Tie-Yan Liu

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Microsoft

Principal Research Manager at Microsoft Research Asia

LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition

Speech synthesis (text to speech, TTS) and recognition (automatic speech...
08/09/2020 ∙ by Jin Xu, et al. ∙ 0 ∙ share

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Taking Notes on the Fly Helps BERT Pre-training

How to make unsupervised language pre-training more efficient and less r...
08/04/2020 ∙ by Qiyu Wu, et al. ∙ 0 ∙ share

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Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary

Membership inference (MI) in machine learning decides whether a given ex...
07/21/2020 ∙ by Da Yu, et al. ∙ 11 ∙ share

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Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation

Non-autoregressive translation (NAT) achieves faster inference speed but...
07/17/2020 ∙ by Jinglin Liu, et al. ∙ 0 ∙ share

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Learning to Match Distributions for Domain Adaptation

When the training and test data are from different distributions, domain...
07/17/2020 ∙ by Chaohui Yu, et al. ∙ 11 ∙ share

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Learn to Use Future Information in Simultaneous Translation

Simultaneous neural machine translation (briefly, NMT) has attracted muc...
07/10/2020 ∙ by Xueqing Wu, et al. ∙ 0 ∙ share

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Neural Architecture Search with GBDT

Neural architecture search (NAS) with an accuracy predictor that predict...
07/09/2020 ∙ by Renqian Luo, et al. ∙ 5 ∙ share

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Learning to Teach with Deep Interactions

Machine teaching uses a meta/teacher model to guide the training of a st...
07/09/2020 ∙ by Yang Fan, et al. ∙ 0 ∙ share

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DeepSinger: Singing Voice Synthesis with Data Mined From the Web

In this paper, we develop DeepSinger, a multi-lingual multi-singer singi...
07/09/2020 ∙ by Yi Ren, et al. ∙ 0 ∙ share

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Rethinking Positional Encoding in Language Pre-training

How to explicitly encode positional information into neural networks is ...
06/28/2020 ∙ by Guolin Ke, et al. ∙ 0 ∙ share

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Rethinking the Positional Encoding in Language Pre-training

How to explicitly encode positional information into neural networks is ...
06/28/2020 ∙ by Guolin Ke, et al. ∙ 0 ∙ share

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Dynamic of Stochastic Gradient Descent with State-Dependent Noise

Stochastic gradient descent (SGD) and its variants are mainstream method...
06/24/2020 ∙ by Qi Meng, et al. ∙ 10 ∙ share

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Modeling Lost Information in Lossy Image Compression

Lossy image compression is one of the most commonly used operators for d...
06/22/2020 ∙ by Yaolong Wang, et al. ∙ 8 ∙ share

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Multi-branch Attentive Transformer

While the multi-branch architecture is one of the key ingredients to the...
06/18/2020 ∙ by Yang Fan, et al. ∙ 0 ∙ share

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UWSpeech: Speech to Speech Translation for Unwritten Languages

Existing speech to speech translation systems heavily rely on the text o...
06/14/2020 ∙ by Chen Zhang, et al. ∙ 0 ∙ share

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MC-BERT: Efficient Language Pre-Training via a Meta Controller

Pre-trained contextual representations (e.g., BERT) have become the foun...
06/10/2020 ∙ by Zhenhui Xu, et al. ∙ 0 ∙ share

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MultiSpeech: Multi-Speaker Text to Speech with Transformer

Transformer-based text to speech (TTS) model (e.g., Transformer TTS <cit...
06/08/2020 ∙ by Mingjian Chen, et al. ∙ 0 ∙ share

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FastSpeech 2: Fast and High-Quality End-to-End Text to Speech

Advanced text to speech (TTS) models such as FastSpeech can synthesize s...
06/08/2020 ∙ by Yi Ren, et al. ∙ 0 ∙ share

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Dual Learning: Theoretical Study and an Algorithmic Extension

Dual learning has been successfully applied in many machine learning app...
05/17/2020 ∙ by Zhibing Zhao, et al. ∙ 0 ∙ share

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Invertible Image Rescaling

High-resolution digital images are usually downscaled to fit various dis...
05/12/2020 ∙ by Mingqing Xiao, et al. ∙ 8 ∙ share

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SEEK: Segmented Embedding of Knowledge Graphs

In recent years, knowledge graph embedding becomes a pretty hot research...
05/02/2020 ∙ by Wentao Xu, et al. ∙ 8 ∙ share

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LightPAFF: A Two-Stage Distillation Framework for Pre-training and Fine-tuning

While pre-training and fine-tuning, e.g., BERT <cit.>, GPT-2 <cit.>, hav...
04/27/2020 ∙ by Kaitao Song, et al. ∙ 0 ∙ share

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A Study of Non-autoregressive Model for Sequence Generation

Non-autoregressive (NAR) models generate all the tokens of a sequence in...
04/22/2020 ∙ by Yi Ren, et al. ∙ 0 ∙ share

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MPNet: Masked and Permuted Pre-training for Language Understanding

BERT adopts masked language modeling (MLM) for pre-training and is one o...
04/20/2020 ∙ by Kaitao Song, et al. ∙ 0 ∙ share

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Discriminator Contrastive Divergence: Semi-Amortized Generative Modeling by Exploring Energy of the Discriminator

