10 citations · 18 across the 6 of their papers we have counts for
6 papers
MAT: Mixed-Strategy Game of Adversarial Training in Fine-tuning
Zhehua Zhong, Tianyi Chen, Zhen Wang
Fine-tuning large-scale pre-trained language models has been demonstrated effective for various natural language processing (NLP) tasks. Previous studies have established that inco…
Automated Search-Space Generation Neural Architecture Search
Tianyi Chen, Luming Liang, Tianyu Ding +1
To search an optimal sub-network within a general deep neural network (DNN), existing neural architecture search (NAS) methods typically rely on handcrafting a search space beforeh…
OTOV2: Automatic, Generic, User-Friendly
Tianyi Chen, Luming Liang, Tianyu Ding +2
The existing model compression methods via structured pruning typically require complicated multi-stage procedures. Each individual stage necessitates numerous engineering efforts…
Alternating Implicit Projected SGD and Its Efficient Variants for Equality-constrained Bilevel Optimization
Quan Xiao, Han Shen, Wotao Yin +1
Stochastic bilevel optimization, which captures the inherent nested structure of machine learning problems, is gaining popularity in many recent applications. Existing works on bil…
Lazy Queries Can Reduce Variance in Zeroth-order Optimization
Quan Xiao, Qing Ling, Tianyi Chen
A major challenge of applying zeroth-order (ZO) methods is the high query complexity, especially when queries are costly. We propose a novel gradient estimation technique for ZO me…
Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning
Momin Abbas, Quan Xiao, Lisha Chen +2
Model-agnostic meta learning (MAML) is currently one of the dominating approaches for few-shot meta-learning. Albeit its effectiveness, the optimization of MAML can be challenging…