78 citations · 144 across the 8 of their papers we have counts for
16 papers
Meta-CPR: Generalize to Unseen Large Number of Agents with Communication Pattern Recognition Module
Wei-Cheng Tseng, Wei Wei, Da-Cheng Juan +1
Designing an effective communication mechanism among agents in reinforcement learning has been a challenging task, especially for real-world applications. The number of agents can…
Uncertainty Modeling of Emerging Device-based Computing-in-Memory Neural Accelerators with Application to Neural Architecture Search
Zheyu Yan, Da-Cheng Juan, Xiaobo Sharon Hu +1
Emerging device-based Computing-in-memory (CiM) has been proved to be a promising candidate for high-energy efficiency deep neural network (DNN) computations. However, most emergin…
Learning with Hierarchical Complement Objective
Hao-Yun Chen, Li-Huang Tsai, Shih-Chieh Chang +4
Label hierarchies widely exist in many vision-related problems, ranging from explicit label hierarchies existed in image classification to latent label hierarchies existed in seman…
Natural Adversarial Sentence Generation with Gradient-based Perturbation
Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan +3
This work proposes a novel algorithm to generate natural language adversarial input for text classification models, in order to investigate the robustness of these models. It invol…
COCO-GAN: Generation by Parts via Conditional Coordinating
Chieh Hubert Lin, Chia-Che Chang, Yu-Sheng Chen +3
Humans can only interact with part of the surrounding environment due to biological restrictions. Therefore, we learn to reason the spatial relationships across a series of observa…
Complement Objective Training
Hao-Yun Chen, Pei-Hsin Wang, Chun-Hao Liu +5
Learning with a primary objective, such as softmax cross entropy for classification and sequence generation, has been the norm for training deep neural networks for years. Although…