Search Results for author: Nan Du

Found 38 papers, 8 papers with code

Mixture-of-Experts with Expert Choice Routing

no code implementations18 Feb 2022 Yanqi Zhou, Tao Lei, Hanxiao Liu, Nan Du, Yanping Huang, Vincent Zhao, Andrew Dai, Zhifeng Chen, Quoc Le, James Laudon

Prior work allocates a fixed number of experts to each token using a top-k function regardless of the relative importance of different tokens.

ST-MoE: Designing Stable and Transferable Sparse Expert Models

1 code implementation17 Feb 2022 Barret Zoph, Irwan Bello, Sameer Kumar, Nan Du, Yanping Huang, Jeff Dean, Noam Shazeer, William Fedus

But advancing the state-of-the-art across a broad set of natural language tasks has been hindered by training instabilities and uncertain quality during fine-tuning.

Natural Language Processing Question Answering +1

Finetuned Language Models Are Zero-Shot Learners

2 code implementations ICLR 2022 Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, Quoc V. Le

We show that instruction tuning -- finetuning language models on a collection of tasks described via instructions -- substantially improves zero-shot performance on unseen tasks.

 Ranked #1 on Common Sense Reasoning on ReCoRD (Accuracy metric)

Common Sense Reasoning Language Modelling +5

R2D2: Relational Text Decoding with Transformers

no code implementations10 May 2021 Aryan Arbabi, Mingqiu Wang, Laurent El Shafey, Nan Du, Izhak Shafran

The other side ignores the sequential nature of the text by representing them as fixed-dimensional vectors and apply graph neural networks.

Data-to-Text Generation

Learning to Select Best Forecast Tasks for Clinical Outcome Prediction

no code implementations NeurIPS 2020 Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M. Dai

The paradigm of pretraining' from a set of relevant auxiliary tasks and thenfinetuning' on a target task has been successfully applied in many different domains.

Meta-Learning

Deep Physiological State Space Model for Clinical Forecasting

no code implementations4 Dec 2019 Yuan Xue, Denny Zhou, Nan Du, Andrew Dai, Zhen Xu, Kun Zhang, Claire Cui

Clinical forecasting based on electronic medical records (EMR) can uncover the temporal correlations between patients' conditions and outcomes from sequences of longitudinal clinical measurements.

Learning to Infer Entities, Properties and their Relations from Clinical Conversations

no code implementations IJCNLP 2019 Nan Du, Mingqiu Wang, Linh Tran, Gang Li, Izhak Shafran

Recently we proposed the Span Attribute Tagging (SAT) Model (Du et al., 2019) to infer clinical entities (e. g., symptoms) and their properties (e. g., duration).

Relation Extraction

Multi-Grained Named Entity Recognition

1 code implementation ACL 2019 Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip Yu

This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totally nested.

Multi-Grained Named Entity Recognition named-entity-recognition +3

Extracting Symptoms and their Status from Clinical Conversations

no code implementations ACL 2019 Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yu-Hui Chen, Izhak Shafran

This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status.

Entity Synonym Discovery via Multipiece Bilateral Context Matching

1 code implementation31 Dec 2018 Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu

Being able to automatically discover synonymous entities in an open-world setting benefits various tasks such as entity disambiguation or knowledge graph canonicalization.

Entity Disambiguation

Joint Slot Filling and Intent Detection via Capsule Neural Networks

3 code implementations ACL 2019 Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu

Being able to recognize words as slots and detect the intent of an utterance has been a keen issue in natural language understanding.

Intent Detection Natural Language Understanding +1

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering

2 code implementations6 Dec 2018 Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Nan Du, Wei Fan, Kai Lei, Ying Shen

Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.

Answer Selection Knowledge Base Question Answering +1

Statistical Robust Chinese Remainder Theorem for Multiple Numbers: Wrapped Gaussian Mixture Model

no code implementations28 Nov 2018 Nan Du, Zhikang Wang, Hanshen Xiao

Generalized Chinese Remainder Theorem (CRT) has been shown to be a powerful approach to solve the ambiguity resolution problem.

Learning Temporal Point Processes via Reinforcement Learning

no code implementations NeurIPS 2018 Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song

Social goods, such as healthcare, smart city, and information networks, often produce ordered event data in continuous time.

Point Processes reinforcement-learning

Finding Similar Medical Questions from Question Answering Websites

no code implementations14 Oct 2018 Yaliang Li, Liuyi Yao, Nan Du, Jing Gao, Qi Li, Chuishi Meng, Chenwei Zhang, Wei Fan

Patients who have medical information demands tend to post questions about their health conditions on these crowdsourced Q&A websites and get answers from other users.

Question Answering

MedTruth: A Semi-supervised Approach to Discovering Knowledge Condition Information from Multi-Source Medical Data

no code implementations27 Sep 2018 Yang Deng, Yaliang Li, Ying Shen, Nan Du, Wei Fan, Min Yang, Kai Lei

In the light of these challenges, we propose a new truth discovery method, MedTruth, for medical knowledge condition discovery, which incorporates prior source quality information into the source reliability estimation procedure, and also utilizes the knowledge triple information for trustworthy information computation.

