Yanjun Qi

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 99

Top Venues

CoRR

ICLR (Workshop)

AISTATS

AAAI

Publications

Xi Fang, Weijie Xu, Fiona Anting Tan, Jiani Zhang, Ziqing Hu, Yanjun Qi, Scott Nickleach, Diego Socolinsky, Srinivasan H. Sengamedu, Christos Faloutsos
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding - A Survey. CoRR (2024)
Dmitriy Bespalov, Sourav Bhabesh, Yi Xiang, Liutong Zhou, Yanjun Qi
Towards Building a Robust Toxicity Predictor. CoRR (2024)
Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Zhenqiang Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John C. Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek
Securing the Future of GenAI: Policy and Technology. IACR Cryptol. ePrint Arch. 2024 (2024)
Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John C. Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek
Securing the Future of GenAI: Policy and Technology. CoRR (2024)
Tong Wang, Ninad Kulkarni, Yanjun Qi
Less is More for Improving Automatic Evaluation of Factual Consistency. CoRR (2024)
Xi Fang, Weijie Xu, Fiona Anting Tan, Ziqing Hu, Jiani Zhang, Yanjun Qi, Srinivasan H. Sengamedu, Christos Faloutsos
Large Language Models (LLMs) on Tabular Data: Prediction, Generation, and Understanding - A Survey. Trans. Mach. Learn. Res. 2024 (2024)
Aman Shrivastava, Yanjun Qi, Vicente Ordonez
Estimating and Maximizing Mutual Information for Knowledge Distillation. CVPR Workshops (2023)
Hanyu Liu, Chengyuan Cai, Yanjun Qi
Expanding Scope: Adapting English Adversarial Attacks to Chinese. CoRR (2023)
Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi
Improving Interpretability via Explicit Word Interaction Graph Layer. CoRR (2023)
Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava, Zhe Wang, Yangfeng Ji, Yanjun Qi
Improving Interpretability via Explicit Word Interaction Graph Layer. AAAI (2023)
Dmitriy Bespalov, Sourav Bhabesh, Yi Xiang, Liutong Zhou, Yanjun Qi
Towards Building a Robust Toxicity Predictor. ACL (industry) (2023)
Zifan Xu, Haozhu Wang, Dmitriy Bespalov, Peter Stone, Yanjun Qi
Latent Skill Discovery for Chain-of-Thought Reasoning. CoRR (2023)
Zhe Wang, Jake Grigsby, Yanjun Qi
PGrad: Learning Principal Gradients For Domain Generalization. CoRR (2023)
Zhe Wang, Jake Grigsby, Yanjun Qi
PGrad: Learning Principal Gradients For Domain Generalization. ICLR (2023)
Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi
Launchpad: Learning to Schedule Using Offline and Online RL Methods. CoRR (2022)
Arshdeep Sekhon, Zhe Wang, Yanjun Qi
Beyond Data Samples: Aligning Differential Networks Estimation with Scientific Knowledge. AISTATS (2022)
Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi
ST-MAML : A stochastic-task based method for task-heterogeneous meta-learning. UAI (2022)
Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi
RARE: Renewable Energy Aware Resource Management in Datacenters. JSSPP (2022)
Vanamala Venkataswamy, Jake Grigsby, Andrew Grimshaw, Yanjun Qi
RARE: Renewable Energy Aware Resource Management in Datacenters. CoRR (2022)
Arshdeep Sekhon, Yangfeng Ji, Matthew B. Dwyer, Yanjun Qi
White-box Testing of NLP models with Mask Neuron Coverage. CoRR (2022)
Paola Cascante-Bonilla, Leonid Karlinsky, James Seale Smith, Yanjun Qi, Vicente Ordonez
On the Transferability of Visual Features in Generalized Zero-Shot Learning. CoRR (2022)
In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey
Forecasting Cloud Application Workloads With CloudInsight for Predictive Resource Management. IEEE Trans. Cloud Comput. 10 (3) (2022)
Arshdeep Sekhon, Yangfeng Ji, Matthew B. Dwyer, Yanjun Qi
White-box Testing of NLP models with Mask Neuron Coverage. NAACL-HLT (Findings) (2022)
Zhe Wang, Jake Grigsby, Arshdeep Sekhon, Yanjun Qi
ST-MAML: A Stochastic-Task based Method for Task-Heterogeneous Meta-Learning. CoRR (2021)
Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon, Yangfeng Ji, Yanjun Qi
Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing. CoRR (2021)
Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi
General Multi-Label Image Classification With Transformers. CVPR (2021)
Jake Grigsby, Yanjun Qi
A Closer Look at Advantage-Filtered Behavioral Cloning in High-Noise Datasets. CoRR (2021)
Sanchit Sinha, Hanjie Chen, Arshdeep Sekhon, Yangfeng Ji, Yanjun Qi
Perturbing Inputs for Fragile Interpretations in Deep Natural Language Processing. BlackboxNLP@EMNLP (2021)
Jin Yong Yoo, Yanjun Qi
Towards Improving Adversarial Training of NLP Models. EMNLP (Findings) (2021)
Jake Grigsby, Zhe Wang, Yanjun Qi
Long-Range Transformers for Dynamic Spatiotemporal Forecasting. CoRR (2021)
Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, Vicente Ordonez
Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning. AAAI (2021)
Aman Shrivastava, Yanjun Qi, Vicente Ordonez
Estimating and Maximizing Mutual Information for Knowledge Distillation. CoRR (2021)
Jin Yong Yoo, Yanjun Qi
Towards Improving Adversarial Training of NLP Models. CoRR (2021)
Paola Cascante-Bonilla, Arshdeep Sekhon, Yanjun Qi, Vicente Ordonez
Evolving Image Compositions for Feature Representation Learning. CoRR (2021)
Paola Cascante-Bonilla, Arshdeep Sekhon, Yanjun Qi, Vicente Ordonez
Evolving Image Compositions for Feature Representation Learning. BMVC (2021)
Arshdeep Sekhon, Zhe Wang, Yanjun Qi
Relate and Predict: Structure-Aware Prediction with Jointly Optimized Neural DAG. CoRR (2021)
Jake Grigsby, Jin Yong Yoo, Yanjun Qi
Towards Automatic Actor-Critic Solutions to Continuous Control. CoRR (2021)
Jack Lanchantin, Tom Weingarten, Arshdeep Sekhon, Clint Miller, Yanjun Qi
Transfer learning for predicting virus-host protein interactions for novel virus sequences. BCB (2021)
John X. Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, Yanjun Qi
Reevaluating Adversarial Examples in Natural Language. CoRR (2020)
Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, Vicente Ordonez
Curriculum Labeling: Self-paced Pseudo-Labeling for Semi-Supervised Learning. CoRR (2020)
Jack Lanchantin, Tianlu Wang, Vicente Ordonez, Yanjun Qi
General Multi-label Image Classification with Transformers. CoRR (2020)
John X. Morris, Eli Lifland, Jin Yong Yoo, Yanjun Qi
TextAttack: A Framework for Adversarial Attacks in Natural Language Processing. CoRR (2020)
Jake Grigsby, Yanjun Qi
Measuring Visual Generalization in Continuous Control from Pixels. CoRR (2020)
Arshdeep Sekhon, Beilun Wang, Zhe Wang, Yanjun Qi
Differential Network Learning Beyond Data Samples. CoRR (2020)
Jin Yong Yoo, John X. Morris, Eli Lifland, Yanjun Qi
Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples. CoRR (2020)
John X. Morris, Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, Yanjun Qi
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP. EMNLP (Demos) (2020)
John X. Morris, Jin Yong Yoo, Yanjun Qi
TextAttack: Lessons learned in designing Python frameworks for NLP. CoRR (2020)
Jin Yong Yoo, John X. Morris, Eli Lifland, Yanjun Qi
Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples. BlackboxNLP@EMNLP (2020)
John X. Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, Yanjun Qi
Reevaluating Adversarial Examples in Natural Language. EMNLP (Findings) (2020)
Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi
Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (5) (2019)
Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi
Neural Message Passing for Multi-Label Classification. CoRR (2019)
Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi
Neural Message Passing for Multi-label Classification. ECML/PKDD (2) (2019)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. AISTATS (2018)
Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi
DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications. CoRR (2018)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. CoRR (2018)
Ji Gao, Jack Lanchantin, Mary Lou Soffa, Yanjun Qi
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. CoRR (2018)
Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi
DeepDiff: DEEP-learning for predicting DIFFerential gene expression from histone modifications. Bioinform. 34 (17) (2018)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. ICML (2018)
Weilin Xu, David Evans, Yanjun Qi
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks. NDSS (2018)
Yanjun Qi
ACM-BCB'18 Tutorial: Making Deep Learning Understandable for Analyzing Sequential Data about Gene Regulation. BCB (2018)
Ji Gao, Jack Lanchantin, Mary Lou Soffa, Yanjun Qi
Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. IEEE Symposium on Security and Privacy Workshops (2018)
In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey
CloudInsight: Utilizing a Council of Experts to Predict Future Cloud Application Workloads. IEEE CLOUD (2018)
Weilin Xu, David Evans, Yanjun Qi
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks. CoRR (2017)
Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. CoRR (2017)
Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi
GaKCo: A Fast Gapped k-mer String Kernel Using Counting. ECML/PKDD (1) (2017)
Ritambhara Singh, Jack Lanchantin, Arshdeep Sekhon, Yanjun Qi
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. NIPS (2017)
Beilun Wang, Ji Gao, Yanjun Qi
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. AISTATS (2017)
