86 citations · 433 across the 35 of their papers we have counts for
9 papers · 1 filter
ARSM Gradient Estimator for Supervised Learning to Rank
Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou +1
We propose a new model for supervised learning to rank. In our model, the relevance labels are assumed to follow a categorical distribution whose probabilities are constructed base…
Semi-Implicit Stochastic Recurrent Neural Networks
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield +3
Stochastic recurrent neural networks with latent random variables of complex dependency structures have shown to be more successful in modeling sequential data than deterministic d…
Variational Graph Recurrent Neural Networks
Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield +3
Representation learning over graph structured data has been mostly studied in static graph settings while efforts for modeling dynamic graphs are still scant. In this paper, we dev…
Semi-Implicit Graph Variational Auto-Encoders
Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield +3
Semi-implicit graph variational auto-encoder (SIG-VAE) is proposed to expand the flexibility of variational graph auto-encoders (VGAE) to model graph data. SIG-VAE employs a hierar…
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images
Wuyang Chen, Ziyu Jiang, Zhangyang Wang +2
Segmentation of ultra-high resolution images is increasingly demanded, yet poses significant challenges for algorithm efficiency, in particular considering the (GPU) memory limits.…
Optimal Clustering with Missing Values
Shahin Boluki, Siamak Zamani Dadaneh, Xiaoning Qian +1
Missing values frequently arise in modern biomedical studies due to various reasons, including missing tests or complex profiling technologies for different omics measurements. Mis…