Haohan Wang

Orcid: 0000-0002-1826-4069

According to our database1, Haohan Wang authored at least 114 papers between 2013 and 2024.

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Bibliography

2024
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-Noise Learning.
IEEE Trans. Pattern Anal. Mach. Intell., June, 2024

Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization.
Trans. Mach. Learn. Res., 2024

SAR Incremental Automatic Target Recognition Based on Mutual Information Maximization.
IEEE Geosci. Remote. Sens. Lett., 2024

Conflict-Aware Adversarial Training.
CoRR, 2024

DistDD: Distributed Data Distillation Aggregation through Gradient Matching.
CoRR, 2024

DS-ViT: Dual-Stream Vision Transformer for Cross-Task Distillation in Alzheimer's Early Diagnosis.
CoRR, 2024

A Quantitative Approach for Evaluating Disease Focus and Interpretability of Deep Learning Models for Alzheimer's Disease Classification.
CoRR, 2024

Quantitative Evaluation of the Saliency Map for Alzheimer's Disease Classifier with Anatomical Segmentation.
CoRR, 2024

JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models.
CoRR, 2024

GenoTEX: A Benchmark for Evaluating LLM-Based Exploration of Gene Expression Data in Alignment with Bioinformaticians.
CoRR, 2024

Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas.
CoRR, 2024

From Tissue Plane to Organ World: A Benchmark Dataset for Multimodal Biomedical Image Registration using Deep Co-Attention Networks.
CoRR, 2024

Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters.
CoRR, 2024

The Devil is in the Edges: Monocular Depth Estimation with Edge-aware Consistency Fusion.
CoRR, 2024

Approximate Nullspace Augmented Finetuning for Robust Vision Transformers.
CoRR, 2024

Towards Adversarially Robust Dataset Distillation by Curvature Regularization.
CoRR, 2024

Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation.
CoRR, 2024

Toward a Team of AI-made Scientists for Scientific Discovery from Gene Expression Data.
CoRR, 2024

GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models.
CoRR, 2024

Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks.
CoRR, 2024

MedTransformer: Accurate AD Diagnosis for 3D MRI Images through 2D Vision Transformers.
CoRR, 2024

DCAI: Data-centric Artificial Intelligence.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

A Lightweight Network for Radar Specific Emitter Identification via Differential Constellation Figure.
Proceedings of the IGARSS 2024, 2024

Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Model-Agnostic Channel Prediction with Meta Predictive Recurrent Neural Networks.
Proceedings of the IEEE International Conference on Communications Workshops, 2024

User Preferences for Icon Design Styles and Their Associations with Personality and Demographic.
Proceedings of the HCI International 2024 Posters, 2024

MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Simple Unsupervised Knowledge Distillation With Space Similarity.
Proceedings of the Computer Vision - ECCV 2024, 2024

CatchBackdoor: Backdoor Detection via Critical Trojan Neural Path Fuzzing.
Proceedings of the Computer Vision - ECCV 2024, 2024

Towards Reliable Advertising Image Generation Using Human Feedback.
Proceedings of the Computer Vision - ECCV 2024, 2024

EditShield: Protecting Unauthorized Image Editing by Instruction-Guided Diffusion Models.
Proceedings of the Computer Vision - ECCV 2024, 2024

Trustworthy and Responsible AI for Information and Knowledge Management System.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Efficient Few-Shot Classification via Contrastive Pretraining on Web Data.
IEEE Trans. Artif. Intell., June, 2023

Generate E-commerce Product Background by Integrating Category Commonality and Personalized Style.
CoRR, 2023

Dataset Distillation via the Wasserstein Metric.
CoRR, 2023

Beyond Pixels: Exploring Human-Readable SVG Generation for Simple Images with Vision Language Models.
CoRR, 2023

ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning.
CoRR, 2023

Understanding Adversarial Transferability in Federated Learning.
CoRR, 2023

Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives.
CoRR, 2023

Leveraging Large Language Models for Scalable Vector Graphics-Driven Image Understanding.
CoRR, 2023

Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Test-Time Personalization for Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Trustworthy Machine Learning: Robustness, Generalization, and Interpretability.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Optimizing the Collaboration Structure in Cross-Silo Federated Learning.
Proceedings of the International Conference on Machine Learning, 2023

Trustworthy Computing for Biomedical Challenges.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

A Sentence Speaks a Thousand Images: Domain Generalization through Distilling CLIP with Language Guidance.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Self-learning for Annotating Website Privacy Policies at Scale.
Proceedings of the 47th IEEE Annual Computers, Software, and Applications Conference, 2023

Toward Robust Diagnosis: A Contour Attention Preserving Adversarial Defense for COVID-19 Detection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Calibrated Teacher for Sparsely Annotated Object Detection.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Few-Shot Steel Surface Defect Detection.
IEEE Trans. Instrum. Meas., 2022

Kernel Mixed Model for Transcriptome Association Study.
J. Comput. Biol., 2022

Trade-offs of Linear Mixed Models in Genome-Wide Association Studies.
J. Comput. Biol., 2022

Expeditious Saliency-guided Mix-up through Random Gradient Thresholding.
CoRR, 2022

A Principled Evaluation Protocol for Comparative Investigation of the Effectiveness of DNN Classification Models on Similar-but-non-identical Datasets.
CoRR, 2022

Robustar: Interactive Toolbox Supporting Precise Data Annotation for Robust Vision Learning.
CoRR, 2022

