A Best-of-Both-Worlds Proof for Tsallis-INF without Fenchel Conjugates
Fuente:
arXiv
Saved in:
| Main Authors: | Lee, Wei-Cheng, Orabona, Francesco |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
by: Lee, Wei-Cheng, et al.
Published: (2025)
by: Lee, Wei-Cheng, et al.
Published: (2025)
A Modern Introduction to Online Learning
by: Orabona, Francesco
Published: (2019)
by: Orabona, Francesco
Published: (2019)
A Note on How to Remove the $\ln\ln T$ Term from the Squint Bound
by: Orabona, Francesco
Published: (2026)
by: Orabona, Francesco
Published: (2026)
New Lower Bounds for Stochastic Non-Convex Optimization through Divergence Decomposition
by: Saad, El Mehdi, et al.
Published: (2025)
by: Saad, El Mehdi, et al.
Published: (2025)
An Equivalence Between Static and Dynamic Regret Minimization
by: Jacobsen, Andrew, et al.
Published: (2024)
by: Jacobsen, Andrew, et al.
Published: (2024)
New Perspectives on the Polyak Stepsize: Surrogate Functions and Negative Results
by: Orabona, Francesco, et al.
Published: (2025)
by: Orabona, Francesco, et al.
Published: (2025)
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
by: Cutkosky, Ashok, et al.
Published: (2023)
by: Cutkosky, Ashok, et al.
Published: (2023)
Best of Many in Both Worlds: Online Resource Allocation with Predictions under Unknown Arrival Model
by: An, Lin, et al.
Published: (2024)
by: An, Lin, et al.
Published: (2024)
LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits
by: Kato, Masahiro, et al.
Published: (2024)
by: Kato, Masahiro, et al.
Published: (2024)
Beyond the Ideal: Analyzing the Inexact Muon Update
by: Shulgin, Egor, et al.
Published: (2025)
by: Shulgin, Egor, et al.
Published: (2025)
Best of Both Worlds Guarantees for Smoothed Online Quadratic Optimization
by: Bhuyan, Neelkamal, et al.
Published: (2023)
by: Bhuyan, Neelkamal, et al.
Published: (2023)
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization
by: Li, Zhehao, et al.
Published: (2025)
by: Li, Zhehao, et al.
Published: (2025)
Tsallis Entropy Regularization for Linearly Solvable MDP and Linear Quadratic Regulator
by: Hashizume, Yota, et al.
Published: (2024)
by: Hashizume, Yota, et al.
Published: (2024)
Continuous-time q-Learning for Jump-Diffusion Models under Tsallis Entropy
by: Bo, Lijun, et al.
Published: (2024)
by: Bo, Lijun, et al.
Published: (2024)
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
by: Maranjyan, Artavazd, et al.
Published: (2025)
by: Maranjyan, Artavazd, et al.
Published: (2025)
Nonlinear Fenchel Conjugates
by: Schiela, Anton, et al.
Published: (2024)
by: Schiela, Anton, et al.
Published: (2024)
High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings
by: Priem, Rémy, et al.
Published: (2025)
by: Priem, Rémy, et al.
Published: (2025)
Which Features are Best for Successor Features?
by: Ollivier, Yann
Published: (2025)
by: Ollivier, Yann
Published: (2025)
Combinatorial Causal Bandits without Graph Skeleton
by: Feng, Shi, et al.
Published: (2023)
by: Feng, Shi, et al.
Published: (2023)
Convergence rate of Tsallis entropic regularized optimal transport
by: Suguro, Takeshi, et al.
Published: (2023)
by: Suguro, Takeshi, et al.
Published: (2023)
Increasing Both Batch Size and Learning Rate Accelerates Stochastic Gradient Descent
by: Umeda, Hikaru, et al.
Published: (2024)
by: Umeda, Hikaru, et al.
Published: (2024)
Best Arm Identification with LLM Judges and Limited Human
by: Ao, Ruicheng, et al.
