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08/08/2023
A Dataset and Analysis of Open-Source Machine Learning Products
Machine learning (ML) components are increasingly incorporated into soft...
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07/25/2023
Continuous Time Evidential Distributions for Irregular Time Series
Prevalent in many real-world settings such as healthcare, irregular time...
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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...
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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...
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06/15/2023
OpenOOD v1.5: Enhanced Benchmark for Out-of-Distribution Detection
Out-of-Distribution (OOD) detection is critical for the reliable operati...
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06/07/2023
Cross-attention learning enables real-time nonuniform rotational distortion correction in OCT
Nonuniform rotational distortion (NURD) correction is vital for endoscop...
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05/06/2023
Annotation-efficient learning for OCT segmentation
Deep learning has been successfully applied to OCT segmentation. However...
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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...
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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...
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02/23/2023
Change is Hard: A Closer Look at Subpopulation Shift
Machine learning models often perform poorly on subgroups that are under...
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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...
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11/15/2022
Adaptive Embedding for Temporal Network
Temporal network has become ubiquitous with the rise of online social pl...
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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...
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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, ...
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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...
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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 ...
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04/04/2022
Target Confusion in End-to-end Speaker Extraction: Analysis and Approaches
Recently, end-to-end speaker extraction has attracted increasing attenti...
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03/23/2022
Improving the Fairness of Chest X-ray Classifiers
Deep learning models have reached or surpassed human-level performance i...
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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...
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12/02/2021
Learning Optimal Predictive Checklists
Checklists are simple decision aids that are often used to promote safet...
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11/21/2021
Differentiable Projection for Constrained Deep Learning
Deep neural networks (DNNs) have achieved extraordinary performance in s...
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10/28/2021
OneFlow: Redesign the Distributed Deep Learning Framework from Scratch
Deep learning frameworks such as TensorFlow and PyTorch provide a produc...
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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...
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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...
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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 ...
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07/25/2021
Invariance-based Multi-Clustering of Latent Space Embeddings for Equivariant Learning
Variational Autoencoders (VAEs) have been shown to be remarkably effecti...
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07/21/2021
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Background: In medical imaging, prior studies have demonstrated disparat...
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04/27/2021
Mobsimilarity: Vector Graph Optimization for Mobility Tableau Comparison
Human mobility similarity comparison plays a critical role in mobility e...
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04/24/2021
Effective Metagraph-based Life Pattern Clustering with Big Human Mobility Data
Life pattern clustering is essential for abstracting the groups' charact...
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04/14/2021
Small World Model for scaling up prediction result based on SEIR model
Data-driven epidemic simulation helps better policymaking. Compared with...
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03/20/2021
An Empirical Framework for Domain Generalization in Clinical Settings
Clinical machine learning models experience significantly degraded perfo...
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12/13/2020
A Dual-Store Structure for Knowledge Graphs
To effectively manage increasing knowledge graphs in various domains, a ...
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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...
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11/23/2020
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
Reinforcement Learning (RL) has recently been applied to sequential esti...
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10/13/2020
Fault-tolerant and Transactional Stateful Serverless Workflows (extended version)
This paper introduces Beldi, a library and runtime system for writing an...
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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...
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09/03/2020
Unfolding-Model-Based Visualization: Theory, Method and Applications
Multidimensional unfolding methods are widely used for visualizing item ...
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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...
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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, ...
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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...
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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...
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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...
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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...
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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...
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08/06/2019
Word Embedding for Response-To-Text Assessment of Evidence
Manually grading the Response to Text Assessment (RTA) is labor intensiv...
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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...
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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...
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11/01/2018