoju, et al.
Pubblicazione: (2025)

Attentive Convolutional Deep Reinforcement Learning for Optimizing Solar-Storage Systems in Real-Time Electricity Markets
di: Li, Jinhao, et al.
Pubblicazione: (2024)

Insights on Muon from Simple Quadratics
di: Gonon, Antoine, et al.
Pubblicazione: (2026)

Optimal Transport for Machine Learners
di: Peyré, Gabriel
Pubblicazione: (2025)

Real-Time Optimal Control via Transformer Networks and Bernstein Polynomials
di: MacLin, Gage, et al.
Pubblicazione: (2025)

An Elementary Proof of the Near Optimality of LogSumExp Smoothing
di: Samakhoana, Thabo, et al.
Pubblicazione: (2025)

Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
di: Kan, Kelvin, et al.
Pubblicazione: (2025)

Optimal and Diffusion Transports in Machine Learning
di: Peyré, Gabriel
Pubblicazione: (2025)

The Rich and the Simple: On the Implicit Bias of Adam and SGD
di: Vasudeva, Bhavya, et al.
Pubblicazione: (2025)

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
di: Zhang, Qixin, et al.
Pubblicazione: (2025)