research
∙
09/30/2022
Sparsity-Constrained Optimal Transport
Regularized optimal transport (OT) is now increasingly used as a loss or...
share
research
∙
10/07/2021
Universal Approximation Under Constraints is Possible with Transformers
Many practical problems need the output of a machine learning model to s...
research
∙
11/25/2020
Interpreting U-Nets via Task-Driven Multiscale Dictionary Learning
U-Nets have been tremendously successful in many imaging inverse problem...
research
∙
06/15/2020
Finding trainable sparse networks through Neural Tangent Transfer
Deep neural networks have dramatically transformed machine learning, but...
research
∙
11/24/2019
Causally Denoise Word Embeddings Using Half-Sibling Regression
Distributional representations of words, also known as word vectors, hav...
research
∙
05/28/2019
Harnessing Slow Dynamics in Neuromorphic Computation
Neuromorphic Computing is a nascent research field in which models and d...
research
∙
04/18/2019
Continual Learning for Sentence Representations Using Conceptors
Distributed representations of sentences have become ubiquitous in natur...
research
∙
11/17/2018
Correcting the Common Discourse Bias in Linear Representation of Sentences using Conceptors
Distributed representations of words, better known as word embeddings, h...
research
∙
11/17/2018
Unsupervised Post-processing of Word Vectors via Conceptor Negation
Word vectors are at the core of many natural language processing tasks. ...
research
∙
08/11/2018
A Consistent Method for Learning OOMs from Asymptotically Stationary Time Series Data Containing Missing Values
In the traditional framework of spectral learning of stochastic time ser...
research
∙
01/30/2018
