Adaptive Linear Embedding for Nonstationary High-Dimensional Optimization
Fuente:
arXiv
Guardado en:
| Autores principales: | Wen, Yuejiang, Franzon, Paul D. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Can an Actor-Critic Optimization Framework Improve Analog Design Optimization?
por: Dutta, Sounak, et al.
Publicado: (2026)
por: Dutta, Sounak, et al.
Publicado: (2026)
Can Low-Rank Knowledge Distillation in LLMs be Useful for Microelectronic Reasoning?
por: Rouf, Nirjhor, et al.
Publicado: (2024)
por: Rouf, Nirjhor, et al.
Publicado: (2024)
Nonstationary Reinforcement Learning with Linear Function Approximation
por: Zhou, Huozhi, et al.
Publicado: (2020)
por: Zhou, Huozhi, et al.
Publicado: (2020)
Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent
por: Lee, Joongkyu, et al.
Publicado: (2026)
por: Lee, Joongkyu, et al.
Publicado: (2026)
Repetitions are not all alike: distinct mechanisms sustain repetition in language models
por: Mahaut, Matéo, et al.
Publicado: (2025)
por: Mahaut, Matéo, et al.
Publicado: (2025)
High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings
por: Priem, Rémy, et al.
Publicado: (2025)
por: Priem, Rémy, et al.
Publicado: (2025)
An Adaptive Dropout Approach for High-Dimensional Bayesian Optimization
por: Huang, Jundi, et al.
Publicado: (2025)
por: Huang, Jundi, et al.
Publicado: (2025)
Adaptive Locally Linear Embedding
por: Goli, Ali, et al.
Publicado: (2025)
por: Goli, Ali, et al.
Publicado: (2025)
Explore-then-Commit for Nonstationary Linear Bandits with Latent Dynamics
por: Choi, Sunmook, et al.
Publicado: (2025)
por: Choi, Sunmook, et al.
Publicado: (2025)
Enhanced High-Dimensional Data Visualization through Adaptive Multi-Scale Manifold Embedding
por: Ni, Tianhao, et al.
Publicado: (2025)
por: Ni, Tianhao, et al.
Publicado: (2025)
On the Provable Suboptimality of Momentum SGD in Nonstationary Stochastic Optimization
por: Sahu, Sharan, et al.
Publicado: (2026)
por: Sahu, Sharan, et al.
Publicado: (2026)
Adapt or Forget: Provable Tradeoffs Between Adam and SGD in Nonstationary Optimization
por: Sahu, Sharan, et al.
Publicado: (2026)
por: Sahu, Sharan, et al.
Publicado: (2026)
Orthogonal Subspace Clustering: Enhancing High-Dimensional Data Analysis through Adaptive Dimensionality Reduction and Efficient Clustering
por: Wen, Qing-Yuan, et al.
Publicado: (2026)
por: Wen, Qing-Yuan, et al.
Publicado: (2026)
Identifying Nonstationary Causal Structures with High-Order Markov Switching Models
por: Balsells-Rodas, Carles, et al.
Publicado: (2024)
por: Balsells-Rodas, Carles, et al.
Publicado: (2024)
Quick-Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms
por: Everett, Derek, et al.
Publicado: (2025)
por: Everett, Derek, et al.
Publicado: (2025)
A Single-Sample Polylogarithmic Regret Bound for Nonstationary Online Linear Programming
por: Xu, Haoran, et al.
Publicado: (2026)
por: Xu, Haoran, et al.
Publicado: (2026)
Nonstationary Sparse Spectral Permanental Process
por: Sun, Zicheng, et al.
Publicado: (2024)
por: Sun, Zicheng, et al.
Publicado: (2024)
Linear Dimensionality Reduction for Word Embeddings in Tabular Data Classification
por: Ressel, Liam, et al.
Publicado: (2025)
por: Ressel, Liam, et al.
Publicado: (2025)
The emergence of numerical representations in communicating artificial agents
por: Mihai, Daniela, et al.
Publicado: (2026)
por: Mihai, Daniela, et al.
Publicado: (2026)
Neighbor Embedding for High-Dimensional Sparse Poisson Data
por: Mudrik, Noga, et al.
Publicado: (2026)
por: Mudrik, Noga, et al.
Publicado: (2026)
DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces
por: Valentin, Romeo, et al.
Publicado: (2025)
por: Valentin, Romeo, et al.
