123 citations · 221 across the 17 of their papers we have counts for
5 papers · 1 filter
Semi-Unified Sparse Dictionary Learning with Learnable Top-K LISTA and FISTA Encoders
Fengsheng Lin, Shengyi Yan, Trac Duy Tran
We present a semi-unified sparse dictionary learning framework that bridges the gap between classical sparse models and modern deep architectures. Specifically, the method integrat…
NAS-Bench-x11 and the Power of Learning Curves
Shen Yan, Colin White, Yash Savani +1
While early research in neural architecture search (NAS) required extreme computational resources, the recent releases of tabular and surrogate benchmarks have greatly increased th…
CATE: Computation-aware Neural Architecture Encoding with Transformers
Shen Yan, Kaiqiang Song, Fei Liu +1
Recent works (White et al., 2020a; Yan et al., 2020) demonstrate the importance of architecture encodings in Neural Architecture Search (NAS). These encodings encode either structu…
Deep Learning in the Era of Edge Computing: Challenges and Opportunities
Mi Zhang, Faen Zhang, Nicholas D. Lane +5
The era of edge computing has arrived. Although the Internet is the backbone of edge computing, its true value lies at the intersection of gathering data from sensors and extractin…
HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
Shen Yan, Biyi Fang, Faen Zhang +4
The use of automatic methods, often referred to as Neural Architecture Search (NAS), in designing neural network architectures has recently drawn considerable attention. In this wo…