Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper.
Query: Learning Recurrent Binary/Ternary Weights
Ternary Weight Networks
Towards Binary-Valued Gates for Robust LSTM Training
Gated XNOR Networks: Deep Neural Networks with Ternary Weights and Activations under a Unified Discretization Framework
Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1
From Hashing to CNNs: Training BinaryWeight Networks via Hashing
Professor Forcing: A New Algorithm for Training Recurrent Networks
Gradient-Based Learning Algorithms for Recurrent Connectionist Networks
Backpropagation-decorrelation: online recurrent learning with O(N) complexity
Perceptron learning for reuse prediction
A Fast Optimization Method for General Binary Code Learning.
Training Compact Neural Networks with Binary Weights and Low Precision Activations
Advances in optimizing recurrent networks
BINARIZED NEURAL NETWORKS
GXNOR-Net: Training deep neural networks with ternary weights and activations without full-precision memory under a unified discretization framework
Markov Chain Hebbian Learning Algorithm With Ternary Synaptic Units
An Efficient Kernel Transformation Architecture for Binary- and Ternary-Weight Neural Network Inference
Hebbian Learning of Context in Recurrent Neural Networks
DeepBE: Learning Deep Binary Encoding for Multi-label Classification
Memory replay in balanced recurrent networks
Capacity and Trainability in Recurrent Neural Networks
Detecting hashtag hijacking from Twitter
Towards Synthesizing Complex Programs from Input-Output Examples
Deep Learning using Linear Support Vector Machines
Recognizing and Segmenting Objects in the Presence of Occlusion and Clutter
An epsilon negative metamaterial antenna with extended bandwidth