Search Results for author: Tong Li

Found 23 papers, 7 papers with code

DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction

no code implementations14 Aug 2022 Yinfeng Li, Chen Gao, Quanming Yao, Tong Li, Depeng Jin, Yong Li

In particular, we first unify the fine-grained user similarity and the complex matching between user preferences and spatiotemporal activity into a heterogeneous hypergraph.

Enhancing Collaborative Filtering Recommender with Prompt-Based Sentiment Analysis

1 code implementation19 Jul 2022 Elliot Dang, Zheyuan Hu, Tong Li

We build the recommenders on the Amazon US Reviews dataset, and tune the pretrained BERT and RoBERTa with the traditional fine-tuned paradigm as well as the new prompt-based learning paradigm.

Collaborative Filtering Sentiment Analysis

Medical Scientific Table-to-Text Generation with Human-in-the-Loop under the Data Sparsity Constraint

no code implementations24 May 2022 Heng-Yi Wu, Jingqing Zhang, Julia Ive, Tong Li, Vibhor Gupta, Bingyuan Chen, Yike Guo

Structured (tabular) data in the preclinical and clinical domains contains valuable information about individuals and an efficient table-to-text summarization system can drastically reduce manual efforts to condense this data into reports.

Data Augmentation Table-to-Text Generation +1

A Scalable Workflow to Build Machine Learning Classifiers with Clinician-in-the-Loop to Identify Patients in Specific Diseases

no code implementations18 May 2022 Jingqing Zhang, Atri Sharma, Luis Bolanos, Tong Li, Ashwani Tanwar, Vibhor Gupta, Yike Guo

This paper proposes a scalable workflow which leverages both structured data and unstructured textual notes from EHRs with techniques including NLP, AutoML and Clinician-in-the-Loop mechanism to build machine learning classifiers to identify patients at scale with given diseases, especially those who might currently be miscoded or missed by ICD codes.

AutoML

Algorithms for Adaptive Experiments that Trade-off Statistical Analysis with Reward: Combining Uniform Random Assignment and Reward Maximization

no code implementations15 Dec 2021 Jacob Nogas, Tong Li, Fernando J. Yanez, Arghavan Modiri, Nina Deliu, Ben Prystawski, Sofia S. Villar, Anna Rafferty, Joseph J. Williams

TS PostDiff takes a Bayesian approach to mixing TS and UR: the probability a participant is assigned using UR allocation is the posterior probability that the difference between two arms is `small' (below a certain threshold), allowing for more UR exploration when there is little or no reward to be gained.

Nonlinear Approaches to Intergenerational Income Mobility allowing for Measurement Error

no code implementations20 Jul 2021 Brantly Callaway, Tong Li, Irina Murtazashvili

This paper considers nonlinear measures of intergenerational income mobility such as (i) the effect of parents' permanent income on the entire distribution of child's permanent income, (ii) transition matrices, and (iii) rank-rank correlations when observed annual incomes are treated as measured-with-error versions of permanent incomes.

Two Sample Unconditional Quantile Effect

no code implementations20 May 2021 Atsushi Inoue, Tong Li, Qi Xu

This paper proposes a new framework to evaluate unconditional quantile effects (UQE) in a data combination model.

Policy Evaluation during a Pandemic

1 code implementation14 May 2021 Brantly Callaway, Tong Li

National and local governments have implemented a large number of policies, particularly non-pharmaceutical interventions, in response to the Covid-19 pandemic.

Epidemiology

Self-Adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images

no code implementations7 May 2021 Yiming Bao, Jun Wang, Tong Li, Linyan Wang, Jianwei Xu, Juan Ye, Dahong Qian

Specifically, the encoder of a DL model that is pre-trained on the source domain is used to initialize the encoder of a reconstruction model.

