82 citations · 175 across the 6 of their papers we have counts for
9 papers
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Full Version
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang +3
A variety of real-world applications rely on far future information to make decisions, thus calling for efficient and accurate long sequence multivariate time series forecasting. W…
Rethinking Co-design of Neural Architectures and Hardware Accelerators
Yanqi Zhou, Xuanyi Dong, Berkin Akin +7
Neural architectures and hardware accelerators have been two driving forces for the progress in deep learning. Previous works typically attempt to optimize hardware given a fixed m…
Isometric Propagation Network for Generalized Zero-shot Learning
Lu Liu, Tianyi Zhou, Guodong Long +3
Zero-shot learning (ZSL) aims to classify images of an unseen class only based on a few attributes describing that class but no access to any training sample. A popular strategy is…
Supervision by Registration and Triangulation for Landmark Detection
Xuanyi Dong, Yi Yang, Shih-En Wei +3
We present Supervision by Registration and Triangulation (SRT), an unsupervised approach that utilizes unlabeled multi-view video to improve the accuracy and precision of landmark…
NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size
Xuanyi Dong, Lu Liu, Katarzyna Musial +1
Neural architecture search (NAS) has attracted a lot of attention and has been illustrated to bring tangible benefits in a large number of applications in the past few years. Archi…
AutoHAS: Efficient Hyperparameter and Architecture Search
Xuanyi Dong, Mingxing Tan, Adams Wei Yu +3
Efficient hyperparameter or architecture search methods have shown remarkable results, but each of them is only applicable to searching for either hyperparameters (HPs) or architec…