Summary of Guided Trajectory Generation with Diffusion Models For Offline Model-based Optimization, by Taeyoung Yun et al.
Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimizationby Taeyoung Yun, Sujin Yun, Jaewoo…
Summary of Badllama 3: Removing Safety Finetuning From Llama 3 in Minutes, by Dmitrii Volkov
Badllama 3: removing safety finetuning from Llama 3 in minutesby Dmitrii VolkovFirst submitted to arxiv…
Summary of Fastclip: a Suite Of Optimization Techniques to Accelerate Clip Training with Limited Resources, by Xiyuan Wei et al.
FastCLIP: A Suite of Optimization Techniques to Accelerate CLIP Training with Limited Resourcesby Xiyuan Wei,…
Summary of Information-theoretic Foundations For Neural Scaling Laws, by Hong Jun Jeon et al.
Information-Theoretic Foundations for Neural Scaling Lawsby Hong Jun Jeon, Benjamin Van RoyFirst submitted to arxiv…
Summary of Scalable Nested Optimization For Deep Learning, by Jonathan Lorraine
Scalable Nested Optimization for Deep Learningby Jonathan LorraineFirst submitted to arxiv on: 1 Jul 2024CategoriesMain:…
Summary of Tparafac2: Tracking Evolving Patterns in (incomplete) Temporal Data, by Christos Chatzis et al.
tPARAFAC2: Tracking evolving patterns in (incomplete) temporal databy Christos Chatzis, Carla Schenker, Max Pfeffer, Evrim…
Summary of Joint Pruning and Channel-wise Mixed-precision Quantization For Efficient Deep Neural Networks, by Beatrice Alessandra Motetti et al.
Joint Pruning and Channel-wise Mixed-Precision Quantization for Efficient Deep Neural Networksby Beatrice Alessandra Motetti, Matteo…
Summary of Wind Estimation in Unmanned Aerial Vehicles with Causal Machine Learning, by Abdulaziz Alwalan et al.
Wind Estimation in Unmanned Aerial Vehicles with Causal Machine Learningby Abdulaziz Alwalan, Miguel Arana-CataniaFirst submitted…
Summary of Cpt: Consistent Proxy Tuning For Black-box Optimization, by Yuanyang He et al.
CPT: Consistent Proxy Tuning for Black-box Optimizationby Yuanyang He, Zitong Huang, Xinxing Xu, Rick Siow…
Summary of Neural Conditional Probability For Inference, by Vladimir R. Kostic et al.
Neural Conditional Probability for Inferenceby Vladimir R. Kostic, Karim Lounici, Gregoire Pacreau, Pietro Novelli, Giacomo…