Domain Adaptation

Microscopic origin of reflection-asymmetric nuclear shapes

no code implementations11 Dec 2020 Mengzhi Chen, Tong Li, Jacek Dobaczewski, Witold Nazarewicz

Background: The presence of nuclear ground states with stable reflection-asymmetric shapes is supported by rich experimental evidence.

Nuclear Theory

Document-aligned Japanese-English Conversation Parallel Corpus

1 code implementation WMT (EMNLP) 2020 Matīss Rikters, Ryokan Ri, Tong Li, Toshiaki Nakazawa

Sentence-level (SL) machine translation (MT) has reached acceptable quality for many high-resourced languages, but not document-level (DL) MT, which is difficult to 1) train with little amount of DL data; and 2) evaluate, as the main methods and data sets focus on SL evaluation.

Machine Translation Translation

C-Learning: Horizon-Aware Cumulative Accessibility Estimation

1 code implementation ICLR 2021 Panteha Naderian, Gabriel Loaiza-Ganem, Harry J. Braviner, Anthony L. Caterini, Jesse C. Cresswell, Tong Li, Animesh Garg

In order to address these limitations, we introduce the concept of cumulative accessibility functions, which measure the reachability of a goal from a given state within a specified horizon.

Continuous Control Motion Planning

Designing the Business Conversation Corpus

1 code implementation WS 2019 Matīss Rikters, Ryokan Ri, Tong Li, Toshiaki Nakazawa

While the progress of machine translation of written text has come far in the past several years thanks to the increasing availability of parallel corpora and corpora-based training technologies, automatic translation of spoken text and dialogues remains challenging even for modern systems.

 Ranked #1 on Machine Translation on Business Scene Dialogue JA-EN (using extra training data)

Machine Translation Translation

Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records

no code implementations1 Aug 2020 Jiatu Shi, Huaxiu Yao, Xian Wu, Tong Li, Zedong Lin, Tengfei Wang, Binqiang Zhao

The goal is to facilitate the learning process in the target segments by leveraging the learned knowledge from data-sufficient source segments.

Meta-Learning

Evaluating Policies Early in a Pandemic: Bounding Policy Effects with Nonrandomly Missing Data

no code implementations19 May 2020 Brantly Callaway, Tong Li

Our approach results in (generally informative) bounds on the effect of the policy on actual cases and in point identification of the effect of the policy on other outcomes.

Urban Anomaly Analytics: Description, Detection, and Prediction

no code implementations25 Apr 2020 Mingyang Zhang, Tong Li, Yue Yu, Yong Li, Pan Hui, Yu Zheng

Urban anomalies may result in loss of life or property if not handled properly.

Edge Intelligence: Architectures, Challenges, and Applications

no code implementations26 Mar 2020 Dianlei Xu, Tong Li, Yong Li, Xiang Su, Sasu Tarkoma, Tao Jiang, Jon Crowcroft, Pan Hui

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence.

On the Optimality of Gaussian Kernel Based Nonparametric Tests against Smooth Alternatives

no code implementations7 Sep 2019 Tong Li, Ming Yuan

In addition, our analysis also pinpoints the importance of choosing a diverging scaling parameter when using Gaussian kernels and suggests a data-driven choice of the scaling parameter that yields tests optimal, up to an iterated logarithmic factor, over a wide range of smooth alternatives.

Cellular Controlled Delay TCP (C2TCP)

1 code implementation7 Jul 2018 Soheil Abbasloo, Tong Li, Yang Xu, H. Jonathan Chao

To cope with these challenges, we present C2TCP, a flexible end-to-end solution targeting interactive applications requiring high throughput and low delay in cellular networks.

Networking and Internet Architecture

On the Optimality of Kernel-Embedding Based Goodness-of-Fit Tests

no code implementations24 Sep 2017 Krishnakumar Balasubramanian, Tong Li, Ming Yuan

The reproducing kernel Hilbert space (RKHS) embedding of distributions offers a general and flexible framework for testing problems in arbitrary domains and has attracted considerable amount of attention in recent years.

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