Summary of Confidence-aware Multi-field Model Calibration, by Yuang Zhao et al.
Confidence-Aware Multi-Field Model Calibrationby Yuang Zhao, Chuhan Wu, Qinglin Jia, Hong Zhu, Jia Yan, Libin…
Summary of Enhanced Bayesian Optimization Via Preferential Modeling Of Abstract Properties, by Arun Kumar a V et al.
Enhanced Bayesian Optimization via Preferential Modeling of Abstract Propertiesby Arun Kumar A V, Alistair Shilton,…
Summary of Sora: a Review on Background, Technology, Limitations, and Opportunities Of Large Vision Models, by Yixin Liu et al.
Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Modelsby Yixin Liu,…
Summary of Orthogonal Gradient Boosting For Simpler Additive Rule Ensembles, by Fan Yang et al.
Orthogonal Gradient Boosting for Simpler Additive Rule Ensemblesby Fan Yang, Pierre Le Bodic, Michael Kamp,…
Summary of The Cost Of Parallelizing Boosting, by Xin Lyu et al.
The Cost of Parallelizing Boostingby Xin Lyu, Hongxun Wu, Junzhao YangFirst submitted to arxiv on:…
Summary of Enhancing One-shot Federated Learning Through Data and Ensemble Co-boosting, by Rong Dai et al.
Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boostingby Rong Dai, Yonggang Zhang, Ang Li,…
Summary of Boosting Gets Full Attention For Relational Learning, by Mathieu Guillame-bert and Richard Nock
Boosting gets full Attention for Relational Learningby Mathieu Guillame-Bert, Richard NockFirst submitted to arxiv on:…
Summary of Fast: An Optimization Framework For Fast Additive Segmentation in Transparent Ml, by Brian Liu and Rahul Mazumder
FAST: An Optimization Framework for Fast Additive Segmentation in Transparent MLby Brian Liu, Rahul MazumderFirst…
Summary of Boosting Of Thoughts: Trial-and-error Problem Solving with Large Language Models, by Sijia Chen et al.
Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Modelsby Sijia Chen, Baochun Li, Di…
Summary of Multi-word Tokenization For Sequence Compression, by Leonidas Gee et al.
Multi-word Tokenization for Sequence Compressionby Leonidas Gee, Leonardo Rigutini, Marco Ernandes, Andrea ZugariniFirst submitted to…