Published: (2026)
by: Ao, Ruicheng, et al.
Published: (2026)
Both Asymptotic and Non-Asymptotic Convergence of Quasi-Hyperbolic Momentum using Increasing Batch Size
by: Imaizumi, Kento, et al.
Published: (2025)
by: Imaizumi, Kento, et al.
Published: (2025)
Automated Proof of Polynomial Inequalities via Reinforcement Learning
by: Liu, Banglong, et al.
Published: (2025)
by: Liu, Banglong, et al.
Published: (2025)
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
by: Chen, Jun, et al.
Published: (2023)
by: Chen, Jun, et al.
Published: (2023)
The Stochastic Conjugate Subgradient Algorithm For Kernel Support Vector Machines
by: Zhang, Di, et al.
Published: (2024)
by: Zhang, Di, et al.
Published: (2024)
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
by: Beznosikov, Aleksandr, et al.
Published: (2023)
by: Beznosikov, Aleksandr, et al.
Published: (2023)
A Unified Theory of Stochastic Proximal Point Methods without Smoothness
by: Richtárik, Peter, et al.
Published: (2024)
by: Richtárik, Peter, et al.
Published: (2024)
A simple uniformly optimal method without line search for convex optimization
by: Li, Tianjiao, et al.
Published: (2023)
by: Li, Tianjiao, et al.
Published: (2023)
Geometric Foundations of Tuning without Forgetting in Neural ODEs
by: Bayram, Erkan, et al.
Published: (2025)
by: Bayram, Erkan, et al.
Published: (2025)
Loss Landscape Characterization of Neural Networks without Over-Parametrization
by: Islamov, Rustem, et al.
Published: (2024)
by: Islamov, Rustem, et al.
Published: (2024)
Solving Stochastic Variational Inequalities without the Bounded Variance Assumption
by: Alacaoglu, Ahmet, et al.
Published: (2026)
by: Alacaoglu, Ahmet, et al.
Published: (2026)
Residual subspace evolution strategies for nonlinear inverse problems
by: Alemanno, Francesco
Published: (2025)
by: Alemanno, Francesco
Published: (2025)
Double Variance Reduction: A Smoothing Trick for Composite Optimization Problems without First-Order Gradient
by: Di, Hao, et al.
Published: (2024)
by: Di, Hao, et al.
Published: (2024)
Non-convex entropic mean-field optimization via Best Response flow
by: Lascu, Razvan-Andrei, et al.
Published: (2025)
by: Lascu, Razvan-Andrei, et al.
Published: (2025)
The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints
by: Wang, Po-Wei, et al.
Published: (2017)
by: Wang, Po-Wei, et al.
Published: (2017)
High-dimensional Mean-Field Games by Particle-based Flow Matching
by: Yu, Jiajia, et al.
Published: (2025)
by: Yu, Jiajia, et al.
Published: (2025)
Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
by: Hose, Henrik, et al.
Published: (2024)
by: Hose, Henrik, et al.
Published: (2024)
Operator World Models for Reinforcement Learning
by: Novelli, Pietro, et al.
Published: (2024)
by: Novelli, Pietro, et al.
Published: (2024)
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
by: Liu, Zijian, et al.
Published: (2024)
by: Liu, Zijian, et al.
Published: (2024)
Similar Items
-
A Finite-Time Analysis of TD Learning with Linear Function Approximation without Projections or Strong Convexity
by: Lee, Wei-Cheng, et al.
Published: (2025) -
A Modern Introduction to Online Learning
by: Orabona, Francesco
Published: (2019) -
A Note on How to Remove the $\ln\ln T$ Term from the Squint Bound
by: Orabona, Francesco
Published: (2026) -
New Lower Bounds for Stochastic Non-Convex Optimization through Divergence Decomposition
by: Saad, El Mehdi, et al.
Published: (2025) -
An Equivalence Between Static and Dynamic Regret Minimization
by: Jacobsen, Andrew, et al.
Published: (2024)