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05/21/2022
Bias-robust Integration of Observational and Experimental Estimators
We describe a simple approach for combining an unbiased and a (possibly)...
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01/26/2022
Recency Dropout for Recurrent Recommender Systems
Recurrent recommender systems have been successful in capturing the temp...
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05/23/2019
Quantifying Long Range Dependence in Language and User Behavior to improve RNNs
Characterizing temporal dependence patterns is a critical step in unders...
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02/26/2019
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
Recurrent neural networks have gained widespread use in modeling sequent...
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02/22/2019
Towards Neural Mixture Recommender for Long Range Dependent User Sequences
Understanding temporal dynamics has proved to be highly valuable for acc...
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01/25/2019
Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs
Training recurrent neural networks (RNNs) on long sequence tasks is plag...
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12/06/2018
Top-K Off-Policy Correction for a REINFORCE Recommender System
Industrial recommender systems deal with extremely large action spaces -...
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06/14/2018
Dynamical Isometry and a Mean Field Theory of RNNs: Gating Enables Signal Propagation in Recurrent Neural Networks
Recurrent neural networks have gained widespread use in modeling sequenc...
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11/18/2017
MinimalRNN: Toward More Interpretable and Trainable Recurrent Neural Networks
We introduce MinimalRNN, a new recurrent neural network architecture tha...
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07/08/2017
Efficient Vector Representation for Documents through Corruption
We present an efficient document representation learning framework, Docu...
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01/28/2013
An alternative text representation to TF-IDF and Bag-of-Words
In text mining, information retrieval, and machine learning, text docume...
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10/09/2012