Search Results for author:
Found 5 papers, 2 papers with code
An Imitation Game for Learning Semantic Parsers from User Interaction
Despite the widely successful applications, bootstrapping and fine-tuning semantic parsers are still a tedious process with challenges such as costly data annotation and privacy risks.
Training Deep Neural Networks with Partially Adaptive Momentum
Experiments on standard benchmarks show that our proposed algorithm can maintain fast convergence rate as Adam/Amsgrad while generalizing as well as SGD in training deep neural networks.
On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization
In this paper, we provide a fine-grained convergence analysis for a general class of adaptive gradient methods including AMSGrad, RMSProp and AdaGrad.
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks
Experiments on standard benchmarks show that our proposed algorithm can maintain a fast convergence rate as Adam/Amsgrad while generalizing as well as SGD in training deep neural networks.
Label Propagation on K-partite Graphs with Heterophily
In this paper, for the first time, we study label propagation in heterogeneous graphs under heterophily assumption.
