Saved in:
| Main Authors: | Holtz, Chester, Chen, Pengwen, Cloninger, Alexander, Cheng, Chung-Kuan, Mishne, Gal |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2308.00142 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Robust Graph-Based Semi-Supervised Learning via $p$-Conductances
by: Robertson, Sawyer Jack, et al.
Published: (2025)
by: Robertson, Sawyer Jack, et al.
Published: (2025)
Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
by: Zhang, Yiming, et al.
Published: (2025)
by: Zhang, Yiming, et al.
Published: (2025)
Sequential subspace methods on Stiefel manifold optimization
by: Chen, Pengwen, et al.
Published: (2024)
by: Chen, Pengwen, et al.
Published: (2024)
Robust boundary detection and density estimation using doubly stochastic scaling of the Gaussian kernel
by: Kohli, Dhruv, et al.
Published: (2024)
by: Kohli, Dhruv, et al.
Published: (2024)
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
by: Kohli, Dhruv, et al.
Published: (2025)
by: Kohli, Dhruv, et al.
Published: (2025)
Semi-Supervised Manifold Learning with Complexity Decoupled Chart Autoencoders
by: Schonsheck, Stefan C., et al.
Published: (2022)
by: Schonsheck, Stefan C., et al.
Published: (2022)
On Robustness and Generalization of ML-Based Congestion Predictors to Valid and Imperceptible Perturbations
by: Holtz, Chester, et al.
Published: (2024)
by: Holtz, Chester, et al.
Published: (2024)
Learning Cartesian Product Graphs with Laplacian Constraints
by: Shi, Changhao, et al.
Published: (2024)
by: Shi, Changhao, et al.
Published: (2024)
Graph Laplacian Learning with Exponential Family Noise
by: Shi, Changhao, et al.
Published: (2023)
by: Shi, Changhao, et al.
Published: (2023)
Learning Kronecker-Structured Graphs from Smooth Signals
by: Shi, Changhao, et al.
Published: (2025)
by: Shi, Changhao, et al.
Published: (2025)
Non-degenerate Rigid Alignment in a Patch Framework
by: Kohli, Dhruv, et al.
Published: (2023)
by: Kohli, Dhruv, et al.
Published: (2023)
Deep and shallow data science for multi-scale optical neuroscience
by: Mishne, Gal, et al.
Published: (2024)
by: Mishne, Gal, et al.
Published: (2024)
SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
by: Mudrik, Noga, et al.
Published: (2023)
by: Mudrik, Noga, et al.
Published: (2023)
The Numerical Stability of Hyperbolic Representation Learning
by: Mishne, Gal, et al.
Published: (2022)
by: Mishne, Gal, et al.
Published: (2022)
On a Generalization of Wasserstein Distance and the Beckmann Problem to Connection Graphs
by: Robertson, Sawyer, et al.
Published: (2023)
by: Robertson, Sawyer, et al.
Published: (2023)
Cluster and then Embed: A Modular Approach for Visualization
by: Coda, Elizabeth, et al.
Published: (2025)
by: Coda, Elizabeth, et al.
Published: (2025)
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights
by: Shen, Zhaiming, et al.
Published: (2025)
by: Shen, Zhaiming, et al.
Published: (2025)
Training Guarantees of Neural Network Classification Two-Sample Tests by Kernel Analysis
by: Khurana, Varun, et al.
Published: (2024)
by: Khurana, Varun, et al.
Published: (2024)
Explaining GNN Explanations with Edge Gradients
by: He, Jesse, et al.
Published: (2025)
by: He, Jesse, et al.
Published: (2025)
Elucidating Flow Matching ODE Dynamics with Respect to Data Geometries and Denoisers
by: Wan, Zhengchao, et al.
Published: (2024)
by: Wan, Zhengchao, et al.
Published: (2024)
Multi-Integration of Labels across Categories for Component Identification (MILCCI)
by: Mudrik, Noga, et al.
Published: (2026)
by: Mudrik, Noga, et al.
