Summary of Beyond Slow Signs in High-fidelity Model Extraction, by Hanna Foerster et al.
Beyond Slow Signs in High-fidelity Model Extractionby Hanna Foerster, Robert Mullins, Ilia Shumailov, Jamie HayesFirst…
Summary of An Elementary Proof Of a Universal Approximation Theorem, by Chris Monico
An elementary proof of a universal approximation theoremby Chris MonicoFirst submitted to arxiv on: 14…
Summary of Gradient-based Learning in State-based Potential Games For Self-learning Production Systems, by Steve Yuwono et al.
Gradient-based Learning in State-based Potential Games for Self-Learning Production Systemsby Steve Yuwono, Marlon Löppenberg, Dorothea…
Summary of Large Language Model Validity Via Enhanced Conformal Prediction Methods, by John J. Cherian et al.
Large language model validity via enhanced conformal prediction methodsby John J. Cherian, Isaac Gibbs, Emmanuel…
Summary of When Will Gradient Regularization Be Harmful?, by Yang Zhao et al.
When Will Gradient Regularization Be Harmful?by Yang Zhao, Hao Zhang, Xiuyuan HuFirst submitted to arxiv…
Summary of Deep Symbolic Optimization For Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics, By Hongyu Liu et al.
Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristicsby Hongyu Liu,…
Summary of Cross-view Geo-localization: a Survey, by Abhilash Durgam et al.
Cross-view geo-localization: a surveyby Abhilash Durgam, Sidike Paheding, Vikas Dhiman, Vijay DevabhaktuniFirst submitted to arxiv…
Summary of How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis, by Yuxin Dong et al.
How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysisby Yuxin Dong, Tieliang Gong, Hong…
Summary of Bootstrapping Language Models with Dpo Implicit Rewards, by Changyu Chen et al.
Bootstrapping Language Models with DPO Implicit Rewardsby Changyu Chen, Zichen Liu, Chao Du, Tianyu Pang,…
Summary of Faster Convergence on Heterogeneous Federated Edge Learning: An Adaptive Clustered Data Sharing Approach, by Gang Hu et al.
Faster Convergence on Heterogeneous Federated Edge Learning: An Adaptive Clustered Data Sharing Approachby Gang Hu,…