32 citations · 45 across the 6 of their papers we have counts for
7 papers
Recovering Linear Causal Models with Latent Variables via Cholesky Factorization of Covariance Matrix
Yunfeng Cai, Xu Li, Minging Sun +1
Discovering the causal relationship via recovering the directed acyclic graph (DAG) structure from the observed data is a well-known challenging combinatorial problem. When there a…
Covariance Regularization for Probabilistic Linear Discriminant Analysis
Zhiyuan Peng, Mingjie Shao, Xuanji He +4
Probabilistic linear discriminant analysis (PLDA) is commonly used in speaker verification systems to score the similarity of speaker embeddings. Recent studies improved the perfor…
CGAR: Critic Guided Action Redistribution in Reinforcement Leaning
Tairan Huang, Xu Li, Hao Li +2
Training a game-playing reinforcement learning agent requires multiple interactions with the environment. Ignorant random exploration may cause a waste of time and resources. It's…
Joint learning of object graph and relation graph for visual question answering
Hao Li, Xu Li, Belhal Karimi +2
Modeling visual question answering(VQA) through scene graphs can significantly improve the reasoning accuracy and interpretability. However, existing models answer poorly for compl…
S-MLPv2: Improved Spatial-Shift MLP Architecture for Vision
Tan Yu, Xu Li, Yunfeng Cai +2
Recently, MLP-based vision backbones emerge. MLP-based vision architectures with less inductive bias achieve competitive performance in image recognition compared with CNNs and vis…
Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation
Haiyan Yin, Dingcheng Li, Xu Li +1
Training generative models that can generate high-quality text with sufficient diversity is an important open problem for Natural Language Generation (NLG) community. Recently, gen…
Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction
Mingming Sun, Xu Li, Xin Wang +3
In this paper, we consider the problem of open information extraction (OIE) for extracting entity and relation level intermediate structures from sentences in open-domain. We focus…