22 citations · 30 across the 2 of their papers we have counts for
7 papers
Hyperparameter Tuning is All You Need for LISTA
Xiaohan Chen, Jialin Liu, Zhangyang Wang +1
Learned Iterative Shrinkage-Thresholding Algorithm (LISTA) introduces the concept of unrolling an iterative algorithm and training it like a neural network. It has had great succes…
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen, Xiaohan Chen, Wuyang Chen +4
Learning to optimize (L2O) is an emerging approach that leverages machine learning to develop optimization methods, aiming at reducing the laborious iterations of hand engineering.…
Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval
Lee Xiong, Chenyan Xiong, Ye Li +5
Conducting text retrieval in a dense learned representation space has many intriguing advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires…
Learning Convolutional Sparse Coding on Complex Domain for Interferometric Phase Restoration
Jian Kang, Danfeng Hong, Jialin Liu +3
Interferometric phase restoration has been investigated for decades and most of the state-of-the-art methods have achieved promising performances for InSAR phase restoration. These…
Task Augmentation by Rotating for Meta-Learning
Jialin Liu, Fei Chao, Chih-Min Lin
Data augmentation is one of the most effective approaches for improving the accuracy of modern machine learning models, and it is also indispensable to train a deep model for meta-…
Multilevel Optimal Transport: a Fast Approximation of Wasserstein-1 distances
Jialin Liu, Wotao Yin, Wuchen Li +1
We propose a fast algorithm for the calculation of the Wasserstein-1 distance, which is a particular type of optimal transport distance with homogeneous of degree one transport cos…