Summary of Confronting the Reproducibility Crisis: a Case Study Of Challenges in Cybersecurity Ai, by Richard H. Moulton et al.
Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AIby Richard H. Moulton,…
Summary of Provable Contrastive Continual Learning, by Yichen Wen et al.
Provable Contrastive Continual Learningby Yichen Wen, Zhiquan Tan, Kaipeng Zheng, Chuanlong Xie, Weiran HuangFirst submitted…
Summary of Learning to Continually Learn with the Bayesian Principle, by Soochan Lee et al.
Learning to Continually Learn with the Bayesian Principleby Soochan Lee, Hyeonseong Jeon, Jaehyeon Son, Gunhee…
Summary of Large Brain Model For Learning Generic Representations with Tremendous Eeg Data in Bci, by Wei-bang Jiang et al.
Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCIby Wei-Bang Jiang,…
Summary of Fdqn: a Flexible Deep Q-network Framework For Game Automation, by Prabhath Reddy Gujavarthy
FDQN: A Flexible Deep Q-Network Framework for Game Automationby Prabhath Reddy GujavarthyFirst submitted to arxiv…
Summary of Quantitative Certification Of Bias in Large Language Models, by Isha Chaudhary et al.
Quantitative Certification of Bias in Large Language Modelsby Isha Chaudhary, Qian Hu, Manoj Kumar, Morteza…
Summary of On the Role Of Attention Masks and Layernorm in Transformers, by Xinyi Wu et al.
On the Role of Attention Masks and LayerNorm in Transformersby Xinyi Wu, Amir Ajorlou, Yifei…
Summary of Kernel Metric Learning For In-sample Off-policy Evaluation Of Deterministic Rl Policies, by Haanvid Lee et al.
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policiesby Haanvid Lee, Tri Wahyu…
Summary of Policy Zooming: Adaptive Discretization-based Infinite-horizon Average-reward Reinforcement Learning, by Avik Kar and Rahul Singh
Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learningby Avik Kar, Rahul SinghFirst submitted to arxiv…
Summary of Federated Q-learning with Reference-advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost, by Zhong Zheng et al.
Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Costby Zhong Zheng, Haochen…