Databases

SynonymNet: Multi-context Bilateral Matching for Entity Synonyms

no code implementations27 Sep 2018 Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu

Being able to automatically discover synonymous entities from a large free-text corpus has transformative effects on structured knowledge discovery.

AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy

2 code implementations15 Aug 2018 Wentao Zhu, Yufang Huang, Liang Zeng, Xuming Chen, Yong liu, Zhen Qian, Nan Du, Wei Fan, Xiaohui Xie

Methods: Our deep learning model, called AnatomyNet, segments OARs from head and neck CT images in an end-to-end fashion, receiving whole-volume HaN CT images as input and generating masks of all OARs of interest in one shot.

3D Medical Imaging Segmentation

Cooperative Denoising for Distantly Supervised Relation Extraction

no code implementations COLING 2018 Kai Lei, Daoyuan Chen, Yaliang Li, Nan Du, Min Yang, Wei Fan, Ying Shen

Distantly supervised relation extraction greatly reduces human efforts in extracting relational facts from unstructured texts.

Denoising Information Retrieval +3

Knowledge as A Bridge: Improving Cross-domain Answer Selection with External Knowledge

no code implementations COLING 2018 Yang Deng, Ying Shen, Min Yang, Yaliang Li, Nan Du, Wei Fan, Kai Lei

In this paper, we propose Knowledge-aware Attentive Network (KAN), a transfer learning framework for cross-domain answer selection, which uses the knowledge base as a bridge to enable knowledge transfer from the source domain to the target domains.

Answer Selection Information Retrieval +2

Generative Discovery of Relational Medical Entity Pairs

no code implementations ICLR 2018 Chenwei Zhang, Yaliang Li, Nan Du, Wei Fan, Philip S. Yu

Online healthcare services can provide the general public with ubiquitous access to medical knowledge and reduce the information access cost for both individuals and societies.

Bringing Semantic Structures to User Intent Detection in Online Medical Queries

no code implementations22 Oct 2017 Chenwei Zhang, Nan Du, Wei Fan, Yaliang Li, Chun-Ta Lu, Philip S. Yu

The healthcare status, complex medical information needs of patients are expressed diversely and implicitly in their medical text queries.

Intent Detection Multi-Task Learning

Time-Dependent Representation for Neural Event Sequence Prediction

no code implementations ICLR 2018 Yang Li, Nan Du, Samy Bengio

Because neural sequence models such as RNN are more amenable for handling token-like input, we propose two methods for time-dependent event representation, based on the intuition on how time is tokenized in everyday life and previous work on embedding contextualization.

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks

no code implementations8 Dec 2016 Nan Du, YIngyu Liang, Maria-Florina Balcan, Manuel Gomez-Rodriguez, Hongyuan Zha, Le Song

A typical viral marketing model identifies influential users in a social network to maximize a single product adoption assuming unlimited user attention, campaign budgets, and time.

Variational hybridization and transformation for large inaccurate noisy-or networks

no code implementations20 May 2016 Yusheng Xie, Nan Du, Wei Fan, Jing Zhai, Weicheng Zhu

In addition, we propose a transformation ranking algorithm that is very stable to large variances in network prior probabilities, a common issue that arises in medical applications of Bayesian networks.

Variational Inference

Time-Sensitive Recommendation From Recurrent User Activities

no code implementations NeurIPS 2015 Nan Du, Yichen Wang, Niao He, Jimeng Sun, Le Song

By making personalized suggestions, a recommender system is playing a crucial role in improving the engagement of users in modern web-services.

Point Processes Recommendation Systems

Shaping Social Activity by Incentivizing Users

no code implementations NeurIPS 2014 Mehrdad Farajtabar, Nan Du, Manuel Gomez Rodriguez, Isabel Valera, Hongyuan Zha, Le Song

Events in an online social network can be categorized roughly into endogenous events, where users just respond to the actions of their neighbors within the network, or exogenous events, where users take actions due to drives external to the network.

Learning Time-Varying Coverage Functions

no code implementations NeurIPS 2014 Nan Du, YIngyu Liang, Maria-Florina F. Balcan, Le Song

Coverage functions are an important class of discrete functions that capture laws of diminishing returns.

Budgeted Influence Maximization for Multiple Products

no code implementations8 Dec 2013 Nan Du, YIngyu Liang, Maria Florina Balcan, Le Song

The typical algorithmic problem in viral marketing aims to identify a set of influential users in a social network, who, when convinced to adopt a product, shall influence other users in the network and trigger a large cascade of adoptions.

Combinatorial Optimization

Scalable Influence Estimation in Continuous-Time Diffusion Networks

no code implementations NeurIPS 2013 Nan Du, Le Song, Manuel Gomez Rodriguez, Hongyuan Zha

If a piece of information is released from a media site, can it spread, in 1 month, to a million web pages?

Learning Networks of Heterogeneous Influence

no code implementations NeurIPS 2012 Nan Du, Le Song, Ming Yuan, Alex J. Smola

However, the underlying transmission networks are often hidden and incomplete, and we observe only the time stamps when cascades of events happen.

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