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Found 6 papers, 1 papers with code
ToDo: Token Downsampling for Efficient Generation of High-Resolution Images
Attention mechanism has been crucial for image diffusion models, however, their quadratic computational complexity limits the sizes of images we can process within reasonable time and memory constraints.
Towards One Shot Search Space Poisoning in Neural Architecture Search
We evaluate the robustness of a Neural Architecture Search (NAS) algorithm known as Efficient NAS (ENAS) against data agnostic poisoning attacks on the original search space with carefully designed ineffective operations.
Sign-to-Speech Model for Sign Language Understanding: A Case Study of Nigerian Sign Language
Through this paper, we seek to reduce the communication barrier between the hearing-impaired community and the larger society who are usually not familiar with sign language in the sub-Saharan region of Africa with the largest occurrences of hearing disability cases, while using Nigeria as a case study.
NeuralArTS: Structuring Neural Architecture Search with Type Theory
Neural Architecture Search (NAS) algorithms automate the task of finding optimal deep learning architectures given an initial search space of possible operations.
Statistical Consequences of Dueling Bandits
Multi-Armed-Bandit frameworks have often been used by researchers to assess educational interventions, however, recent work has shown that it is more beneficial for a student to provide qualitative feedback through preference elicitation between different alternatives, making a dueling bandits framework more appropriate.
Poisoning the Search Space in Neural Architecture Search
Deep learning has proven to be a highly effective problem-solving tool for object detection and image segmentation across various domains such as healthcare and autonomous driving.
