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The exploding gradient problem demystified - definition, prevalence, impact, origin, tradeoffs, and solutions
George Philipp, Dawn Song, Jaime G. Carbonell
Whereas it is believed that techniques such as Adam, batch normalization and, more recently, SeLU nonlinearities "solve" the exploding gradient problem, we show that this is not th…
Adversarial Example Defenses: Ensembles of Weak Defenses are not Strong
Warren He, James Wei, Xinyun Chen +2
Ongoing research has proposed several methods to defend neural networks against adversarial examples, many of which researchers have shown to be ineffective. We ask whether a stron…
Towards Synthesizing Complex Programs from Input-Output Examples
Xinyun Chen, Chang Liu, Dawn Song
In recent years, deep learning techniques have been developed to improve the performance of program synthesis from input-output examples. Albeit its significant progress, the progr…
Making Neural Programming Architectures Generalize via Recursion
Jonathon Cai, Richard Shin, Dawn Song
Empirically, neural networks that attempt to learn programs from data have exhibited poor generalizability. Moreover, it has traditionally been difficult to reason about the behavi…