228 citations · 2.2k across the 99 of their papers we have counts for
17 papers · 1 filter
Interpretation of Time-Series Deep Models: A Survey
Ziqi Zhao, Yucheng Shi, Shushan Wu +3
Deep learning models developed for time-series associated tasks have become more widely researched nowadays. However, due to the unintuitive nature of time-series data, the interpr…
DEGREE: Decomposition Based Explanation For Graph Neural Networks
Qizhang Feng, Ninghao Liu, Fan Yang +3
Graph Neural Networks (GNNs) are gaining extensive attention for their application in graph data. However, the black-box nature of GNNs prevents users from understanding and trusti…
CoRTX: Contrastive Framework for Real-time Explanation
Yu-Neng Chuang, Guanchu Wang, Fan Yang +4
Recent advancements in explainable machine learning provide effective and faithful solutions for interpreting model behaviors. However, many explanation methods encounter efficienc…
Data-centric Artificial Intelligence: A Survey
Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai +4
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler of its great success is the availability of abundant and high-quality data for buil…
Efficient XAI Techniques: A Taxonomic Survey
Yu-Neng Chuang, Guanchu Wang, Fan Yang +4
Recently, there has been a growing demand for the deployment of Explainable Artificial Intelligence (XAI) algorithms in real-world applications. However, traditional XAI methods ty…
Learning Cooperative Oversubscription for Cloud by Chance-Constrained Multi-Agent Reinforcement Learning
Junjie Sheng, Lu Wang, Fangkai Yang +9
Oversubscription is a common practice for improving cloud resource utilization. It allows the cloud service provider to sell more resources than the physical limit, assuming not al…
Deep-Learning-Empowered Inverse Design for Freeform Reconfigurable Metasurfaces
Changhao Liu, Fan Yang, Maokun Li +1
The past decade has witnessed the advances of artificial intelligence with various applications in engineering. Recently, artificial neural network empowered inverse design for met…
Improving alignment of dialogue agents via targeted human judgements
Amelia Glaese, Nat McAleese, Maja Trębacz +31
We present Sparrow, an information-seeking dialogue agent trained to be more helpful, correct, and harmless compared to prompted language model baselines. We use reinforcement lear…
Differentially Private Counterfactuals via Functional Mechanism
Fan Yang, Qizhang Feng, Kaixiong Zhou +2
Counterfactual, serving as one emerging type of model explanation, has attracted tons of attentions recently from both industry and academia. Different from the conventional featur…
Accelerating Shapley Explanation via Contributive Cooperator Selection
Guanchu Wang, Yu-Neng Chuang, Mengnan Du +5
Even though Shapley value provides an effective explanation for a DNN model prediction, the computation relies on the enumeration of all possible input feature coalitions, which le…
Learning from Attacks: Attacking Variational Autoencoder for Improving Image Classification
Jianzhang Zheng, Fan Yang, Hao Shen +4
Adversarial attacks are often considered as threats to the robustness of Deep Neural Networks (DNNs). Various defending techniques have been developed to mitigate the potential neg…
Defense Against Explanation Manipulation
Ruixiang Tang, Ninghao Liu, Fan Yang +2
Explainable machine learning attracts increasing attention as it improves transparency of models, which is helpful for machine learning to be trusted in real applications. However,…
Adaptive Label Smoothing To Regularize Large-Scale Graph Training
Kaixiong Zhou, Ninghao Liu, Fan Yang +5
Graph neural networks (GNNs), which learn the node representations by recursively aggregating information from its neighbors, have become a predominant computational tool in many d…
Model-Based Counterfactual Synthesizer for Interpretation
Fan Yang, Sahan Suresh Alva, Jiahao Chen +1
Counterfactuals, serving as one of the emerging type of model interpretations, have recently received attention from both researchers and practitioners. Counterfactual explanations…
Defending SVMs against Poisoning Attacks: the Hardness and DBSCAN Approach
Hu Ding, Fan Yang, Jiawei Huang
Adversarial machine learning has attracted a great amount of attention in recent years. In a poisoning attack, the adversary can inject a small number of specially crafted samples…
Relational State-Space Model for Stochastic Multi-Object Systems
Fan Yang, Ling Chen, Fan Zhou +2
Real-world dynamical systems often consist of multiple stochastic subsystems that interact with each other. Modeling and forecasting the behavior of such dynamics are generally not…
Good Semi-supervised Learning that Requires a Bad GAN
Zihang Dai, Zhilin Yang, Fan Yang +2
Semi-supervised learning methods based on generative adversarial networks (GANs) obtained strong empirical results, but it is not clear 1) how the discriminator benefits from joint…