Chin-Chia Michael Yeh

Orcid: 0000-0002-9807-2963

According to our database1, Chin-Chia Michael Yeh authored at least 85 papers between 2012 and 2024.

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Bibliography

2024
Visual Analytics for Efficient Image Exploration and User-Guided Image Captioning.
IEEE Trans. Vis. Comput. Graph., June, 2024

VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations.
ACM Trans. Interact. Intell. Syst., March, 2024

Matrix Profile for Anomaly Detection on Multidimensional Time Series.
CoRR, 2024

Preserving Individuality while Following the Crowd: Understanding the Role of User Taste and Crowd Wisdom in Online Product Rating Prediction.
CoRR, 2024

Random Projection Layers for Multidimensional Time Series Forecasting.
CoRR, 2024

Has Your Pretrained Model Improved? A Multi-head Posterior Based Approach.
CoRR, 2024

Masked Graph Transformer for Large-Scale Recommendation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Analysis of Causal and Non-Causal Convolution Networks for Time Series Classification.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

PromptLandscape: Guiding Prompts Exploration and Analysis with Visualization.
Proceedings of the 17th IEEE Pacific Visualization Conference, 2024

RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Revealing the Power of Masked Autoencoders in Traffic Forecasting.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
How Does Attention Work in Vision Transformers? A Visual Analytics Attempt.
IEEE Trans. Vis. Comput. Graph., June, 2023

Learning-From-Disagreement: A Model Comparison and Visual Analytics Framework.
IEEE Trans. Vis. Comput. Graph., 2023

Revealing the Power of Spatial-Temporal Masked Autoencoders in Multivariate Time Series Forecasting.
CoRR, 2023

PDT: Pretrained Dual Transformers for Time-aware Bipartite Graphs.
CoRR, 2023

Sharpness-Aware Graph Collaborative Filtering.
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Hessian-aware Quantized Node Embeddings for Recommendation.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Adversarial Collaborative Filtering for Free.
Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Spatial-Temporal Graph Sandwich Transformer for Traffic Flow Forecasting.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track, 2023

EmbeddingTree: Hierarchical Exploration of Entity Features in Embedding.
Proceedings of the 16th IEEE Pacific Visualization Symposium, 2023

Probabilistic Masked Attention Networks for Explainable Sequential Recommendation.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Multitask Learning for Time Series Data with 2D Convolution.
Proceedings of the International Conference on Machine Learning and Applications, 2023

Interpretable Debiasing of Vectorized Language Representations with Iterative Orthogonalization.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

FATA-Trans: Field And Time-Aware Transformer for Sequential Tabular Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Toward a Foundation Model for Time Series Data.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

An Efficient Content-based Time Series Retrieval System.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Spatial-Temporal Graph Boosting Networks: Enhancing Spatial-Temporal Graph Neural Networks via Gradient Boosting.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Sketching Multidimensional Time Series for Fast Discord Mining.
Proceedings of the IEEE International Conference on Big Data, 2023

Ego-Network Transformer for Subsequence Classification in Time Series Data.
Proceedings of the IEEE International Conference on Big Data, 2023

Temporal Treasure Hunt: Content-based Time Series Retrieval System for Discovering Insights.
Proceedings of the IEEE International Conference on Big Data, 2023

Time Series Synthesis Using the Matrix Profile for Anonymization.
Proceedings of the IEEE International Conference on Big Data, 2023

2022
Visual Analytics for RNN-Based Deep Reinforcement Learning.
IEEE Trans. Vis. Comput. Graph., 2022

Graph Neural Transport Networks with Non-local Attentions for Recommender Systems.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Error-bounded Approximate Time Series Joins using Compact Dictionary Representations of Time Series.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Denoising Self-Attentive Sequential Recommendation.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

PerfSig: Extracting Performance Bug Signatures via Multi-modality Causal Analysis.
Proceedings of the 44th IEEE/ACM 44th International Conference on Software Engineering, 2022

Normalization of Language Embeddings for Cross-Lingual Alignment.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Matrix Profile XXVII: A Novel Distance Measure for Comparing Long Time Series.
Proceedings of the IEEE International Conference on Knowledge Graph, 2022

Learning from Disagreement for Event Detection.
Proceedings of the IEEE International Conference on Big Data, 2022

