Yan Zheng

Orcid: 0000-0003-4422-9889

Affiliations:
  • Visa Research, Palo Alto, CA, USA
  • University of Utah, School of Computing, Salt Lake City, UT, USA (PhD 2017)


According to our database1, Yan Zheng authored at least 51 papers between 2013 and 2024.

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Timeline

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Bibliography

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

PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies.
CoRR, 2024

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

Compressing and interpreting word embeddings with latent space regularization and interactive semantics probing.
Inf. Vis., 2023

Sketching Multidimensional Time Series for Fast Discord Mining.
CoRR, 2023

Time Series Synthesis Using the Matrix Profile for Anonymization.
CoRR, 2023

Ego-Network Transformer for Subsequence Classification in Time Series Data.
CoRR, 2023

Temporal Treasure Hunt: Content-based Time Series Retrieval System for Discovering Insights.
CoRR, 2023

Visual Analytics for Efficient Image Exploration and User-Guided Image Captioning.
CoRR, 2023

Multitask Learning for Time Series Data with 2D Convolution.
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

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

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
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

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

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
Visualization of Big Spatial Data Using Coresets for Kernel Density Estimates.
IEEE Trans. Big Data, 2021

VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations.
CoRR, 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
Towards a Flexible Embedding Learning Framework.
Proceedings of the 20th International Conference on Data Mining Workshops, 2020

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

2019
Feature Detection and Attenuation in Embeddings.
CoRR, 2019

2018
Fully convolutional structured LSTM networks for joint 4D medical image segmentation.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017
Algorithms and Coresets for Large-Scale Kernel Smoothing.
PhD thesis, 2017

Coresets for Kernel Regression.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2015
L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Geometric Inference on Kernel Density Estimates.
Proceedings of the 31st International Symposium on Computational Geometry, 2015

Subsampling in Smoothed Range Spaces.
Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2013
Quality and efficiency for kernel density estimates in large data.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013


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