b'Haoran Zhang'

research

∙ 08/08/2023

A Dataset and Analysis of Open-Source Machine Learning Products

Machine learning (ML) components are increasingly incorporated into soft...

0 Nadia Nahar, et al. ∙

research

∙ 07/25/2023

Continuous Time Evidential Distributions for Irregular Time Series

Prevalent in many real-world settings such as healthcare, irregular time...

0 Taylor W. Killian, et al. ∙

research

∙ 07/09/2023

Enhancing Building Semantic Segmentation Accuracy with Super Resolution and Deep Learning: Investigating the Impact of Spatial Resolution on Various Datasets

The development of remote sensing and deep learning techniques has enabl...

0 Zhiling Guo, et al. ∙

research

∙ 06/24/2023

Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling

In recent years, single-frame image super-resolution (SR) has become mor...

0 Zhiling Guo, et al. ∙

research

∙ 06/15/2023

OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection

Out-of-Distribution (OOD) detection is critical for the reliable operati...

0 Jingyang Zhang, et al. ∙

research

∙ 06/07/2023

Cross-attention learning enables real-time nonuniform rotational distortion correction in OCT

Nonuniform rotational distortion (NURD) correction is vital for endoscop...

0 Haoran Zhang, et al. ∙

research

∙ 05/06/2023

Annotation-efficient learning for OCT segmentation

Deep learning has been successfully applied to OCT segmentation. However...

0 Haoran Zhang, et al. ∙

research

∙ 03/31/2023

A Meta-Summary of Challenges in Building Products with ML Components – Collecting Experiences from 4758+ Practitioners

Incorporating machine learning (ML) components into software products ra...

0 Nadia Nahar, et al. ∙

research

∙ 03/02/2023

Identifiability and Consistent Estimation of the Gaussian Chain Graph Model

The chain graph model admits both undirected and directed edges in one g...

0 Ruixuan Zhao, et al. ∙

research

∙ 02/23/2023

Change is Hard: A Closer Look at Subpopulation Shift

Machine learning models often perform poorly on subgroups that are under...

0 Yuzhe Yang, et al. ∙

research

∙ 02/02/2023

SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling

Time series analysis is widely used in extensive areas. Recently, to red...

12 Jiaxiang Dong, et al. ∙

research

∙ 11/15/2022

Adaptive Embedding for Temporal Network

Temporal network has become ubiquitous with the rise of online social pl...

0 Haoran Zhang, et al. ∙

research

∙ 10/19/2022

"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts

Performance of machine learning models may differ between training and d...

0 Haoran Zhang, et al. ∙

research

∙ 07/30/2022

Efficient estimation and inference for the signed β-model in directed signed networks

This paper proposes a novel signed β-model for directed signed network, ...

0 Haoran Zhang, et al. ∙

research

∙ 07/08/2022

Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomalies

Signed networks are frequently observed in real life with additional sig...

0 Haoran Zhang, et al. ∙

research

∙ 05/06/2022

The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations

Machine learning models in safety-critical settings like healthcare are ...

0 Aparna Balagopalan, et al. ∙

research

∙ 04/04/2022

Target Confusion in End-to-end Speaker Extraction: Analysis and Approaches

Recently, end-to-end speaker extraction has attracted increasing attenti...

0 Zifeng Zhao, et al. ∙

research

∙ 03/23/2022

Improving the Fairness of Chest X-ray Classifiers

Deep learning models have reached or surpassed human-level performance i...

0 Haoran Zhang, et al. ∙

research

∙ 02/23/2022

Reinforcement Learning from Demonstrations by Novel Interactive Expert and Application to Automatic Berthing Control Systems for Unmanned Surface Vessel

In this paper, two novel practical methods of Reinforcement Learning fro...

0 Haoran Zhang, et al. ∙

research

∙ 12/02/2021

Learning Optimal Predictive Checklists

Checklists are simple decision aids that are often used to promote safet...

5 Haoran Zhang, et al. ∙

research

∙ 11/21/2021

Differentiable Projection for Constrained Deep Learning

Deep neural networks (DNNs) have achieved extraordinary performance in s...

0 Dou Huang, et al. ∙

research

∙ 10/28/2021

OneFlow: Redesign the Distributed Deep Learning Framework from Scratch

Deep learning frameworks such as TensorFlow and PyTorch provide a produc...

0 Jinhui Yuan, et al. ∙

research

∙ 09/17/2021

An open GPS trajectory dataset and benchmark for travel mode detection

Travel mode detection has been a hot topic in the field of GPS trajector...

0 Jinyu Chen, et al. ∙

research

∙ 08/27/2021

Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing

Machine learning models achieve state-of-the-art performance on many sup...

