86 citations · 356 across the 24 of their papers we have counts for
4 papers · 1 filter
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs
Francois Belletti, Minmin Chen, Ed H. Chi
Characterizing temporal dependence patterns is a critical step in understanding the statistical properties of sequential data. Long Range Dependence (LRD) --- referring to long-ran…
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
Bo Chang, Minmin Chen, Eldad Haber +1
Recurrent neural networks have gained widespread use in modeling sequential data. Learning long-term dependencies using these models remains difficult though, due to exploding or v…
Towards Neural Mixture Recommender for Long Range Dependent User Sequences
Jiaxi Tang, Francois Belletti, Sagar Jain +4
Understanding temporal dynamics has proved to be highly valuable for accurate recommendation. Sequential recommenders have been successful in modeling the dynamics of users and ite…
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs
Dar Gilboa, Bo Chang, Minmin Chen +4
Training recurrent neural networks (RNNs) on long sequence tasks is plagued with difficulties arising from the exponential explosion or vanishing of signals as they propagate forwa…