Summary of A Survey on Contribution Evaluation in Vertical Federated Learning, by Yue Cui et al.
A Survey on Contribution Evaluation in Vertical Federated Learningby Yue Cui, Chung-ju Huang, Yuzhu Zhang,…
Summary of Triadic-ocd: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence, by Yancheng Huang et al.
Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergenceby Yancheng Huang, Kai Yang,…
Summary of Enhancing Social Media Post Popularity Prediction with Visual Content, by Dahyun Jeong et al.
Enhancing Social Media Post Popularity Prediction with Visual Contentby Dahyun Jeong, Hyelim Son, Yunjin Choi,…
Summary of Histogram-based Federated Xgboost Using Minimal Variance Sampling For Federated Tabular Data, by William Lindskog et al.
Histogram-Based Federated XGBoost using Minimal Variance Sampling for Federated Tabular Databy William Lindskog, Christian Prehofer,…
Summary of A Federated Learning Benchmark on Tabular Data: Comparing Tree-based Models and Neural Networks, by William Lindskog and Christian Prehofer
A Federated Learning Benchmark on Tabular Data: Comparing Tree-Based Models and Neural Networksby William Lindskog,…
Summary of A Mutual Information Perspective on Federated Contrastive Learning, by Christos Louizos et al.
A Mutual Information Perspective on Federated Contrastive Learningby Christos Louizos, Matthias Reisser, Denis KorzhenkovFirst submitted…
Summary of Multi-level Projection with Exponential Parallel Speedup; Application to Sparse Auto-encoders Neural Networks, by Guillaume Perez and Michel Barlaud
Multi-level projection with exponential parallel speedup; Application to sparse auto-encoders neural networksby Guillaume Perez, Michel…
Summary of Forecasting Ferry Passenger Flow Using Long-short Term Memory Neural Networks, by Daniel Fesalbon
Forecasting Ferry Passenger Flow Using Long-Short Term Memory Neural Networksby Daniel FesalbonFirst submitted to arxiv…
Summary of A Comparative Study Of Conformal Prediction Methods For Valid Uncertainty Quantification in Machine Learning, by Nicolas Dewolf
A comparative study of conformal prediction methods for valid uncertainty quantification in machine learningby Nicolas…
Summary of An Information Theoretic Perspective on Conformal Prediction, by Alvaro H.c. Correia et al.
An Information Theoretic Perspective on Conformal Predictionby Alvaro H.C. Correia, Fabio Valerio Massoli, Christos Louizos,…