MRCLens: an MRC Dataset Bias Detection Toolkit.
CoRR, 2022

Bear the Query in Mind: Visual Grounding with Query-conditioned Convolution.
CoRR, 2022

The Two Dimensions of Worst-case Training and the Integrated Effect for Out-of-domain Generalization.
CoRR, 2022

Toward learning human-aligned cross-domain robust models by countering misaligned features.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Gene Set Priorization Guided by Regulatory Networks with p-values through Kernel Mixed Model.
Proceedings of the Research in Computational Molecular Biology, 2022

Measure and Improve Robustness in NLP Models: A Survey.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Iterative Few-shot Semantic Segmentation from Image Label Text.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

The Two Dimensions of Worst-case Training and Their Integrated Effect for Out-of-domain Generalization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Supervised Adversarial Alignment of Single-Cell RNA-seq Data.
J. Comput. Biol., May, 2021

Toward Learning Human-aligned Cross-domain Robust Models by Countering Misaligned Features.
CoRR, 2021

Tradeoffs of Linear Mixed Models in Genome-wide Association Studies.
CoRR, 2021

Enabling the Network to Surf the Internet.
CoRR, 2021

Coupled mixed model for joint genetic analysis of complex disorders with two independently collected data sets.
BMC Bioinform., 2021

Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography.
Bioinform., 2021

Robust Contrastive Learning Using Negative Samples with Diminished Semantics.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Poly(A)-DG: A deep-learning-based domain generalization method to identify cross-species Poly(A) signal without prior knowledge from target species.
PLoS Comput. Biol., November, 2020

Squared 𝓁<sub>2</sub> Norm as Consistency Loss for Leveraging Augmented Data to Learn Robust and Invariant Representations.
CoRR, 2020

Word Shape Matters: Robust Machine Translation with Visual Embedding.
CoRR, 2020

Self-challenging Improves Cross-Domain Generalization.
Proceedings of the Computer Vision - ECCV 2020, 2020

High-Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Anomaly Detection in Road Networks Using Sliding-Window Tensor Factorization.
IEEE Trans. Intell. Transp. Syst., 2019

Discovery of Critical Nodes in Road Networks Through Mining From Vehicle Trajectories.
IEEE Trans. Intell. Transp. Syst., 2019

High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks.
CoRR, 2019

Deep mixed model for marginal epistasis detection and population stratification correction in genome-wide association studies.
BMC Bioinform., 2019

Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data.
Bioinform., 2019

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Automatic Human-like Mining and Constructing Reliable Genetic Association Database with Deep Reinforcement Learning.
Proceedings of the Biocomputing 2019: Proceedings of the Pacific Symposium, 2019

Learning Robust Global Representations by Penalizing Local Predictive Power.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Robust Representations by Projecting Superficial Statistics Out.
Proceedings of the 7th International Conference on Learning Representations, 2019

Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Deep Inductive Matrix Completion for Biomedical Interaction Prediction.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Graph-structured Sparse Mixed Models for Genetic Association with Confounding Factors Correction.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual.
Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP, 2019

What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
3-HBP: A Three-Level Hidden Bayesian Link Prediction Model in Social Networks.
IEEE Trans. Comput. Soc. Syst., 2018

Fair Deep Learning Prediction for Healthcare Applications with Confounder Filtering.
CoRR, 2018

Deep Learning for Genomics: A Concise Overview.
CoRR, 2018

GLDA-FP: Gaussian LDA Model for Forward Prediction.
Proceedings of the Big Data - BigData 2018, 2018

Heterogeneous Hi-C Data Super-resolution with a Conditional Generative Adversarial Network.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

2017
Extracting compact representation of knowledge from gene expression data for protein-protein interaction.
Int. J. Data Min. Bioinform., 2017

A Sparse Graph-Structured Lasso Mixed Model for Genetic Association with Confounding Correction.
CoRR, 2017

On the Origin of Deep Learning.
CoRR, 2017

Select-additive learning: Improving generalization in multimodal sentiment analysis.
Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017

Multiplex confounding factor correction for genomic association mapping with squared sparse linear mixed model.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

Variable selection in heterogeneous datasets: A truncated-rank sparse linear mixed model with applications to genome-wide association studies.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016
SeDMiD for Confusion Detection: Uncovering Mind State from Time Series Brain Wave Data.
CoRR, 2016

Select-Additive Learning: Improving Cross-individual Generalization in Multimodal Sentiment Analysis.
CoRR, 2016

Multiple confounders correction with regularized linear mixed effect models, with application in biological processes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016

2015
A Survey: Time Travel in Deep Learning Space: An Introduction to Deep Learning Models and How Deep Learning Models Evolved from the Initial Ideas.
CoRR, 2015

Evaluating Protein-protein Interaction Predictors with a Novel 3-Dimensional Metric.
CoRR, 2015

Evaluation of Protein-protein Interaction Predictors with Noisy Partially Labeled Data Sets.
CoRR, 2015

Learning structure in gene expression data using deep architectures, with an application to gene clustering.
Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

2014
Discovery of Important Crossroads in Road Network using Massive Taxi Trajectories.
CoRR, 2014

Multimodal Transfer Deep Learning for Audio Visual Recognition.
CoRR, 2014

2013
Behavior analysis of low-literate users of a viral speech-based telephone service.
Proceedings of the Annual Symposium on Computing for Development, 2013

Using EEG to Improve Massive Open Online Courses Feedback Interaction.
Proceedings of the Workshops at the 16th International Conference on Artificial Intelligence in Education AIED 2013, 2013


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