Summary of Predicting the Performance Of Foundation Models Via Agreement-on-the-line, by Rahul Saxena et al.
Predicting the Performance of Foundation Models via Agreement-on-the-Lineby Rahul Saxena, Taeyoun Kim, Aman Mehra, Christina…
Predicting the Performance of Foundation Models via Agreement-on-the-Lineby Rahul Saxena, Taeyoun Kim, Aman Mehra, Christina…
Propensity Score Alignment of Unpaired Multimodal Databy Johnny Xi, Jana Osea, Zuheng Xu, Jason HartfordFirst…
Extremum-Seeking Action Selection for Accelerating Policy Optimizationby Ya-Chien Chang, Sicun GaoFirst submitted to arxiv on:…
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasksby Xingwu Chen,…
FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimalityby Sai Li,…
Audio Simulation for Sound Source Localization in Virtual Evironmentby Yi Di Yuan, Swee Liang Wong,…
Learning Equi-angular Representations for Online Continual Learningby Minhyuk Seo, Hyunseo Koh, Wonje Jeung, Minjae Lee,…
Learning to Control Camera Exposure via Reinforcement Learningby Kyunghyun Lee, Ukcheol Shin, Byeong-Uk LeeFirst submitted…
Patch Synthesis for Property Repair of Deep Neural Networksby Zhiming Chi, Jianan Ma, Pengfei Yang,…
Enhancing Functional Safety in Automotive AMS Circuits through Unsupervised Machine Learningby Ayush Arunachalam, Ian Kintz,…