Summary of Procedural Fairness in Machine Learning, by Ziming Wang et al.
Procedural Fairness in Machine Learningby Ziming Wang, Changwu Huang, Xin YaoFirst submitted to arxiv on:…
Summary of Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policies, by Shlomi Weitzman and Sivan Sabato
Adaptive Combinatorial Maximization: Beyond Approximate Greedy Policiesby Shlomi Weitzman, Sivan SabatoFirst submitted to arxiv on:…
Summary of Joint-task Regularization For Partially Labeled Multi-task Learning, by Kento Nishi et al.
Joint-Task Regularization for Partially Labeled Multi-Task Learningby Kento Nishi, Junsik Kim, Wanhua Li, Hanspeter PfisterFirst…
Summary of Incentives in Private Collaborative Machine Learning, by Rachael Hwee Ling Sim et al.
Incentives in Private Collaborative Machine Learningby Rachael Hwee Ling Sim, Yehong Zhang, Trong Nghia Hoang,…
Summary of Hessian-free Online Certified Unlearning, by Xinbao Qiao et al.
Hessian-Free Online Certified Unlearningby Xinbao Qiao, Meng Zhang, Ming Tang, Ermin WeiFirst submitted to arxiv…
Summary of Preventing Model Collapse in Gaussian Process Latent Variable Models, by Ying Li et al.
Preventing Model Collapse in Gaussian Process Latent Variable Modelsby Ying Li, Zhidi Lin, Feng Yin,…
Summary of Global Mapping Of Exposure and Physical Vulnerability Dynamics in Least Developed Countries Using Remote Sensing and Machine Learning, by Joshua Dimasaka et al.
Global Mapping of Exposure and Physical Vulnerability Dynamics in Least Developed Countries using Remote Sensing…
Summary of When Does Subagging Work?, by Christos Revelas et al.
When does Subagging Work?by Christos Revelas, Otilia Boldea, Bas J.M. WerkerFirst submitted to arxiv on:…
Summary of Fair Mp-boost: Fair and Interpretable Minipatch Boosting, by Camille Olivia Little and Genevera I. Allen
Fair MP-BOOST: Fair and Interpretable Minipatch Boostingby Camille Olivia Little, Genevera I. AllenFirst submitted to…
Summary of Fairm: Learning Invariant Representations For Algorithmic Fairness and Domain Generalization with Minimax Optimality, by Sai Li and Linjun Zhang
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimalityby Sai Li,…