Saved in:
| Main Authors: | Andrade, Francisco, Peyré, Gabriel, Poon, Clarice |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2505.07124 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Sparsistency for Inverse Optimal Transport
by: Andrade, Francisco, et al.
Published: (2023)
by: Andrade, Francisco, et al.
Published: (2023)
On the global convergence of gradient descent for wide shallow models with bounded nonlinearities
by: Petit, Romain, et al.
Published: (2026)
by: Petit, Romain, et al.
Published: (2026)
Statistical Inverse Problems in Hilbert Scales
by: Rastogi, Abhishake
Published: (2022)
by: Rastogi, Abhishake
Published: (2022)
Inferring Change Points in Regression via Sample Weighting
by: Arpino, Gabriel, et al.
Published: (2026)
by: Arpino, Gabriel, et al.
Published: (2026)
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
by: Altekrüger, Fabian, et al.
Published: (2023)
by: Altekrüger, Fabian, et al.
Published: (2023)
Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators
by: Chen, Youguang, et al.
Published: (2026)
by: Chen, Youguang, et al.
Published: (2026)
Stress-Aware Learning under KL Drift via Trust-Decayed Mirror Descent
by: Raj, Gabriel Nixon
Published: (2025)
by: Raj, Gabriel Nixon
Published: (2025)
Statistical analysis of Inverse Entropy-regularized Reinforcement Learning
by: Belomestny, Denis, et al.
Published: (2025)
by: Belomestny, Denis, et al.
Published: (2025)
The Central Role of the Loss Function in Reinforcement Learning
by: Wang, Kaiwen, et al.
Published: (2024)
by: Wang, Kaiwen, et al.
Published: (2024)
Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
by: Cheng, Ziheng, et al.
Published: (2025)
by: Cheng, Ziheng, et al.
Published: (2025)
Partitioning the Sample Space for a More Precise Shannon Entropy Estimation
by: Bastos, Gabriel F. A., et al.
Published: (2025)
by: Bastos, Gabriel F. A., et al.
Published: (2025)
Efficient Inference for Inverse Reinforcement Learning and Dynamic Discrete Choice Models
by: van der Laan, Lars, et al.
Published: (2025)
by: van der Laan, Lars, et al.
Published: (2025)
Refined Risk Bounds for Unbounded Losses via Transductive Priors
by: Qian, Jian, et al.
Published: (2024)
by: Qian, Jian, et al.
Published: (2024)
Optimal Transport under Group Fairness Constraints
by: Bleistein, Linus, et al.
Published: (2026)
by: Bleistein, Linus, et al.
Published: (2026)
A Fenchel-Young Loss Approach to Data-Driven Inverse Optimization
by: Li, Zhehao, et al.
Published: (2025)
by: Li, Zhehao, et al.
Published: (2025)
Ratio-based Loss Functions
by: Helgerth, Lena, et al.
Published: (2026)
by: Helgerth, Lena, et al.
Published: (2026)
Nonparametric Instrumental Variable Analysis Without Structural Equations: Debiased Inference on Functionals of Inverse Problems with No Solutions
by: Shen, Zikai, et al.
Published: (2026)
by: Shen, Zikai, et al.
Published: (2026)
Nonparametric Estimation of Joint Entropy via Partitioned Sample-Spacing
by: Ho, Jungwoo, et al.
Published: (2025)
by: Ho, Jungwoo, et al.
Published: (2025)
Asymptotically Optimal Problem-Dependent Bandit Policies for Transfer Learning
by: Prevost, Adrien, et al.
Published: (2025)
by: Prevost, Adrien, et al.
Published: (2025)
A Generative Approach to Quasi-Random Sampling from Copulas via Space-Filling Designs
by: Wang, Sumin, et al.
Published: (2024)
by: Wang, Sumin, et al.
Published: (2024)
Unbiased Estimating Equation on Inverse Divergence and Its Conditions
by: Kobayashi, Masahiro, et al.
Published: (2024)
by: Kobayashi, Masahiro, et al.
Published: (2024)
Sample Amplification: Increasing Dataset Size even when Learning is Impossible
by: Axelrod, Brian, et al.
