Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria
Fuente:
arXiv
Guardado en:
| Autor principal: | Liang, Tengyuan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2022
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity
por: Liang, Tengyuan, et al.
Publicado: (2024)
por: Liang, Tengyuan, et al.
Publicado: (2024)
On the Uniform Convergence of Subdifferentials in Stochastic Optimization and Learning
por: Ruan, Feng
Publicado: (2024)
por: Ruan, Feng
Publicado: (2024)
Randomization Inference When N Equals One
por: Liang, Tengyuan, et al.
Publicado: (2023)
por: Liang, Tengyuan, et al.
Publicado: (2023)
Trajectory-Restricted Optimization Conditions and Geometry-Aware Linear Convergence
por: Chaudhry, Faris, et al.
Publicado: (2026)
por: Chaudhry, Faris, et al.
Publicado: (2026)
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality
por: Chen, Siyu, et al.
Publicado: (2024)
por: Chen, Siyu, et al.
Publicado: (2024)
Variational Transport: A Convergent Particle-BasedAlgorithm for Distributional Optimization
por: Yang, Zhuoran, et al.
Publicado: (2020)
por: Yang, Zhuoran, et al.
Publicado: (2020)
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
por: Alfano, Carlo, et al.
Publicado: (2023)
por: Alfano, Carlo, et al.
Publicado: (2023)
Decentralized Sparse Linear Regression via Gradient-Tracking: Linear Convergence and Statistical Guarantees
por: Maros, Marie, et al.
Publicado: (2022)
por: Maros, Marie, et al.
Publicado: (2022)
Convergence of flow-based generative models via proximal gradient descent in Wasserstein space
por: Cheng, Xiuyuan, et al.
Publicado: (2023)
por: Cheng, Xiuyuan, et al.
Publicado: (2023)
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise
por: Armacki, Aleksandar, et al.
Publicado: (2023)
por: Armacki, Aleksandar, et al.
Publicado: (2023)
Learning the Uncertainty Sets for Control Dynamics via Set Membership: A Non-Asymptotic Analysis
por: Li, Yingying, et al.
Publicado: (2023)
por: Li, Yingying, et al.
Publicado: (2023)
Joint Learning of Linear Dynamical Systems under Smoothness Constraints
por: Tyagi, Hemant
Publicado: (2024)
por: Tyagi, Hemant
Publicado: (2024)
Convergence of coordinate ascent variational inference for log-concave measures via optimal transport
por: Arnese, Manuel, et al.
Publicado: (2024)
por: Arnese, Manuel, et al.
Publicado: (2024)
Shifted Interpolation for Differential Privacy
por: Bok, Jinho, et al.
Publicado: (2024)
por: Bok, Jinho, et al.
Publicado: (2024)
Data-Efficient Non-Gaussian Semi-Nonparametric Density Estimation for Nonlinear Dynamical Systems
por: Liao, Aaron R., et al.
Publicado: (2026)
por: Liao, Aaron R., et al.
Publicado: (2026)
The High Line: Exact Risk and Learning Rate Curves of Stochastic Adaptive Learning Rate Algorithms
por: Collins-Woodfin, Elizabeth, et al.
Publicado: (2024)
por: Collins-Woodfin, Elizabeth, et al.
Publicado: (2024)
No-Regret Generative Modeling via Parabolic Monge-Ampère PDE
por: Deb, Nabarun, et al.
Publicado: (2025)
por: Deb, Nabarun, et al.
Publicado: (2025)
A Theory of Feature Learning in Kernel Models
por: Chen, Yunlu, et al.
Publicado: (2023)
por: Chen, Yunlu, et al.
Publicado: (2023)
Gradient Equilibrium in Online Learning: Theory and Applications
por: Angelopoulos, Anastasios N., et al.
Publicado: (2025)
por: Angelopoulos, Anastasios N., et al.
Publicado: (2025)
Bayesian Design Principles for Frequentist Sequential Learning
por: Xu, Yunbei, et al.
Publicado: (2023)
por: Xu, Yunbei, et al.
Publicado: (2023)
Learning an Optimal Assortment Policy under Observational Data
por: Han, Yuxuan, et al.
Publicado: (2025)
por: Han, Yuxuan, et al.
Publicado: (2025)
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
por: Zhang, Dake, et al.
