Tie-Yan Liu

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Microsoft

Principal Research Manager at Microsoft Research Asia

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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Adaptive Regret of Convex and Smooth Functions

We investigate online convex optimization in changing environments, and ...
04/26/2019 ∙ by Lijun Zhang, et al. ∙ 10 ∙ 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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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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A Game-theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search

Sponsored search is an important monetization channel for search engines...
06/03/2014 ∙ by Di He, et al. ∙ 0 ∙ share

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Generalization Analysis for Game-Theoretic Machine Learning

For Internet applications like sponsored search, cautions need to be tak...
10/09/2014 ∙ by Haifang Li, et al. ∙ 0 ∙ share

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Generalized Second Price Auction with Probabilistic Broad Match

Generalized Second Price (GSP) auctions are widely used by search engine...
04/15/2014 ∙ by Wei Chen, et al. ∙ 0 ∙ share

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Convergence Analysis of Distributed Stochastic Gradient Descent with Shuffling

When using stochastic gradient descent to solve large-scale machine lear...
09/29/2017 ∙ by Qi Meng, et al. ∙ 0 ∙ share

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Ensemble-Compression: A New Method for Parallel Training of Deep Neural Networks

Parallelization framework has become a necessity to speed up the trainin...
06/02/2016 ∙ by Shizhao Sun, et al. ∙ 0 ∙ share

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Word-Entity Duet Representations for Document Ranking

This paper presents a word-entity duet framework for utilizing knowledge...
06/20/2017 ∙ by Chenyan Xiong, et al. ∙ 0 ∙ share

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Large-Scale Low-Rank Matrix Learning with Nonconvex Regularizers

Low-rank modeling has many important applications in computer vision and...
08/01/2017 ∙ by Quanming Yao, et al. ∙ 0 ∙ share

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Dual Supervised Learning

Many supervised learning tasks are emerged in dual forms, e.g., English-...
07/03/2017 ∙ by Yingce Xia, et al. ∙ 0 ∙ share

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Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks

Click prediction is one of the fundamental problems in sponsored search....
04/23/2014 ∙ by Yuyu Zhang, et al. ∙ 0 ∙ share

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Randomized Mechanisms for Selling Reserved Instances in Cloud

Selling reserved instances (or virtual machines) is a basic service in c...
11/22/2016 ∙ by Jia Zhang, et al. ∙ 0 ∙ share

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Learning What Data to Learn

Machine learning is essentially the sciences of playing with data. An ad...
02/28/2017 ∙ by Yang Fan, et al. ∙ 0 ∙ share

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Generalization Error Bounds for Optimization Algorithms via Stability

Many machine learning tasks can be formulated as Regularized Empirical R...
09/27/2016 ∙ by Qi Meng, et al. ∙ 0 ∙ share

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LightLDA: Big Topic Models on Modest Compute Clusters

When building large-scale machine learning (ML) programs, such as big to...
12/04/2014 ∙ by Jinhui Yuan, et al. ∙ 0 ∙ share

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A Theoretical Analysis of NDCG Type Ranking Measures

A central problem in ranking is to design a ranking measure for evaluati...
04/24/2013 ∙ by Yining Wang, et al. ∙ 0 ∙ share

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Adversarial Neural Machine Translation

In this paper, we study a new learning paradigm for Neural Machine Trans...
04/20/2017 ∙ by Lijun Wu, et al. ∙ 0 ∙ share

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Dual Learning for Machine Translation

While neural machine translation (NMT) is making good progress in the pa...
11/01/2016 ∙ by Yingce Xia, et al. ∙ 0 ∙ share

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LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

Recurrent neural networks (RNNs) have achieved state-of-the-art performa...
10/31/2016 ∙ by Xiang Li, et al. ∙ 0 ∙ share

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Sentence Level Recurrent Topic Model: Letting Topics Speak for Themselves

We propose Sentence Level Recurrent Topic Model (SLRTM), a new topic mod...
04/07/2016 ∙ by Fei Tian, et al. ∙ 0 ∙ share

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Optimizing Neural Networks in the Equivalent Class Space

It has been widely observed that many activation functions and pooling m...
02/11/2018 ∙ by Qi Meng, et al. ∙ 0 ∙ share

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Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation

Stochastic gradient descent (SGD) has achieved great success in training...
02/27/2018 ∙ by Huishuai Zhang, et al. ∙ 0 ∙ share

