26 citations · 62 across the 14 of their papers we have counts for
14 papers
Extending the saemix package for R to fit non Gaussian outcomes
Emmanuelle Comets, Maud Delattre, Belhal Karimi
Background and Objectives: Longitudinal data are increasingly collected in clinical trials to provide information on treatment action and disease evolution. The trajectory of conti…
STANLEY: Stochastic Gradient Anisotropic Langevin Dynamics for Learning Energy-Based Models
Belhal Karimi, Jianwen Xie, Ping Li
We propose in this paper, STANLEY, a STochastic gradient ANisotropic LangEvin dYnamics, for sampling high dimensional data. With the growing efficacy and potential of Energy-Based…
FeatureBox: Feature Engineering on GPUs for Massive-Scale Ads Systems
Weijie Zhao, Xuewu Jiao, Xinsheng Luo +3
Deep learning has been widely deployed for online ads systems to predict Click-Through Rate (CTR). Machine learning researchers and practitioners frequently retrain CTR models to t…
Variational Flow Graphical Model
Shaogang Ren, Belhal Karimi, Dingcheng Li +1
This paper introduces a novel approach to embed flow-based models with hierarchical structures. The proposed framework is named Variational Flow Graphical (VFG) Model. VFGs learn t…
On Distributed Adaptive Optimization with Gradient Compression
Xiaoyun Li, Belhal Karimi, Ping Li
We study COMP-AMS, a distributed optimization framework based on gradient averaging and adaptive AMSGrad algorithm. Gradient compression with error feedback is applied to reduce th…
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…