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Viewing Publication 1 - 100 from 222

2024

PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval ModelsWei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan. wsdm 2024: 77-86 [doi]

Temporal shuffling for defending deep action recognition models against adversarial attacksJaehui Hwang, Huan Zhang 0001, Jun Ho Choi, Cho-Jui Hsieh, Jong-Seok Lee. NN, 169:388-397, January 2024. [doi]

2023

Robust Lipschitz Bandits to Adversarial CorruptionsYue Kang 0002, Cho-Jui Hsieh, Thomas Chun Man Lee. nips 2023: [doi]

Concept Gradient: Concept-based Interpretation Without Linear AssumptionAndrew Bai, Chih-Kuan Yeh, Neil Y. C. Lin, Pradeep Kumar Ravikumar, Cho-Jui Hsieh. iclr 2023: [doi]

FINGER: Fast Inference for Graph-based Approximate Nearest Neighbor SearchPatrick H. Chen, Wei-Cheng Chang, Jyun-Yu Jiang, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh. WWW 2023: 3225-3235 [doi]

Why Does Sharpness-Aware Minimization Generalize Better Than SGD?Zixiang Chen, Junkai Zhang, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh, Quanquan Gu. nips 2023: [doi]

Symbolic Discovery of Optimization AlgorithmsXiangning Chen, Chen Liang, Da Huang, Esteban Real, Kaiyuan Wang, Hieu Pham 0001, Xuanyi Dong, Thang Luong, Cho-Jui Hsieh, Yifeng Lu, Quoc V. Le. nips 2023: [doi]

PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood AggregationEli Chien, Jiong Zhang, Cho-Jui Hsieh, Jyun-Yu Jiang, Wei-Cheng Chang, Olgica Milenkovic, Hsiang-Fu Yu. icml 2023: 5616-5630 [doi]

Scaling Up Dataset Distillation to ImageNet-1K with Constant MemoryJustin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh. icml 2023: 6565-6590 [doi]

A Computationally Efficient Sparsified Online Newton MethodDevvrit, Sai Surya Duvvuri, Rohan Anil, Vineet Gupta 0001, Cho-Jui Hsieh, Inderjit S. Dhillon. nips 2023: [doi]

Uncertainty Quantification for Extreme ClassificationJyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu. sigir 2023: 1649-1659 [doi]

Incorporating physics into data-driven computer visionAchuta Kadambi, Celso de Melo, Cho-Jui Hsieh, Mani B. Srivastava, Stefano Soatto. natmi, 5(6):572-580, June 2023. [doi]

Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution TrajectoriesLi-Cheng Lan, Huan Zhang 0001, Cho-Jui Hsieh. iclr 2023: [doi]

Fast block-wise partitioning for extreme multi-label classificationYuefeng Liang, Cho-Jui Hsieh, Thomas C. M. Lee. datamine, 37(6):2192-2215, November 2023. [doi]

Enhancing Unsupervised Semantic Parsing with Distributed Contextual RepresentationsZixuan Ling, Xiaoqing Zheng, Jianhan Xu, Jinshu Lin, Kai-Wei Chang, Cho-Jui Hsieh, Xuanjing Huang 0001. acl 2023: 11454-11465 [doi]

Stochastically Controlled Compositional Gradient for Composition ProblemsLiu Liu, Ji Liu, Cho-Jui Hsieh, Dacheng Tao. tnn, 34(2):611-622, February 2023. [doi]

Improving Adversarial Robustness to Sensitivity and Invariance Attacks with Deep Metric Learning (Student Abstract)Anaelia Ovalle, Evan Czyzycki, Cho-Jui Hsieh. AAAI 2023: 16292-16293 [doi]

NeSSA: Near-Storage Data Selection for Accelerated Machine Learning TrainingNeha Prakriya, Yu Yang, Baharan Mirzasoleiman, Cho-Jui Hsieh, Jason Cong. hotstorage 2023: 8-15 [doi]

Training Meta-Surrogate Model for Transferable Adversarial AttackYunxiao Qin, Yuanhao Xiong, Jinfeng Yi, Cho-Jui Hsieh. AAAI 2023: 9516-9524 [doi]

Effective Robustness against Natural Distribution Shifts for Models with Different Training DataZhouxing Shi, Nicholas Carlini, Ananth Balashankar, Ludwig Schmidt, Cho-Jui Hsieh, Alex Beutel, Yao Qin 0001. nips 2023: [doi]

Serving Graph Compression for Graph Neural NetworksSi Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar. iclr 2023: [doi]

Representer Point Selection for Explaining Regularized High-dimensional ModelsChe-Ping Tsai, Jiong Zhang, Hsiang-Fu Yu, Eli Chien, Cho-Jui Hsieh, Pradeep Kumar Ravikumar. icml 2023: 34469-34490 [doi]

Universality and Limitations of Prompt TuningYihan Wang, Jatin Chauhan, Wei Wang 0010, Cho-Jui Hsieh. nips 2023: [doi]

FedDM: Iterative Distribution Matching for Communication-Efficient Federated LearningYuanhao Xiong, Ruochen Wang, Minhao Cheng, Felix Yu, Cho-Jui Hsieh. cvpr 2023: 16323-16332 [doi]

Block Low-Rank Preconditioner with Shared Basis for Stochastic OptimizationJui-Nan Yen, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh. nips 2023: [doi]

