research
∙
02/13/2023
In Search for a Generalizable Method for Source Free Domain Adaptation
Source-free domain adaptation (SFDA) is compelling because it allows ada...
share
research
∙
01/13/2022
GradMax: Growing Neural Networks using Gradient Information
The architecture and the parameters of neural networks are often optimiz...
research
∙
06/08/2020
Halting Time is Predictable for Large Models: A Universality Property and Average-case Analysis
Average-case analysis computes the complexity of an algorithm averaged o...
research
∙
06/27/2019
Fast Training of Sparse Graph Neural Networks on Dense Hardware
Graph neural networks have become increasingly popular in recent years d...
research
∙
06/18/2019
Information matrices and generalization
This work revisits the use of information criteria to characterize the g...
research
∙
10/26/2018
Automatic differentiation in ML: Where we are and where we should be going
We review the current state of automatic differentiation (AD) for array ...
research
∙
09/25/2018
Tangent: Automatic differentiation using source-code transformation for dynamically typed array programming
The need to efficiently calculate first- and higher-order derivatives of...
research
∙
11/07/2017
Tangent: Automatic Differentiation Using Source Code Transformation in Python
Automatic differentiation (AD) is an essential primitive for machine lea...
research
∙
07/03/2017
Multiscale sequence modeling with a learned dictionary
We propose a generalization of neural network sequence models. Instead o...
research
∙
05/09/2016
Theano: A Python framework for fast computation of mathematical expressions
Theano is a Python library that allows to define, optimize, and evaluate...
research
∙
06/01/2015
Blocks and Fuel: Frameworks for deep learning
We introduce two Python frameworks to train neural networks on large dat...
research
∙
02/19/2015
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
One long-term goal of machine learning research is to produce methods th...
research
∙
09/03/2014
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
The authors of (Cho et al., 2014a) have shown that the recently introduc...
research
∙
06/03/2014