Published: (2019)
by: Axelrod, Brian, et al.
Published: (2019)
Decomposing Probabilistic Scores: Reliability, Information Loss and Uncertainty
by: Charpentier, Arthur, et al.
Published: (2026)
by: Charpentier, Arthur, et al.
Published: (2026)
Inferring Change Points in High-Dimensional Regression via Approximate Message Passing
by: Arpino, Gabriel, et al.
Published: (2024)
by: Arpino, Gabriel, et al.
Published: (2024)
Breaking AR's Sampling Bottleneck: Provable Acceleration via Diffusion Language Models
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
Optimization, Isoperimetric Inequalities, and Sampling via Lyapunov Potentials
by: Chen, August Y., et al.
Published: (2024)
by: Chen, August Y., et al.
Published: (2024)
Training Implicit Generative Models via an Invariant Statistical Loss
by: de Frutos, José Manuel, et al.
Published: (2024)
by: de Frutos, José Manuel, et al.
Published: (2024)
Statistical-Computational Trade-offs in Tensor PCA and Related Problems via Communication Complexity
by: Dudeja, Rishabh, et al.
Published: (2022)
by: Dudeja, Rishabh, et al.
Published: (2022)
Sampling from the Mean-Field Stationary Distribution
by: Kook, Yunbum, et al.
Published: (2024)
by: Kook, Yunbum, et al.
Published: (2024)
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking
by: Rioux, Gabriel, et al.
Published: (2024)
by: Rioux, Gabriel, et al.
Published: (2024)
Sampling conditioned diffusions via Pathspace Projected Monte Carlo
by: Grafke, Tobias
Published: (2025)
by: Grafke, Tobias
Published: (2025)
Kernel Two-Sample Testing via Directional Components Analysis
by: Cui, Rui, et al.
Published: (2025)
by: Cui, Rui, et al.
Published: (2025)
The Sample Complexity of Multicalibration
by: Collina, Natalie, et al.
Published: (2026)
by: Collina, Natalie, et al.
Published: (2026)
Learning from Aggregate responses: Instance Level versus Bag Level Loss Functions
by: Javanmard, Adel, et al.
Published: (2024)
by: Javanmard, Adel, et al.
Published: (2024)
Characterizing Dependence of Samples along the Langevin Dynamics and Algorithms via Contraction of $Φ$-Mutual Information
by: Liang, Jiaming, et al.
Published: (2024)
by: Liang, Jiaming, et al.
Published: (2024)
When Are Trade-Off Functions Testable from Finite Samples?
by: Shi, Kaining, et al.
Published: (2026)
by: Shi, Kaining, et al.
Published: (2026)
Adaptive Sample Aggregation In Transfer Learning
by: Hanneke, Steve, et al.
Published: (2024)
by: Hanneke, Steve, et al.
Published: (2024)
Conformal Risk Control for Non-Monotonic Losses
by: Angelopoulos, Anastasios N.
Published: (2026)
by: Angelopoulos, Anastasios N.
Published: (2026)
Sampling from multi-modal distributions with polynomial query complexity in fixed dimension via reverse diffusion
by: Vacher, Adrien, et al.
Published: (2024)
by: Vacher, Adrien, et al.
Published: (2024)
Kernel Two-Sample Tests in High Dimension: Interplay Between Moment Discrepancy and Dimension-and-Sample Orders
by: Yan, Jian, et al.
Published: (2021)
by: Yan, Jian, et al.
Published: (2021)
Similar Items
-
Sparsistency for Inverse Optimal Transport
by: Andrade, Francisco, et al.
Published: (2023) -
On the global convergence of gradient descent for wide shallow models with bounded nonlinearities
by: Petit, Romain, et al.
Published: (2026) -
Statistical Inverse Problems in Hilbert Scales
by: Rastogi, Abhishake
Published: (2022) -
Inferring Change Points in Regression via Sample Weighting
by: Arpino, Gabriel, et al.
Published: (2026) -
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
by: Altekrüger, Fabian, et al.
Published: (2023)