Generative Adversarial Networks (GANs) have shown great promise in model...
04/05/2020 ∙ by Yuxuan Song, et al. ∙ 0 ∙ share

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Suphx: Mastering Mahjong with Deep Reinforcement Learning

Artificial Intelligence (AI) has achieved great success in many domains,...
03/30/2020 ∙ by Junjie Li, et al. ∙ 0 ∙ share

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Semi-Supervised Neural Architecture Search

Neural architecture search (NAS) relies on a good controller to generate...
02/24/2020 ∙ by Renqian Luo, et al. ∙ 0 ∙ share

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Incorporating BERT into Neural Machine Translation

The recently proposed BERT has shown great power on a variety of natural...
02/17/2020 ∙ by Jinhua Zhu, et al. ∙ 0 ∙ share

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On Layer Normalization in the Transformer Architecture

The Transformer is widely used in natural language processing tasks. To ...
02/12/2020 ∙ by Ruibin Xiong, et al. ∙ 0 ∙ share

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A Study of Multilingual Neural Machine Translation

Multilingual neural machine translation (NMT) has recently been investig...
12/25/2019 ∙ by Xu Tan, et al. ∙ 0 ∙ share

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Gradient Perturbation is Underrated for Differentially Private Convex Optimization

Gradient perturbation, widely used for differentially private optimizati...
11/26/2019 ∙ by Da Yu, et al. ∙ 0 ∙ share

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Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation

Non-autoregressive translation (NAT) models remove the dependence on pre...
11/20/2019 ∙ by Junliang Guo, et al. ∙ 0 ∙ share

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Microsoft Research Asia's Systems for WMT19

We Microsoft Research Asia made submissions to 11 language directions in...
11/07/2019 ∙ by Yingce Xia, et al. ∙ 0 ∙ share

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Distributional Reward Decomposition for Reinforcement Learning

Many reinforcement learning (RL) tasks have specific properties that can...
11/06/2019 ∙ by Zichuan Lin, et al. ∙ 38 ∙ share

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Hint-Based Training for Non-Autoregressive Machine Translation

Due to the unparallelizable nature of the autoregressive factorization, ...
09/15/2019 ∙ by Zhuohan Li, et al. ∙ 0 ∙ share

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Self-paced Ensemble for Highly Imbalanced Massive Data Classification

Many real-world applications reveal difficulties in learning classifiers...
09/08/2019 ∙ by Zhining Liu, et al. ∙ 1 ∙ share

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Training Effective Ensemble on Imbalanced Data by Self-paced Harmonizing Classification Hardness

Many real-world applications reveal difficulties in learning classifiers...
09/08/2019 ∙ by Zhining Liu, et al. ∙ 0 ∙ share

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Multilingual Neural Machine Translation with Language Clustering

Multilingual neural machine translation (NMT), which translates multiple...
08/25/2019 ∙ by Xu Tan, et al. ∙ 0 ∙ share

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Representation Degeneration Problem in Training Natural Language Generation Models

We study an interesting problem in training neural network-based models ...
07/28/2019 ∙ by Jun Gao, et al. ∙ 0 ∙ share

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Light Multi-segment Activation for Model Compression

Model compression has become necessary when applying neural networks (NN...
07/16/2019 ∙ by Zhenhui Xu, et al. ∙ 0 ∙ share

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Depth Growing for Neural Machine Translation

While very deep neural networks have shown effectiveness for computer vi...
07/03/2019 ∙ by Lijun Wu, et al. ∙ 0 ∙ share

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Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View

The Transformer architecture is widely used in natural language processi...
06/06/2019 ∙ by Yiping Lu, et al. ∙ 0 ∙ share

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Unsupervised Pivot Translation for Distant Languages

Unsupervised neural machine translation (NMT) has attracted a lot of att...
06/06/2019 ∙ by Yichong Leng, et al. ∙ 0 ∙ share

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Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data

Stochastic variance reduced methods have gained a lot of interest recent...
05/29/2019 ∙ by Shicong Cen, et al. ∙ 0 ∙ share

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Beyond Exponentially Discounted Sum: Automatic Learning of Return Function

In reinforcement learning, Return, which is the weighted accumulated fut...
05/28/2019 ∙ by Yufei Wang, et al. ∙ 0 ∙ share

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Learning Efficient and Effective Exploration Policies with Counterfactual Meta Policy

A fundamental issue in reinforcement learning algorithms is the balance ...
05/28/2019 ∙ by Ruihan Yang, et al. ∙ 0 ∙ share

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Soft Contextual Data Augmentation for Neural Machine Translation

While data augmentation is an important trick to boost the accuracy of d...
05/25/2019 ∙ by Jinhua Zhu, et al. ∙ 0 ∙ share

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FastSpeech: Fast, Robust and Controllable Text to Speech

Neural network based end-to-end text to speech (TTS) has significantly i...
05/22/2019 ∙ by Yi Ren, et al. ∙ 0 ∙ share

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Almost Unsupervised Text to Speech and Automatic Speech Recognition

Text to speech (TTS) and automatic speech recognition (ASR) are two dual...
05/13/2019 ∙ by Yi Ren, et al. ∙ 0 ∙ share

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MASS: Masked Sequence to Sequence Pre-training for Language Generation

Pre-training and fine-tuning, e.g., BERT, have achieved great success in...
05/07/2019 ∙ by Kaitao Song, et al. ∙ 0 ∙ share

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Tie-Yan Liu

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