0 Sindhu C. M. Gowda, et al. ∙

research

∙ 08/27/2021

A comparison of approaches to improve worst-case predictive model performance over patient subpopulations

Predictive models for clinical outcomes that are accurate on average in ...

0 Stephen R. Pfohl, et al. ∙

research

∙ 07/25/2021

Invariance-based Multi-Clustering of Latent Space Embeddings for Equivariant Learning

Variational Autoencoders (VAEs) have been shown to be remarkably effecti...

7 Chandrajit Bajaj, et al. ∙

research

∙ 07/21/2021

Reading Race: AI Recognises Patient's Racial Identity In Medical Images

Background: In medical imaging, prior studies have demonstrated disparat...

17 Imon Banerjee, et al. ∙

research

∙ 04/27/2021

Mobsimilarity: Vector Graph Optimization for Mobility Tableau Comparison

Human mobility similarity comparison plays a critical role in mobility e...

0 Yuhao Yao, et al. ∙

research

∙ 04/24/2021

Effective Metagraph-based Life Pattern Clustering with Big Human Mobility Data

Life pattern clustering is essential for abstracting the groups' charact...

0 Wenjing Li, et al. ∙

research

∙ 04/14/2021

Small World Model for scaling up prediction result based on SEIR model

Data-driven epidemic simulation helps better policymaking. Compared with...

0 Guixu Lin, et al. ∙

research

∙ 03/20/2021

An Empirical Framework for Domain Generalization in Clinical Settings

Clinical machine learning models experience significantly degraded perfo...

13 Haoran Zhang, et al. ∙

research

∙ 12/13/2020

A Dual-Store Structure for Knowledge Graphs

To effectively manage increasing knowledge graphs in various domains, a ...

0 Zhixin Qi, et al. ∙

research

∙ 12/11/2020

Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method

Machine learning models have been successfully used in many scientific a...

0 Yuntian Chen, et al. ∙

research

∙ 11/23/2020

An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare

Reinforcement Learning (RL) has recently been applied to sequential esti...

23 Taylor W. Killian, et al. ∙

research

∙ 10/13/2020

Fault-tolerant and Transactional Stateful Serverless Workflows (extended version)

This paper introduces Beldi, a library and runtime system for writing an...

0 Haoran Zhang, et al. ∙

research

∙ 09/16/2020

Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction

Joint entity and relation extraction aims to extract relation triplets f...

0 Haoran Zhang, et al. ∙

research

∙ 09/03/2020

Unfolding-Model-Based Visualization: Theory, Method and Applications

Multidimensional unfolding methods are widely used for visualizing item ...

0 Yunxiao Chen, et al. ∙

research

∙ 08/10/2020

A Note on Likelihood Ratio Tests for Models with Latent Variables

The likelihood ratio test (LRT) is widely used for comparing the relativ...

0 Yunxiao Chen, et al. ∙

research

∙ 08/04/2020

Automated Topical Component Extraction Using Neural Network Attention Scores from Source-based Essay Scoring

While automated essay scoring (AES) can reliably grade essays at scale, ...

0 Haoran Zhang, et al. ∙

research

∙ 07/01/2020

COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation

To combat COVID-19, both clinicians and scientists need to digest the va...

18 Qingyun Wang, et al. ∙

research

∙ 03/11/2020

Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings

In this work, we examine the extent to which embeddings may encode margi...

0 Haoran Zhang, et al. ∙

research

∙ 11/24/2019

CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning

Joint extraction of entities and relations has received significant atte...

0 Daojian Zeng, et al. ∙

research

∙ 08/06/2019

Co-Attention Based Neural Network for Source-Dependent Essay Scoring

This paper presents an investigation of using a co-attention based neura...

1 Haoran Zhang, et al. ∙

research

∙ 08/06/2019

eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing

Writing a good essay typically involves students revising an initial pap...

4 Haoran Zhang, et al. ∙

research

∙ 08/06/2019

Word Embedding for Response-To-Text Assessment of Evidence

Manually grading the Response to Text Assessment (RTA) is labor intensiv...

1 Haoran Zhang, et al. ∙

research

∙ 07/19/2019

A Note on Exploratory Item Factor Analysis by Singular Value Decomposition

In this note, we revisit a singular value decomposition (SVD) based algo...

0 Haoran Zhang, et al. ∙

research

∙ 12/13/2018

Dose-response modeling in high-throughput cancer drug screenings: A case study with recommendations for practitioners

Personalized cancer treatments based on the molecular profile of a patie...

0 Wesley Tansey, et al. ∙

research

∙ 11/01/2018

The Holdout Randomization Test: Principled and Easy Black Box Feature Selection

We consider the problem of feature selection using black box predictive ...

0 Wesley Tansey, et al. ∙

Haoran Zhang

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