Dynamic Graph Node Classification via Time Augmentation.
Proceedings of the IEEE International Conference on Big Data, 2022

Quantized Wasserstein Procrustes Alignment of Word Embedding Spaces.
Proceedings of the 15th biennial conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), 2022

2021
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations.
CoRR, 2021

Structured Graph Convolutional Networks with Stochastic Masks for Recommender Systems.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Mining Anomalies in Subspaces of High-Dimensional Time Series for Financial Transactional Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021

An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Constrained Non-Affine Alignment of Embeddings.
Proceedings of the IEEE International Conference on Data Mining, 2021

Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020
The Swiss army knife of time series data mining: ten useful things you can do with the matrix profile and ten lines of code.
Data Min. Knowl. Discov., 2020

Multi-stream RNN for Merchant Transaction Prediction.
CoRR, 2020

Multi-future Merchant Transaction Prediction.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Towards a Flexible Embedding Learning Framework.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

Matrix Profile XVII: Indexing the Matrix Profile to Allow Arbitrary Range Queries.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Merchant Category Identification Using Credit Card Transactions.
Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019
Fast Similarity Matrix Profile for Music Analysis and Exploration.
IEEE Trans. Multim., 2019

The UCR time series archive.
IEEE CAA J. Autom. Sinica, 2019

Correction to: Domain agnostic online semantic segmentation for multi-dimensional time series.
Data Min. Knowl. Discov., 2019

Domain agnostic online semantic segmentation for multi-dimensional time series.
Data Min. Knowl. Discov., 2019

Online Amnestic DTW to allow Real-Time Golden Batch Monitoring.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018
Towards a Near Universal Time Series Data Mining Tool: Introducing the Matrix Profile.
PhD thesis, 2018

Exploiting a novel algorithm and GPUs to break the ten quadrillion pairwise comparisons barrier for time series motifs and joins.
Knowl. Inf. Syst., 2018

Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile.
Data Min. Knowl. Discov., 2018

Towards a Near Universal Time Series Data Mining Tool: Introducing the Matrix Profile.
CoRR, 2018

Representation Learning by Reconstructing Neighborhoods.
CoRR, 2018

Time Series Classification to Improve Poultry Welfare.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Matrix Profile XI: SCRIMP++: Time Series Motif Discovery at Interactive Speeds.
Proceedings of the IEEE International Conference on Data Mining, 2018

2017
Matrix Profile IV: Using Weakly Labeled Time Series to Predict Outcomes.
Proc. VLDB Endow., 2017

Matrix Profile VI: Meaningful Multidimensional Motif Discovery.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Matrix Profile VIII: Domain Agnostic Online Semantic Segmentation at Superhuman Performance Levels.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
SiMPle: Assessing Music Similarity Using Subsequences Joins.
Proceedings of the 17th International Society for Music Information Retrieval Conference, 2016

Matrix Profile II: Exploiting a Novel Algorithm and GPUs to Break the One Hundred Million Barrier for Time Series Motifs and Joins.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Matrix Profile I: All Pairs Similarity Joins for Time Series: A Unifying View That Includes Motifs, Discords and Shapelets.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Matrix Profile III: The Matrix Profile Allows Visualization of Salient Subsequences in Massive Time Series.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2014
A Systematic Evaluation of the Bag-of-Frames Representation for Music Information Retrieval.
IEEE Trans. Multim., 2014

AWtoolbox: Characterizing Audio Information Using Audio Words.
Proceedings of the ACM International Conference on Multimedia, MM '14, Orlando, FL, USA, November 03, 2014

Improving music auto-tagging by intra-song instance bagging.
Proceedings of the IEEE International Conference on Acoustics, 2014

Modified lasso screening for audio word-based music classification using large-scale dictionary.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Dual-layer bag-of-frames model for music genre classification.
Proceedings of the IEEE International Conference on Acoustics, 2013

Towards a more efficient sparse coding based audio-word feature extraction system.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2013

2012
Bilingual analysis of song lyrics and audio words.
Proceedings of the 20th ACM Multimedia Conference, MM '12, Nara, Japan, October 29, 2012

Supervised dictionary learning for music genre classification.
Proceedings of the International Conference on Multimedia Retrieval, 2012


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