Igor Gitman | DeepAI

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∙ 06/27/2023

Confidence-based Ensembles of End-to-End Speech Recognition Models

The number of end-to-end speech recognition models grows every year. The...

0 Igor Gitman, et al. ∙

∙ 03/18/2023

Powerful and Extensible WFST Framework for RNN-Transducer Losses

This paper presents a framework based on Weighted Finite-State Transduce...

0 Aleksandr Laptev, et al. ∙

∙ 10/30/2019

Understanding the Role of Momentum in Stochastic Gradient Methods

The use of momentum in stochastic gradient methods has become a widespre...

0 Igor Gitman, et al. ∙

∙ 05/25/2018

OpenSeq2Seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models

We present OpenSeq2Seq -- an open-source toolkit for training sequence-t...

0 Oleksii Kuchaiev, et al. ∙

∙ 04/28/2018

Novel Prediction Techniques Based on Clusterwise Linear Regression

In this paper we explore different regression models based on Clusterwis...

0 Igor Gitman, et al. ∙

∙ 01/09/2018

Convergence Analysis of Gradient Descent Algorithms with Proportional Updates

The rise of deep learning in recent years has brought with it increasing...

0 Igor Gitman, et al. ∙

∙ 09/24/2017

Comparison of Batch Normalization and Weight Normalization Algorithms for the Large-scale Image Classification

Batch normalization (BN) has become a de facto standard for training dee...

0 Igor Gitman, et al. ∙

∙ 08/13/2017

Large Batch Training of Convolutional Networks

A common way to speed up training of large convolutional networks is to ...

0 Yang You, et al. ∙

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