Saved in:
| Main Authors: | Zhang, Hongzhe, Auddy, Arnab, Lee, Hongzhe |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.02411 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Multicalibration Boosting: Theory, Convergence, and Transferability
by: Ye, Hanxuan, et al.
Published: (2026)
by: Ye, Hanxuan, et al.
Published: (2026)
Transfer Learning for Contextual Multi-armed Bandits
by: Cai, Changxiao, et al.
Published: (2022)
by: Cai, Changxiao, et al.
Published: (2022)
Test of partial effects for Frechet regression on Bures-Wasserstein manifolds
by: Xu, Haoshu, et al.
Published: (2025)
by: Xu, Haoshu, et al.
Published: (2025)
Wasserstein F-tests for Fréchet regression on Bures-Wasserstein manifolds
by: Xu, Haoshu, et al.
Published: (2024)
by: Xu, Haoshu, et al.
Published: (2024)
Learning covariate importance for matching in policy-relevant observational research
by: Zhang, Hongzhe, et al.
Published: (2024)
by: Zhang, Hongzhe, et al.
Published: (2024)
On Spectral Learning for Odeco Tensors: Perturbation, Initialization, and Algorithms
by: Auddy, Arnab, et al.
Published: (2025)
by: Auddy, Arnab, et al.
Published: (2025)
Minimax And Adaptive Transfer Learning for Nonparametric Classification under Distributed Differential Privacy Constraints
by: Auddy, Arnab, et al.
Published: (2024)
by: Auddy, Arnab, et al.
Published: (2024)
Tensor Methods in High Dimensional Data Analysis: Opportunities and Challenges
by: Auddy, Arnab, et al.
Published: (2024)
by: Auddy, Arnab, et al.
Published: (2024)
Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning
by: Auddy, Arnab, et al.
Published: (2026)
by: Auddy, Arnab, et al.
Published: (2026)
Who Gets Credit or Blame? Attributing Accountability in Modern AI Systems
by: Zhang, Shichang, et al.
Published: (2025)
by: Zhang, Shichang, et al.
Published: (2025)
Theoretical Analysis of Leave-one-out Cross Validation for Non-differentiable Penalties under High-dimensional Settings
by: Zou, Haolin, et al.
Published: (2024)
by: Zou, Haolin, et al.
Published: (2024)
Recent advances in deep learning and language models for studying the microbiome
by: Yan, Binghao, et al.
Published: (2024)
by: Yan, Binghao, et al.
Published: (2024)
ChemCLIP: Bridging Organic and Inorganic Anticancer Compounds Through Contrastive Learning
by: Koohi-Moghadam, Mohamad, et al.
Published: (2026)
by: Koohi-Moghadam, Mohamad, et al.
Published: (2026)
Gaussian Certified Unlearning in High Dimensions: A Hypothesis Testing Approach
by: Pandey, Aaradhya, et al.
Published: (2025)
by: Pandey, Aaradhya, et al.
Published: (2025)
Causal Network Discovery from Interventional Count Data with Latent Linear DAGs
by: Zhang, Yijiao, et al.
Published: (2026)
by: Zhang, Yijiao, et al.
Published: (2026)
Spectrally-Corrected and Regularized Linear Discriminant Analysis for Spiked Covariance Model
by: Li, Hua, et al.
Published: (2022)
by: Li, Hua, et al.
Published: (2022)
DOSE3 : Diffusion-based Out-of-distribution detection on SE(3) trajectories
by: Cheng, Hongzhe, et al.
Published: (2025)
by: Cheng, Hongzhe, et al.
Published: (2025)
Certified Data Removal Under High-dimensional Settings
by: Zou, Haolin, et al.
Published: (2025)
by: Zou, Haolin, et al.
Published: (2025)
Newfluence: Boosting Model interpretability and Understanding in High Dimensions
by: Zou, Haolin, et al.
Published: (2025)
by: Zou, Haolin, et al.
Published: (2025)
Structural Effect and Spectral Enhancement of High-Dimensional Regularized Linear Discriminant Analysis
by: Zhang, Yonghan, et al.
Published: (2025)
by: Zhang, Yonghan, et al.
Published: (2025)
How Digital Asset Treasury Companies Can Survive Bear Markets: The Case of the Strategy and Bitcoin
by: Wen, Hongzhe
Published: (2025)
by: Wen, Hongzhe
Published: (2025)
Regularized Linear Discriminant Analysis Using a Nonlinear Covariance Matrix Estimator
by: Mahadi, Maaz, et al.
