Summary of Convolutional Neural Network Compression Via Dynamic Parameter Rank Pruning, by Manish Sharma et al.
Convolutional Neural Network Compression via Dynamic Parameter Rank Pruningby Manish Sharma, Jamison Heard, Eli Saber,…
Summary of Semi-supervised Semantic Segmentation Using Redesigned Self-training For White Blood Cells, by Vinh Quoc Luu et al.
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cellsby Vinh Quoc Luu, Duy Khanh…
Summary of R-bi: Regularized Batched Inputs Enhance Incremental Decoding Framework For Low-latency Simultaneous Speech Translation, by Jiaxin Guo et al.
R-BI: Regularized Batched Inputs enhance Incremental Decoding Framework for Low-Latency Simultaneous Speech Translationby Jiaxin Guo,…
Summary of Treatment Effect Estimation For Graph-structured Targets, by Shonosuke Harada et al.
Treatment Effect Estimation for Graph-Structured Targetsby Shonosuke Harada, Ryosuke Yoneda, Hisashi KashimaFirst submitted to arxiv…
Summary of Distributionally Robust Optimization Via Iterative Algorithms in Continuous Probability Spaces, by Linglingzhi Zhu et al.
Distributionally Robust Optimization via Iterative Algorithms in Continuous Probability Spacesby Linglingzhi Zhu, Yao XieFirst submitted…
Summary of Kryptonite-n: Machine Learning Strikes Back, by Albus Li et al.
Kryptonite-N: Machine Learning Strikes Backby Albus Li, Nathan Bailey, Will Sumerfield, Kira KimFirst submitted to…
Summary of Accurate Coresets For Latent Variable Models and Regularized Regression, by Sanskar Ranjan and Supratim Shit
Accurate Coresets for Latent Variable Models and Regularized Regressionby Sanskar Ranjan, Supratim ShitFirst submitted to…
Summary of Neighbor Does Matter: Density-aware Contrastive Learning For Medical Semi-supervised Segmentation, by Feilong Tang et al.
Neighbor Does Matter: Density-Aware Contrastive Learning for Medical Semi-supervised Segmentationby Feilong Tang, Zhongxing Xu, Ming…
Summary of Standard-deviation-inspired Regularization For Improving Adversarial Robustness, by Olukorede Fakorede et al.
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustnessby Olukorede Fakorede, Modeste Atsague, Jin TianFirst submitted to arxiv…
Summary of Pearsan: a Machine Learning Method For Inverse Design Using Pearson Correlated Surrogate Annealing, by Michael Bezick et al.
PearSAN: A Machine Learning Method for Inverse Design using Pearson Correlated Surrogate Annealingby Michael Bezick,…