Erich Elsen | DeepAI

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∙ 06/17/2022

The State of Sparse Training in Deep Reinforcement Learning

The use of sparse neural networks has seen rapid growth in recent years,...

0 Laura Graesser, et al. ∙

∙ 03/29/2022

Training Compute-Optimal Large Language Models

We investigate the optimal model size and number of tokens for training ...

6 Jordan Hoffmann, et al. ∙

∙ 02/02/2022

Unified Scaling Laws for Routed Language Models

The performance of a language model has been shown to be effectively mod...

2 Aidan Clark, et al. ∙

∙ 12/13/2021

Step-unrolled Denoising Autoencoders for Text Generation

In this paper we propose a new generative model of text, Step-unrolled D...

0 Nikolay Savinov, et al. ∙

∙ 12/08/2021

Improving language models by retrieving from trillions of tokens

We enhance auto-regressive language models by conditioning on document c...

8 Sebastian Borgeaud, et al. ∙

∙ 06/07/2021

Top-KAST: Top-K Always Sparse Training

Sparse neural networks are becoming increasingly important as the field ...

0 Siddhant M. Jayakumar, et al. ∙

∙ 06/26/2020

On the Generalization Benefit of Noise in Stochastic Gradient Descent

It has long been argued that minibatch stochastic gradient descent can g...

12 Samuel L. Smith, et al. ∙

∙ 06/18/2020

Sparse GPU Kernels for Deep Learning

Scientific workloads have traditionally exploited high levels of sparsit...

11 Trevor Gale, et al. ∙

∙ 06/12/2020

AlgebraNets

Neural networks have historically been built layerwise from the set of f...

0 Jordan Hoffmann, et al. ∙

∙ 06/12/2020

A Practical Sparse Approximation for Real Time Recurrent Learning

Current methods for training recurrent neural networks are based on back...

4 Jacob Menick, et al. ∙

∙ 06/05/2020

End-to-End Adversarial Text-to-Speech

Modern text-to-speech synthesis pipelines typically involve multiple pro...

0 Jeff Donahue, et al. ∙

∙ 11/25/2019

Rigging the Lottery: Making All Tickets Winners

Sparse neural networks have been shown to be more parameter and compute ...

0 Utku Evci, et al. ∙

∙ 11/21/2019

Fast Sparse ConvNets

Historically, the pursuit of efficient inference has been one of the dri...

0 Erich Elsen, et al. ∙

∙ 09/25/2019

High Fidelity Speech Synthesis with Adversarial Networks

Generative adversarial networks have seen rapid development in recent ye...

0 Mikołaj Bińkowski, et al. ∙

∙ 06/25/2019

The Difficulty of Training Sparse Neural Networks

We investigate the difficulties of training sparse neural networks and m...

5 Utku Evci, et al. ∙

∙ 06/07/2019

Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods

In this work we show that Evolution Strategies (ES) are a viable method ...

9 Karel Lenc, et al. ∙

∙ 02/25/2019

The State of Sparsity in Deep Neural Networks

We rigorously evaluate three state-of-the-art techniques for inducing sp...

0 Trevor Gale, et al. ∙

∙ 10/29/2018

Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset

Generating musical audio directly with neural networks is notoriously di...

0 Curtis Hawthorne, et al. ∙

∙ 02/23/2018

Efficient Neural Audio Synthesis

Sequential models achieve state-of-the-art results in audio, visual and ...

0 Nal Kalchbrenner, et al. ∙

∙ 11/28/2017

Parallel WaveNet: Fast High-Fidelity Speech Synthesis

The recently-developed WaveNet architecture is the current state of the ...

0 Aaron van den Oord, et al. ∙

∙ 10/30/2017

Onsets and Frames: Dual-Objective Piano Transcription

We consider the problem of transcribing polyphonic piano music with an e...

0 Curtis Hawthorne, et al. ∙

∙ 10/10/2017

Mixed Precision Training

Deep neural networks have enabled progress in a wide variety of applicat...

0 Paulius Micikevicius, et al. ∙

∙ 04/17/2017

Exploring Sparsity in Recurrent Neural Networks

Recurrent Neural Networks (RNN) are widely used to solve a variety of pr...

0 Sharan Narang, et al. ∙

∙ 07/15/2016

DSD: Dense-Sparse-Dense Training for Deep Neural Networks

Modern deep neural networks have a large number of parameters, making th...

0 Song Han, et al. ∙

∙ 12/08/2015

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

We show that an end-to-end deep learning approach can be used to recogni...

0 Dario Amodei, et al. ∙

∙ 12/17/2014

Deep Speech: Scaling up end-to-end speech recognition

We present a state-of-the-art speech recognition system developed using ...

0 Awni Hannun, et al. ∙

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