2 citations · 3 across the 2 of their papers we have counts for
4 papers
Stochastic Negative Mining for Learning with Large Output Spaces
Sashank J. Reddi, Satyen Kale, Felix Yu +3
We consider the problem of retrieving the most relevant labels for a given input when the size of the output space is very large. Retrieval methods are modeled as set-valued classi…
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi +5
Linear encoding of sparse vectors is widely popular, but is commonly data-independent -- missing any possible extra (but a priori unknown) structure beyond sparsity. In this paper…
Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition
Shankar Kumar, Michael Nirschl, Daniel Holtmann-Rice +3
Recurrent neural network (RNN) language models (LMs) and Long Short Term Memory (LSTM) LMs, a variant of RNN LMs, have been shown to outperform traditional N-gram LMs on speech rec…
What's In A Patch, I: Tensors, Differential Geometry and Statistical Shading Analysis
Daniel Niels Holtmann-Rice, Benjamin S. Kunsberg, Steven W. Zucker
We develop a linear algebraic framework for the shape-from-shading problem, because tensors arise when scalar (e.g. image) and vector (e.g. surface normal) fields are differentiate…