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07/11/2023
Towards Robust and Efficient Continual Language Learning
As the application space of language models continues to evolve, a natur...
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04/25/2023
Towards Compute-Optimal Transfer Learning
The field of transfer learning is undergoing a significant shift with th...
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10/10/2022
Multi-step Planning for Automated Hyperparameter Optimization with OptFormer
As machine learning permeates more industries and models become more exp...
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05/26/2022
Towards Learning Universal Hyperparameter Optimizers with Transformers
Meta-learning hyperparameter optimization (HPO) algorithms from prior ex...
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06/17/2021
On Anytime Learning at Macroscale
Classical machine learning frameworks assume access to a possibly large ...
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06/06/2021
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation
One of the biggest challenges hindering progress in low-resource and mul...
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12/23/2020
Efficient Continual Learning with Modular Networks and Task-Driven Priors
Existing literature in Continual Learning (CL) has focused on overcoming...
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12/17/2020
Few-shot Sequence Learning with Transformers
Few-shot algorithms aim at learning new tasks provided only a handful of...
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05/01/2020
Multi-scale Transformer Language Models
We investigate multi-scale transformer language models that learn repres...
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04/22/2020
Residual Energy-Based Models for Text Generation
Text generation is ubiquitous in many NLP tasks, from summarization, to ...
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10/15/2019
Facebook AI's WAT19 Myanmar-English Translation Task Submission
This paper describes Facebook AI's submission to the WAT 2019 Myanmar-En...
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09/30/2019
Revisiting Self-Training for Neural Sequence Generation
Self-training is one of the earliest and simplest semi-supervised method...
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09/28/2019
The Source-Target Domain Mismatch Problem in Machine Translation
While we live in an increasingly interconnected world, different places ...
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08/14/2019
On The Evaluation of Machine Translation Systems Trained With Back-Translation
Back-translation is a widely used data augmentation technique which leve...
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07/10/2019
Large Memory Layers with Product Keys
This paper introduces a structured memory which can be easily integrated...
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06/07/2019
Real or Fake? Learning to Discriminate Machine from Human Generated Text
Recent advances in generative modeling of text have demonstrated remarka...
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05/15/2019
Task-Driven Modular Networks for Zero-Shot Compositional Learning
One of the hallmarks of human intelligence is the ability to compose lea...
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02/27/2019
Continual Learning with Tiny Episodic Memories
Learning with less supervision is a major challenge in artificial intell...
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02/20/2019
Mixture Models for Diverse Machine Translation: Tricks of the Trade
Mixture models trained via EM are among the simplest, most widely used a...
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02/04/2019
Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English
The vast majority of language pairs in the world are low-resource becaus...
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12/02/2018
Efficient Lifelong Learning with A-GEM
In lifelong learning, the learner is presented with a sequence of tasks,...
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11/01/2018
Multiple-Attribute Text Style Transfer
The dominant approach to unsupervised "style transfer" in text is based ...
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04/20/2018
Phrase-Based & Neural Unsupervised Machine Translation
Machine translation systems achieve near human-level performance on some...
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04/20/2018
Lightweight Adaptive Mixture of Neural and N-gram Language Models
It is often the case that the best performing language model is an ensem...
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02/28/2018
Analyzing Uncertainty in Neural Machine Translation
Machine translation is a popular test bed for research in neural sequenc...
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11/14/2017
Classical Structured Prediction Losses for Sequence to Sequence Learning
There has been much recent work on training neural attention models at t...
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10/31/2017
Unsupervised Machine Translation Using Monolingual Corpora Only
Machine translation has recently achieved impressive performance thanks ...
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10/11/2017
Word Translation Without Parallel Data
State-of-the-art methods for learning cross-lingual word embeddings have...
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06/26/2017
Gradient Episodic Memory for Continual Learning
One major obstacle towards AI is the poor ability of models to solve new...
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06/01/2017
Fader Networks: Manipulating Images by Sliding Attributes
This paper introduces a new encoder-decoder architecture that is trained...
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04/20/2017
Hard Mixtures of Experts for Large Scale Weakly Supervised Vision
Training convolutional networks (CNN's) that fit on a single GPU with mi...
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02/15/2017
Training Language Models Using Target-Propagation
While Truncated Back-Propagation through Time (BPTT) is the most popular...
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01/29/2017
Transformation-Based Models of Video Sequences
In this work we propose a simple unsupervised approach for next frame pr...
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12/15/2016
Learning through Dialogue Interactions by Asking Questions
A good dialogue agent should have the ability to interact with users by ...
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11/29/2016
Dialogue Learning With Human-In-The-Loop
An important aspect of developing conversational agents is to give a bot...
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11/20/2015
Sequence Level Training with Recurrent Neural Networks
Many natural language processing applications use language models to gen...
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06/26/2015
Convolutional networks and learning invariant to homogeneous multiplicative scalings
The conventional classification schemes -- notably multinomial logistic ...
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12/24/2014
Learning Longer Memory in Recurrent Neural Networks
Recurrent neural network is a powerful model that learns temporal patter...
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12/17/2014
Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews
Sentiment analysis is a common task in natural language processing that ...
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06/20/2014
Web-Scale Training for Face Identification
Scaling machine learning methods to very large datasets has attracted co...
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04/24/2014
On Learning Where To Look
Current automatic vision systems face two major challenges: scalability ...
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12/20/2013
Multi-GPU Training of ConvNets
In this work we evaluate different approaches to parallelize computation...
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12/16/2013
Learning Factored Representations in a Deep Mixture of Experts
Mixtures of Experts combine the outputs of several "expert" networks, ea...
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11/21/2013
PANDA: Pose Aligned Networks for Deep Attribute Modeling
We propose a method for inferring human attributes (such as gender, hair...
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06/03/2013
Predicting Parameters in Deep Learning
We demonstrate that there is significant redundancy in the parameterizat...
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12/29/2011
Building high-level features using large scale unsupervised learning
We consider the problem of building high-level, class-specific feature d...
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10/18/2010