Poster "dimensionality reduction" Papers
14 papers found
Conference
A Flag Decomposition for Hierarchical Datasets
Nathan Mankovich, Ignacio Santamaria, Gustau Camps-Valls et al.
CVPR 2025arXiv:2502.07782
3
citations
A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann et al.
ICLR 2025arXiv:2504.16929
13
citations
AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing
Sam Bright-Thonney, Christina Reissel, Gaia Grosso et al.
NEURIPS 2025arXiv:2510.21935
2
citations
Bayesian Regularization of Latent Representation
Chukwudi Paul Obite, Zhi Chang, Keyan Wu et al.
ICLR 2025
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang
ICLR 2025arXiv:2502.19865
Efficient Sparse PCA via Block-Diagonalization
Alberto Del Pia, Dekun Zhou, Yinglun Zhu
ICLR 2025arXiv:2410.14092
2
citations
EigenGS Representation: From Eigenspace to Gaussian Image Space
LO-WEI TAI, Ching-En Ching En, Li et al.
CVPR 2025arXiv:2503.07446
3
citations
Probabilistic Geometric Principal Component Analysis with application to neural data
Han-Lin Hsieh, Maryam Shanechi
ICLR 2025arXiv:2509.18469
3
citations
Understanding Contrastive Learning via Gaussian Mixture Models
Parikshit Bansal, Ali Kavis, Sujay Sanghavi
NEURIPS 2025
4
citations
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
Jing Xiong, Zixuan Li, Chuanyang Zheng et al.
ICLR 2024arXiv:2310.02954
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
ICML 2024arXiv:2312.03656
20
citations
Preventing Model Collapse in Gaussian Process Latent Variable Models
Ying Li, Zhidi Lin, Feng Yin et al.
ICML 2024arXiv:2404.01697
4
citations
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen et al.
ICML 2024arXiv:2302.06165
3
citations
VLAD-BuFF: Burst-aware Fast Feature Aggregation for Visual Place Recognition
Ahmad Khaliq, Ming Xu, Stephen Hausler et al.
ECCV 2024arXiv:2409.19293
6
citations