Publicado: (2024)
por: Zhang, Dake, et al.
Publicado: (2024)
Learning and Decision-Making with Data: Optimal Formulations and Phase Transitions
por: Bennouna, Amine, et al.
Publicado: (2021)
por: Bennouna, Amine, et al.
Publicado: (2021)
Robustly Learning Monotone Generalized Linear Models via Data Augmentation
por: Zarifis, Nikos, et al.
Publicado: (2025)
por: Zarifis, Nikos, et al.
Publicado: (2025)
Convergence rate of random scan Coordinate Ascent Variational Inference under log-concavity
por: Lavenant, Hugo, et al.
Publicado: (2024)
por: Lavenant, Hugo, et al.
Publicado: (2024)
Learning linear dynamical systems under convex constraints
por: Tyagi, Hemant, et al.
Publicado: (2023)
por: Tyagi, Hemant, et al.
Publicado: (2023)
Kernel Mean Embedding Topology: Weak and Strong Forms for Stochastic Kernels and Implications for Model Learning
por: Saldi, Naci, et al.
Publicado: (2025)
por: Saldi, Naci, et al.
Publicado: (2025)
Gradient Projection onto Historical Descent Directions for Communication-Efficient Federated Learning
por: Descours, Arnaud, et al.
Publicado: (2025)
por: Descours, Arnaud, et al.
Publicado: (2025)
Is Q-Learning Minimax Optimal? A Tight Sample Complexity Analysis
por: Li, Gen, et al.
Publicado: (2021)
por: Li, Gen, et al.
Publicado: (2021)
Causal Invariance Learning via Efficient Nonconvex Optimization
por: Wang, Zhenyu, et al.
Publicado: (2024)
por: Wang, Zhenyu, et al.
Publicado: (2024)
Federated Optimization of Smooth Loss Functions
por: Jadbabaie, Ali, et al.
Publicado: (2022)
por: Jadbabaie, Ali, et al.
Publicado: (2022)
Sparse PCA With Multiple Components
por: Cory-Wright, Ryan, et al.
Publicado: (2022)
por: Cory-Wright, Ryan, et al.
Publicado: (2022)
Stochastic Optimization with Optimal Importance Sampling
por: Aolaritei, Liviu, et al.
Publicado: (2025)
por: Aolaritei, Liviu, et al.
Publicado: (2025)
Joint learning of a network of linear dynamical systems via total variation penalization
por: Donnat, Claire, et al.
Publicado: (2025)
por: Donnat, Claire, et al.
Publicado: (2025)
A review of NMF, PLSA, LBA, EMA, and LCA with a focus on the identifiability issue
por: Qi, Qianqian, et al.
Publicado: (2025)
por: Qi, Qianqian, et al.
Publicado: (2025)
High-dimensional Limit of SGD for Diagonal Linear Networks
por: Malaxechebarría, Begoña García, et al.
Publicado: (2026)
por: Malaxechebarría, Begoña García, et al.
Publicado: (2026)
Error Analysis of Triangular Optimal Transport Maps for Filtering
por: Al-Jarrah, Mohammad, et al.
Publicado: (2025)
por: Al-Jarrah, Mohammad, et al.
Publicado: (2025)
Online Inference of Constrained Optimization: Primal-Dual Optimality and Sequential Quadratic Programming
por: Gao, Yihang, et al.
Publicado: (2025)
por: Gao, Yihang, et al.
Publicado: (2025)
A Spectral Framework for Closed-Form Relative Density Estimation
por: Bach, Francis
Publicado: (2026)
por: Bach, Francis
Publicado: (2026)
Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity
por: Bravo, Mario, et al.
Publicado: (2025)
por: Bravo, Mario, et al.
Publicado: (2025)
Ejemplares similares
-
Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity
por: Liang, Tengyuan, et al.
Publicado: (2024) -
On the Uniform Convergence of Subdifferentials in Stochastic Optimization and Learning
por: Ruan, Feng
Publicado: (2024) -
Randomization Inference When N Equals One
por: Liang, Tengyuan, et al.
Publicado: (2023) -
Trajectory-Restricted Optimization Conditions and Geometry-Aware Linear Convergence
por: Chaudhry, Faris, et al.
Publicado: (2026) -
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality
por: Chen, Siyu, et al.
Publicado: (2024)