Muthuraman Chidambaram, Yanjun Qi
Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently. CoRR (2017)
Andrew P. Norton, Yanjun Qi
Adversarial-Playground: A Visualization Suite for Adversarial Sample Generation. CoRR (2017)
Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi
Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. PSB (2017)
Beilun Wang, Arshdeep Sekhon, Yanjun Qi
Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. CoRR (2017)
Ji Gao, Beilun Wang, Zeming Lin, Weilin Xu, Yanjun Qi
DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. ICLR (Workshop) (2017)
Ji Gao, Beilun Wang, Yanjun Qi
DeepMask: Masking DNN Models for robustness against adversarial samples. CoRR (2017)
Andrew P. Norton, Yanjun Qi
Adversarial-Playground: A Visualization Suite Showing How Adversarial Examples Fool Deep Learning. CoRR (2017)
Jack Lanchantin, Ritambhara Singh, Yanjun Qi
Memory Matching Networks for Genomic Sequence Classification. ICLR (Workshop) (2017)
Andrew P. Norton, Yanjun Qi
Adversarial-Playground: A visualization suite showing how adversarial examples fool deep learning. VizSEC (2017)
Beilun Wang, Ji Gao, Yanjun Qi
A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples. ICLR (Workshop) (2017)
Chandan Singh, Beilun Wang, Yanjun Qi
A Constrained, Weighted-L1 Minimization Approach for Joint Discovery of Heterogeneous Neural Connectivity Graphs. CoRR (2017)
Beilun Wang, Ritambhara Singh, Yanjun Qi
A constrained $$\ell $$ ℓ 1 minimization approach for estimating multiple sparse Gaussian or nonparanormal graphical models. Mach. Learn. 106 (9-10) (2017)
Jack Lanchantin, Arshdeep Sekhon, Ritambhara Singh, Yanjun Qi
Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification. CoRR (2017)
Beilun Wang, Ji Gao, Yanjun Qi
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. CoRR (2017)
Ritambhara Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, Yanjun Qi
GaKCo: a Fast GApped k-mer string Kernel using COunting. CoRR (2017)
Weilin Xu, David Evans, Yanjun Qi
Feature Squeezing Mitigates and Detects Carlini/Wagner Adversarial Examples. CoRR (2017)
Jack Lanchantin, Ritambhara Singh, Yanjun Qi
Memory Matching Networks for Genomic Sequence Classification. CoRR (2017)
Beilun Wang, Ritambhara Singh, Yanjun Qi
A constrained L1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models. CoRR (2016)
Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi
Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. CoRR (2016)
Jack Lanchantin, Ritambhara Singh, Zeming Lin, Yanjun Qi
Deep Motif: Visualizing Genomic Sequence Classifications. CoRR (2016)
Feiyu Xiong, Moshe Kam, Leonid Hrebien, Beilun Wang, Yanjun Qi
Kernelized Information-Theoretic Metric Learning for Cancer Diagnosis Using High-Dimensional Molecular Profiling Data. ACM Trans. Knowl. Discov. Data 10 (4) (2016)
Beilun Wang, Ji Gao, Yanjun Qi
A Theoretical Framework for Robustness of (Deep) Classifiers Under Adversarial Noise. CoRR (2016)
Weilin Xu, Yanjun Qi, David Evans
Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers. NDSS (2016)
Jiaqi Gong, Philip Asare, Yanjun Qi, John C. Lach
Piecewise Linear Dynamical Model for Action Clustering from Real-World Deployments of Inertial Body Sensors. IEEE Trans. Affect. Comput. 7 (3) (2016)
Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi
DeepChrome: deep-learning for predicting gene expression from histone modifications. Bioinform. 32 (17) (2016)
Ritambhara Singh, Yanjun Qi
Character based String Kernels for Bio-Entity Relation Detection. BioNLP@ACL (2016)
Zeming Lin, Jack Lanchantin, Yanjun Qi
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction. AAAI (2016)
Zeming Lin, Jack Lanchantin, Yanjun Qi
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-based Protein Structure Prediction. CoRR (2016)
Jiaqi Gong, Yanjun Qi, Myla D. Goldman, John C. Lach
Causality Analysis of Inertial Body Sensors for Multiple Sclerosis Diagnostic Enhancement. IEEE J. Biomed. Health Informatics 20 (5) (2016)
In Kee Kim, Wei Wang, Yanjun Qi, Marty Humphrey
Empirical Evaluation of Workload Forecasting Techniques for Predictive Cloud Resource Scaling. CLOUD (2016)
Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi
Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction. CoRR (2016)
Ritambhara Singh, Jack Lanchantin, Gabriel Robins, Yanjun Qi
DeepChrome: Deep-learning for predicting gene expression from histone modifications. CoRR (2016)
Oznur Tastan, Yanjun Qi, Jaime G. Carbonell, Judith Klein-Seetharaman
Refining Literature Curated Protein Interactions Using Expert Opinions. Pacific Symposium on Biocomputing (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yanjun Qi