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Achieving Human Parity on Automatic Chinese to English News Translation

Machine translation has made rapid advances in recent years. Millions of...
03/15/2018 ∙ by Hany Hassan, et al. ∙ 0 ∙ share

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Conditional Image-to-Image Translation

Image-to-image translation tasks have been widely investigated with Gene...
05/01/2018 ∙ by Jianxin Lin, et al. ∙ 0 ∙ share

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Differential Equations for Modeling Asynchronous Algorithms

Asynchronous stochastic gradient descent (ASGD) is a popular parallel op...
05/08/2018 ∙ by Li He, et al. ∙ 0 ∙ share

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Learning to Teach

Teaching plays a very important role in our society, by spreading human ...
05/09/2018 ∙ by Yang Fan, et al. ∙ 0 ∙ share

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Dense Information Flow for Neural Machine Translation

Recently, neural machine translation has achieved remarkable progress by...
06/03/2018 ∙ by Yanyao Shen, et al. ∙ 0 ∙ share

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Double Path Networks for Sequence to Sequence Learning

Encoder-decoder based Sequence to Sequence learning (S2S) has made remar...
06/13/2018 ∙ by Kaitao Song, et al. ∙ 0 ∙ share

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Towards Binary-Valued Gates for Robust LSTM Training

Long Short-Term Memory (LSTM) is one of the most widely used recurrent s...
06/08/2018 ∙ by Zhuohan Li, et al. ∙ 0 ∙ share

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Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling

This paper presents a Kernel Entity Salience Model (KESM) that improves ...
05/03/2018 ∙ by Chenyan Xiong, et al. ∙ 0 ∙ share

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Neural Architecture Optimization

Automatic neural architecture design has shown its potential in discover...
08/22/2018 ∙ by Renqian Luo, et al. ∙ 0 ∙ share

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Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter

Neural machine translation usually adopts autoregressive models and suff...
09/01/2018 ∙ by Lijun Wu, et al. ∙ 0 ∙ share

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A Study of Reinforcement Learning for Neural Machine Translation

Recent studies have shown that reinforcement learning (RL) is an effecti...
08/27/2018 ∙ by Lijun Wu, et al. ∙ 0 ∙ share

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Capacity Control of ReLU Neural Networks by Basis-path Norm

Recently, path norm was proposed as a new capacity measure for neural ne...
09/19/2018 ∙ by Shuxin Zheng, et al. ∙ 0 ∙ share

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Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting

In reinforcement learning (RL) , one of the key components is policy eva...
09/21/2018 ∙ by Yue Wang, et al. ∙ 0 ∙ share

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FRAGE: Frequency-Agnostic Word Representation

Continuous word representation (aka word embedding) is a basic building ...
09/18/2018 ∙ by Chengyue Gong, et al. ∙ 0 ∙ share

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Target Transfer Q-Learning and Its Convergence Analysis

Q-learning is one of the most popular methods in Reinforcement Learning ...
09/21/2018 ∙ by Yue Wang, et al. ∙ 0 ∙ share

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Learning to Teach with Dynamic Loss Functions

Teaching is critical to human society: it is with teaching that prospect...
10/29/2018 ∙ by Lijun Wu, et al. ∙ 0 ∙ share

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Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks

Recurrent Neural Networks (RNNs) have been widely used in processing nat...
11/13/2018 ∙ by Chang Xu, et al. ∙ 0 ∙ share

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Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input

Non-autoregressive translation (NAT) models, which remove the dependence...
12/23/2018 ∙ by Junliang Guo, et al. ∙ 0 ∙ share

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Reinforcement Learning with Dynamic Boltzmann Softmax Updates

Value function estimation is an important task in reinforcement learning...
03/14/2019 ∙ by Ling Pan, et al. ∙ 0 ∙ share

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Positively Scale-Invariant Flatness of ReLU Neural Networks

It was empirically confirmed by Keskar et al.SharpMinima that flatter mi...
03/06/2019 ∙ by Mingyang Yi, et al. ∙ 0 ∙ share

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Non-Autoregressive Machine Translation with Auxiliary Regularization

As a new neural machine translation approach, Non-Autoregressive machine...
02/22/2019 ∙ by Yiren Wang, et al. ∙ 0 ∙ share

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Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network

It has been proved that gradient descent converges linearly to the globa...
03/17/2019 ∙ by Huishuai Zhang, 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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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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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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Tie-Yan Liu

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