Published: (2024)
by: Mahadi, Maaz, et al.
Published: (2024)
Simplex Deep Linear Discriminant Analysis
by: Tezekbayev, Maxat, et al.
Published: (2026)
by: Tezekbayev, Maxat, et al.
Published: (2026)
Deep Linear Discriminant Analysis Revisited
by: Tezekbayev, Maxat, et al.
Published: (2026)
by: Tezekbayev, Maxat, et al.
Published: (2026)
How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence
by: Du, Hongzhe, et al.
Published: (2025)
by: Du, Hongzhe, et al.
Published: (2025)
Linear Discriminant Analysis with Gradient Optimization
by: Shen, Cencheng, et al.
Published: (2025)
by: Shen, Cencheng, et al.
Published: (2025)
H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation
by: Bi, Hongzhe, et al.
Published: (2025)
by: Bi, Hongzhe, et al.
Published: (2025)
Implicit Bias in Deep Linear Discriminant Analysis
by: Li, Jiawen
Published: (2026)
by: Li, Jiawen
Published: (2026)
Simultaneous Estimation of Many Sparse Networks via Hierarchical Poisson Log-Normal Model
by: Ge, Changhao, et al.
Published: (2024)
by: Ge, Changhao, et al.
Published: (2024)
Effect of Optimizer, Initializer, and Architecture of Hypernetworks on Continual Learning from Demonstration
by: Auddy, Sayantan, et al.
Published: (2023)
by: Auddy, Sayantan, et al.
Published: (2023)
Linear Discriminant Analysis with the Randomized Kaczmarz Method
by: Chi, Jocelyn T., et al.
Published: (2022)
by: Chi, Jocelyn T., et al.
Published: (2022)
Regularized Q-learning
by: Lim, Han-Dong, et al.
Published: (2022)
by: Lim, Han-Dong, et al.
Published: (2022)
Trajectory First: A Curriculum for Discovering Diverse Policies
by: Braun, Cornelius V., et al.
Published: (2025)
by: Braun, Cornelius V., et al.
Published: (2025)
A Robust Local Fréchet Regression Using Unbalanced Neural Optimal Transport with Applications to Dynamic Single-cell Genomics Data
by: Yan, Binghao, et al.
Published: (2025)
by: Yan, Binghao, et al.
Published: (2025)
Understanding the UV/Optical Variability of AGNs through Quasi-Periodic Large-scale Magnetic Dynamos
by: Zhou, Hongzhe, et al.
Published: (2024)
by: Zhou, Hongzhe, et al.
Published: (2024)
Stochastic Motion Planning as Gaussian Variational Inference: Theory and Algorithms
by: Yu, Hongzhe, et al.
Published: (2023)
by: Yu, Hongzhe, et al.
Published: (2023)
Confounder-robust causal discovery and inference in Perturb-seq using proxy and instrumental variables
by: Park, Kwangmoon, et al.
Published: (2026)
by: Park, Kwangmoon, et al.
Published: (2026)
Correlation times of velocity and kinetic helicity fluctuations in nonhelical hydrodynamic turbulence
by: Zhou, Hongzhe, et al.
Published: (2024)
by: Zhou, Hongzhe, et al.
Published: (2024)
Multicalibration for Modeling Censored Survival Data with Universal Adaptability
by: Ye, Hanxuan, et al.
Published: (2024)
by: Ye, Hanxuan, et al.
Published: (2024)
Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization
by: Wu, Jingfeng, et al.
Published: (2025)
by: Wu, Jingfeng, et al.
Published: (2025)
Similar Items
-
Multicalibration Boosting: Theory, Convergence, and Transferability
by: Ye, Hanxuan, et al.
Published: (2026) -
Transfer Learning for Contextual Multi-armed Bandits
by: Cai, Changxiao, et al.
Published: (2022) -
Test of partial effects for Frechet regression on Bures-Wasserstein manifolds
by: Xu, Haoshu, et al.
Published: (2025) -
Wasserstein F-tests for Fréchet regression on Bures-Wasserstein manifolds
by: Xu, Haoshu, et al.
Published: (2024) -
Learning covariate importance for matching in policy-relevant observational research
by: Zhang, Hongzhe, et al.
Published: (2024)