Sparse Solution Technique

Sparse solution techniques aim to find efficient and accurate solutions by utilizing only a minimal subset of available data or model parameters, thereby improving computational efficiency and reducing resource demands. Current research focuses on applying these techniques to diverse fields, including neural network training (using algorithms like Iterative Hard Thresholding), matrix factorization for fMRI data analysis, and image processing (e.g., for medical image classification and bird's-eye view representations in autonomous driving). This approach is proving valuable across various domains by enabling faster processing, improved model interpretability, and enhanced performance in resource-constrained environments, particularly in large-scale applications like deep learning.

Papers

July 11, 2024

Local Clustering for Lung Cancer Image Classification via Sparse Solution Technique
Jackson Hamel, Ming-Jun Lai, Zhaiming Shen, Ye Tian
Spectral Clustering Graph Clustering Lung Nodule Malignancy Local Clustering Sparse Solution Technique

April 29, 2024

Learning a Sparse Neural Network using IHT
Saeed Damadi, Soroush Zolfaghari, Mahdi Rezaie, Jinglai Shen
Gradient Descent Sparse Neural Network Sparse Optimization Hard Thresholding Sparse Solution Technique

December 14, 2023

Performance evaluation of matrix factorization for fMRI data
Yusuke Endo, Koujin Takeda
Many Sparse Matrix Factorization Functional Magnetic Resonance Imaging Performance Evaluation Sparse Principal Component Analysis Sparse Solution Technique

December 1, 2023

PointBeV: A Sparse Approach to BeV Predictions
Loick Chambon, Eloi Zablocki, Mickael Chen, Florent Bartoccioni, Patrick Perez, Matthieu Cord
Bird'S Eye View Sparse Feature Sparse Solution Technique

March 3, 2023

Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang
Sparsity Increase Sparse Neural Network United State Efficient Sparse Sparse Solution Technique

September 22, 2022

EPIC TTS Models: Empirical Pruning Investigations Characterizing Text-To-Speech Models
Perry Lam, Huayun Zhang, Nancy F. Chen, Berrak Sisman
Many Sparse Neural Model Text to Speech Model Sparse Solution Technique

January 5, 2022

Deep Learning-Based Sparse Whole-Slide Image Analysis for the Diagnosis of Gastric Intestinal Metaplasia
Jon Braatz, Pranav Rajpurkar, Stephanie Zhang, Andrew Y. Ng, Jeanne Shen
Medical Diagnosis Whole Slide Image Morphological Variation Gastric Cancer Sparse Solution Technique