"dimensionality reduction" Papers
17 papers found
Conference
A Flag Decomposition for Hierarchical Datasets
Nathan Mankovich, Ignacio Santamaria, Gustau Camps-Valls et al.
A Unifying Framework for Representation Learning
Shaden Alshammari, John Hershey, Axel Feldmann et al.
AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing
Sam Bright-Thonney, Christina Reissel, Gaia Grosso et al.
Bayesian Regularization of Latent Representation
Chukwudi Paul Obite, Zhi Chang, Keyan Wu et al.
Beyond Worst-Case Dimensionality Reduction for Sparse Vectors
Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang
Efficient Sparse PCA via Block-Diagonalization
Alberto Del Pia, Dekun Zhou, Yinglun Zhu
EigenGS Representation: From Eigenspace to Gaussian Image Space
LO-WEI TAI, Ching-En Ching En, Li et al.
Factor Augmented Tensor-on-Tensor Neural Networks
Guanhao Zhou, Yuefeng Han, Xiufan Yu
Federated t-SNE and UMAP for Distributed Data Visualization
Dong Qiao, Xinxian Ma, Jicong Fan
High-dimensional neuronal activity from low-dimensional latent dynamics: a solvable model
Valentin Schmutz, Ali Haydaroğlu, Shuqi Wang et al.
Probabilistic Geometric Principal Component Analysis with application to neural data
Han-Lin Hsieh, Maryam Shanechi
Understanding Contrastive Learning via Gaussian Mixture Models
Parikshit Bansal, Ali Kavis, Sujay Sanghavi
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
Jing Xiong, Zixuan Li, Chuanyang Zheng et al.
Interpretability Illusions in the Generalization of Simplified Models
Dan Friedman, Andrew Lampinen, Lucas Dixon et al.
Preventing Model Collapse in Gaussian Process Latent Variable Models
Ying Li, Zhidi Lin, Feng Yin et al.
Sparse Dimensionality Reduction Revisited
Mikael Møller Høgsgaard, Lior Kamma, Kasper Green Larsen et al.
VLAD-BuFF: Burst-aware Fast Feature Aggregation for Visual Place Recognition
Ahmad Khaliq, Ming Xu, Stephen Hausler et al.