Summary of Ask Your Distribution Shift If Pre-training Is Right For You, by Benjamin Cohen-wang et al.
Ask Your Distribution Shift if Pre-Training is Right for Youby Benjamin Cohen-Wang, Joshua Vendrow, Aleksander…
Summary of Shifted Interpolation For Differential Privacy, by Jinho Bok et al.
Shifted Interpolation for Differential Privacyby Jinho Bok, Weijie Su, Jason M. AltschulerFirst submitted to arxiv…
Summary of Introducing User Feedback-based Counterfactual Explanations (ufce), by Muhammad Suffian et al.
Introducing User Feedback-based Counterfactual Explanations (UFCE)by Muhammad Suffian, Jose M. Alonso-Moral, Alessandro BoglioloFirst submitted to…
Summary of Learning to Deliver: a Foundation Model For the Montreal Capacitated Vehicle Routing Problem, by Samuel J. K. Chin et al.
Learning to Deliver: a Foundation Model for the Montreal Capacitated Vehicle Routing Problemby Samuel J.…
Summary of On Robustness and Generalization Of Ml-based Congestion Predictors to Valid and Imperceptible Perturbations, by Chester Holtz et al.
On Robustness and Generalization of ML-Based Congestion Predictors to Valid and Imperceptible Perturbationsby Chester Holtz,…
Summary of Longitudinal Counterfactuals: Constraints and Opportunities, by Alexander Asemota and Giles Hooker
Longitudinal Counterfactuals: Constraints and Opportunitiesby Alexander Asemota, Giles HookerFirst submitted to arxiv on: 29 Feb…
Summary of Privacy-preserving Distributed Optimization and Learning, by Ziqin Chen and Yongqiang Wang
Privacy-Preserving Distributed Optimization and Learningby Ziqin Chen, Yongqiang WangFirst submitted to arxiv on: 29 Feb…
Summary of Rl-gpt: Integrating Reinforcement Learning and Code-as-policy, by Shaoteng Liu et al.
RL-GPT: Integrating Reinforcement Learning and Code-as-policyby Shaoteng Liu, Haoqi Yuan, Minda Hu, Yanwei Li, Yukang…
Summary of Loss-free Machine Unlearning, by Jack Foster et al.
Loss-Free Machine Unlearningby Jack Foster, Stefan Schoepf, Alexandra BrintrupFirst submitted to arxiv on: 29 Feb…
Summary of Training Dynamics Of Multi-head Softmax Attention For In-context Learning: Emergence, Convergence, and Optimality, by Siyu Chen et al.
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimalityby Siyu Chen,…