Published: (2026)
Interface Laplace Learning: Learnable Interface Term Helps Semi-Supervised Learning
by: Wang, Tangjun, et al.
Published: (2024)
by: Wang, Tangjun, et al.
Published: (2024)
Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
by: Lin, Ya-Wei Eileen, et al.
Published: (2025)
by: Lin, Ya-Wei Eileen, et al.
Published: (2025)
Riemannian Optimization for LoRA on the Stiefel Manifold
by: Park, Juneyoung, et al.
Published: (2025)
by: Park, Juneyoung, et al.
Published: (2025)
StelLA: Subspace Learning in Low-rank Adaptation using Stiefel Manifold
by: Li, Zhizhong, et al.
Published: (2025)
by: Li, Zhizhong, et al.
Published: (2025)
Unsupervised Feature Selection Through Group Discovery
by: Lifshitz, Shira, et al.
Published: (2025)
by: Lifshitz, Shira, et al.
Published: (2025)
Comparing Graph Transformers via Positional Encodings
by: Black, Mitchell, et al.
Published: (2024)
by: Black, Mitchell, et al.
Published: (2024)
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
by: Chen, Jun, et al.
Published: (2023)
by: Chen, Jun, et al.
Published: (2023)
ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis
by: Zhang, Zhanqi, et al.
Published: (2026)
by: Zhang, Zhanqi, et al.
Published: (2026)
Graph Semi-Supervised Learning for Point Classification on Data Manifolds
by: Netto, Caio F. Deberaldini, et al.
Published: (2025)
by: Netto, Caio F. Deberaldini, et al.
Published: (2025)
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
by: Lin, Ya-Wei Eileen, et al.
Published: (2024)
by: Lin, Ya-Wei Eileen, et al.
Published: (2024)
Point Cloud Classification via Deep Set Linearized Optimal Transport
by: Mahan, Scott, et al.
Published: (2024)
by: Mahan, Scott, et al.
Published: (2024)
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
by: Xie, Jiancheng, et al.
Published: (2024)
by: Xie, Jiancheng, et al.
Published: (2024)
GeoEdit: Local Frames for Fast, Training-Free On-Manifold Editing in Diffusion Models
by: Zhang, Yiming, et al.
Published: (2026)
by: Zhang, Yiming, et al.
Published: (2026)
In-Context Semi-Supervised Learning
by: Fan, Jiashuo, et al.
Published: (2025)
by: Fan, Jiashuo, et al.
Published: (2025)
FORML: A Riemannian Hessian-free Method for Meta-learning on Stiefel Manifolds
by: Tabealhojeh, Hadi, et al.
Published: (2024)
by: Tabealhojeh, Hadi, et al.
Published: (2024)
Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks
by: Lee, Hyungu, et al.
Published: (2025)
by: Lee, Hyungu, et al.
Published: (2025)
Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds
by: Linwu, Jun, et al.
Published: (2025)
by: Linwu, Jun, et al.
Published: (2025)
Calibrated Adaptation: Bayesian Stiefel Manifold Priors for Reliable Parameter-Efficient Fine-Tuning
by: Shihab, Ibne Farabi, et al.
Published: (2026)
by: Shihab, Ibne Farabi, et al.
Published: (2026)
Optimization without Retraction on the Random Generalized Stiefel Manifold
by: Vary, Simon, et al.
Published: (2024)
by: Vary, Simon, et al.
Published: (2024)
Similar Items
-
Robust Graph-Based Semi-Supervised Learning via $p$-Conductances
by: Robertson, Sawyer Jack, et al.
Published: (2025) -
Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
by: Zhang, Yiming, et al.
Published: (2025) -
Sequential subspace methods on Stiefel manifold optimization
by: Chen, Pengwen, et al.
Published: (2024) -
Robust boundary detection and density estimation using doubly stochastic scaling of the Gaussian kernel
by: Kohli, Dhruv, et al.
Published: (2024) -
Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
by: Kohli, Dhruv, et al.
Published: (2025)