Publicado: (2025)
Describing Nonstationary Data Streams in Frequency Domain
por: Komorniczak, Joanna
Publicado: (2025)
por: Komorniczak, Joanna
Publicado: (2025)
Regular Fourier Features for Nonstationary Gaussian Processes
por: Jawaid, Arsalan, et al.
Publicado: (2026)
por: Jawaid, Arsalan, et al.
Publicado: (2026)
Co-Supervised Learning: Improving Weak-to-Strong Generalization with Hierarchical Mixture of Experts
por: Liu, Yuejiang, et al.
Publicado: (2024)
por: Liu, Yuejiang, et al.
Publicado: (2024)
High-Dimensional Private Linear Regression with Optimal Rates
por: Bombari, Simone, et al.
Publicado: (2025)
por: Bombari, Simone, et al.
Publicado: (2025)
Fairness Constraints in High-Dimensional Generalized Linear Models
por: Lin, Yixiao, et al.
Publicado: (2026)
por: Lin, Yixiao, et al.
Publicado: (2026)
Scaling Laws of Global Weather Models
por: Yu, Yuejiang, et al.
Publicado: (2026)
por: Yu, Yuejiang, et al.
Publicado: (2026)
Learning Low-Dimensional Embeddings for Black-Box Optimization
por: Busetto, Riccardo, et al.
Publicado: (2025)
por: Busetto, Riccardo, et al.
Publicado: (2025)
Understanding High-Dimensional Bayesian Optimization
por: Papenmeier, Leonard, et al.
Publicado: (2025)
por: Papenmeier, Leonard, et al.
Publicado: (2025)
A State-Space Approach to Nonstationary Discriminant Analysis
por: Xie, Shuilian, et al.
Publicado: (2025)
por: Xie, Shuilian, et al.
Publicado: (2025)
Online Conformal Model Selection for Nonstationary Time Series
por: Li, Shibo, et al.
Publicado: (2025)
por: Li, Shibo, et al.
Publicado: (2025)
Causal Temporal Representation Learning with Nonstationary Sparse Transition
por: Song, Xiangchen, et al.
Publicado: (2024)
por: Song, Xiangchen, et al.
Publicado: (2024)
Causal Inference from Slowly Varying Nonstationary Processes
por: Du, Kang, et al.
Publicado: (2024)
por: Du, Kang, et al.
Publicado: (2024)
Unified Transfer Learning Models in High-Dimensional Linear Regression
por: Liu, Shuo Shuo
Publicado: (2023)
por: Liu, Shuo Shuo
Publicado: (2023)
Lecture Notes on High Dimensional Linear Regression
por: Quaini, Alberto
Publicado: (2024)
por: Quaini, Alberto
Publicado: (2024)
Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
por: Chen, Changan, et al.
Publicado: (2018)
por: Chen, Changan, et al.
Publicado: (2018)
SEEK: Self-adaptive Explainable Kernel For Nonstationary Gaussian Processes
por: Negarandeh, Nima, et al.
Publicado: (2025)
por: Negarandeh, Nima, et al.
Publicado: (2025)
Learning to Query History: Nonstationary Classification via Learned Retrieval
por: Gammell, Jimmy, et al.
Publicado: (2026)
por: Gammell, Jimmy, et al.
Publicado: (2026)
Nonstationary Time Series Forecasting via Unknown Distribution Adaptation
por: Li, Zijian, et al.
Publicado: (2024)
por: Li, Zijian, et al.
Publicado: (2024)
Interpretation of High-Dimensional Regression Coefficients by Comparison with Linearized Compressing Features
por: Schaeffer, Joachim, et al.
Publicado: (2024)
por: Schaeffer, Joachim, et al.
Publicado: (2024)
Ejemplares similares
-
Can an Actor-Critic Optimization Framework Improve Analog Design Optimization?
por: Dutta, Sounak, et al.
Publicado: (2026) -
Can Low-Rank Knowledge Distillation in LLMs be Useful for Microelectronic Reasoning?
por: Rouf, Nirjhor, et al.
Publicado: (2024) -
Nonstationary Reinforcement Learning with Linear Function Approximation
por: Zhou, Huozhi, et al.
Publicado: (2020) -
Nonstationary Generalized Linear Bandits with Discounted Online Mirror Descent
por: Lee, Joongkyu, et al.
Publicado: (2026) -
Repetitions are not all alike: distinct mechanisms sustain repetition in language models
por: Mahaut, Matéo, et al.
Publicado: (2025)