Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
The accurate prediction of program's memory requirements is a critical component in software development. Existing heap space analyses either do not take deallocation into ac...
In this paper, we propose a new way to automatically model and predict human behavior of receiving and disseminating information by analyzing the contact and content of personal c...
Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming...
Large-scale websites are increasingly moving from relational databases to distributed key-value stores for high request rate, low latency workloads. Often this move is motivated n...
Michael Armbrust, Stephen Tu, Armando Fox, Michael...