63 citations · 69 across the 4 of their papers we have counts for
7 papers
Synt++: Utilizing Imperfect Synthetic Data to Improve Speech Recognition
Ting-Yao Hu, Mohammadreza Armandpour, Ashish Shrivastava +3
With recent advances in speech synthesis, synthetic data is becoming a viable alternative to real data for training speech recognition models. However, machine learning with synthe…
Deep Spatio-Temporal Wind Power Forecasting
Jiangyuan Li, Mohammadreza Armandpour
Wind power forecasting has drawn increasing attention among researchers as the consumption of renewable energy grows. In this paper, we develop a deep learning approach based on en…
Deep Personalized Glucose Level Forecasting Using Attention-based Recurrent Neural Networks
Mohammadreza Armandpour, Brian Kidd, Yu Du +1
In this paper, we study the problem of blood glucose forecasting and provide a deep personalized solution. Predicting blood glucose level in people with diabetes has significant va…
Partition-Guided GANs
Mohammadreza Armandpour, Ali Sadeghian, Chunyuan Li +1
Despite the success of Generative Adversarial Networks (GANs), their training suffers from several well-known problems, including mode collapse and difficulties learning a disconne…
ChronoR: Rotation Based Temporal Knowledge Graph Embedding
Ali Sadeghian, Mohammadreza Armandpour, Anthony Colas +1
Despite the importance and abundance of temporal knowledge graphs, most of the current research has been focused on reasoning on static graphs. In this paper, we study the challeng…
Convex Polytope Trees
Mohammadreza Armandpour, Mingyuan Zhou
A decision tree is commonly restricted to use a single hyperplane to split the covariate space at each of its internal nodes. It often requires a large number of nodes to achieve h…