Country
DetNAS: Backbone Search for Object Detection
Yukang Chen, Tong Yang, Xiangyu Zhang, GAOFENG MENG, Xinyu Xiao, Jian Sun
Neural Information Processing Systems http://nips.cc/
Regularizing Trajectory Optimization with Denoising Autoencoders
Rinu Boney, Norman Di Palo, Mathias Berglund, Alexander Ilin, Juho Kannala, Antti Rasmus, Harri Valpola
Neural Information Processing Systems http://nips.cc/
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond
Lin Chen, Hossein Esfandiari, Gang Fu, Vahab Mirrokni
Neural Information Processing Systems http://nips.cc/
e7dfca01f394755c11f853602cb2608a-Paper.pdf
The dense connections between layers change the definition of what from one layer to the next.
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models Jiaqi Li
Machine unlearning (MU) empowers individuals with the'right to be forgotten' by removing their private or sensitive information encoded in machine learning models. However, it remains uncertain whether MU can be effectively applied to Multimodal Large Language Models (MLLMs), particularly in scenarios of forgetting the leaked visual data of concepts.
Chirality Nets for Human Pose Regression
Raymond Yeh, Yuan-Ting Hu, Alexander Schwing
The proposed layers lead toamore data efficient representation and areduction in computation by exploiting symmetry. We evaluate chirality nets on the task ofhuman poseregression, which naturally exploits theleft/right mirroring ofthe human body.
Extensive-Form Game Solving via Blackwell Approachability on Treeplexes
In this paper, we focus on solving Extensive-F orm Games (EFGs).
bc218a0c656e49d4b086975a9c785f47-Supplemental-Datasets_and_Benchmarks.pdf
Emerging ethical approaches have attempted to filter pretraining material, but such approaches have been ad hoc and failed to take context into account. We offer an approach to filtering grounded in law, which has directly addressed the tradeoffs in filtering material.