Towards Robustness Certification Against Universal PerturbationsYi Zeng, Zhouxing Shi, Ming Jin 0002, Feiyang Kang, Lingjuan Lyu, Cho-Jui Hsieh, Ruoxi Jia. iclr 2023: [doi]

Build Faster with Less: A Journey to Accelerate Sparse Model Building for Semantic Matching in Product SearchJiong Zhang, Yau-Shian Wang, Wei-Cheng Chang, Wei Li, Jyun-Yu Jiang, Cho-Jui Hsieh, Hsiang-Fu Yu. CIKM 2023: 4960-4966 [doi]

2022

Robust Stochastic Linear Contextual Bandits Under Adversarial AttacksQin Ding 0002, Cho-Jui Hsieh, James Sharpnack. aistats 2022: 7111-7123 [doi]

Syndicated Bandits: A Framework for Auto Tuning Hyper-parameters in Contextual Bandit AlgorithmsQin Ding 0002, Yue Kang, Yi-Wei Liu, Thomas Chun Man Lee, Cho-Jui Hsieh, James Sharpnack. nips 2022: [doi]

When Vision Transformers Outperform ResNets without Pre-training or Strong Data AugmentationsXiangning Chen, Cho-Jui Hsieh, Boqing Gong. iclr 2022: [doi]

The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022)Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu. kdd 2022: 4858-4859 [doi]

CAT: Customized Adversarial Training for Improved RobustnessMinhao Cheng, Qi Lei, Pin-Yu Chen, Inderjit S. Dhillon, Cho-Jui Hsieh. IJCAI 2022: 673-679 [doi]

Node Feature Extraction by Self-Supervised Multi-scale Neighborhood PredictionEli Chien, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Jiong Zhang, Olgica Milenkovic, Inderjit S. Dhillon. iclr 2022: [doi]

Deep Image Destruction: Vulnerability of Deep Image-to-Image Models against Adversarial AttacksJun Ho Choi, Huan Zhang, Jun Hyuk Kim, Cho-Jui Hsieh, Jong-Seok Lee. icpr 2022: 1287-1293 [doi]

DC-BENCH: Dataset Condensation BenchmarkJustin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh. nips 2022: [doi]

ELIAS: End-to-End Learning to Index and Search in Large Output SpacesNilesh Gupta, Patrick H. Chen, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon. nips 2022: [doi]

Generalizing Few-Shot NAS with Gradient MatchingShoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng. iclr 2022: [doi]

Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label ClassificationJyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu. sigir 2022: 1870-1874 [doi]

Efficient Frameworks for Generalized Low-Rank Matrix Bandit ProblemsYue Kang, Cho-Jui Hsieh, Thomas Chun Man Lee. nips 2022: [doi]

Are AlphaZero-like Agents Robust to Adversarial Perturbations?Li-Cheng Lan, Huan Zhang 0001, Ti-Rong Wu, Meng-Yu Tsai 0001, I-Chen Wu, Cho-Jui Hsieh. nips 2022: [doi]

Local Critic Training for Model-Parallel Learning of Deep Neural NetworksHojung Lee, Cho-Jui Hsieh, Jong-Seok Lee. tnn, 33(9):4424-4436, 2022. [doi]

Concurrent Adversarial Learning for Large-Batch TrainingYong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You. iclr 2022: [doi]

Towards Efficient and Scalable Sharpness-Aware MinimizationYong Liu, Siqi Mai, Xiangning Chen, Cho-Jui Hsieh, Yang You. cvpr 2022: 12350-12360 [doi]

Random Sharpness-Aware MinimizationYong Liu, Siqi Mai, Minhao Cheng, Xiangning Chen, Cho-Jui Hsieh, Yang You. nips 2022: [doi]

Robust Text CAPTCHAs Using Adversarial ExamplesRulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh. bigdataconf 2022: 1495-1504 [doi]

On the Adversarial Robustness of Vision TransformersRulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh. tmlr, 2022, 2022. [doi]

Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound PropagationZhouxing Shi, Yihan Wang, Huan Zhang 0001, J. Zico Kolter, Cho-Jui Hsieh. nips 2022: [doi]

2.5D visual relationship detectionYu-Chuan Su, Soravit Changpinyo, Xiangning Chen, Sathish Thoppay, Cho-Jui Hsieh, Lior Shapira, Radu Soricut, Hartwig Adam, Matthew Brown, Ming-Hsuan Yang 0001, Boqing Gong. cviu, 224:103557, 2022. [doi]

On the Convergence of Certified Robust Training with Interval Bound PropagationYihan Wang, Zhouxing Shi, Quanquan Gu, Cho-Jui Hsieh. iclr 2022: [doi]

Efficient Non-Parametric Optimizer Search for Diverse TasksRuochen Wang, Yuanhao Xiong, Minhao Cheng, Cho-Jui Hsieh. nips 2022: [doi]

Extreme Zero-Shot Learning for Extreme Text ClassificationYuanhao Xiong, Wei-Cheng Chang, Cho-Jui Hsieh, Hsiang-Fu Yu, Inderjit S. Dhillon. naacl 2022: 5455-5468 [doi]

Learning to Learn with Smooth RegularizationYuanhao Xiong, Cho-Jui Hsieh. eccv 2022: 550-565 [doi]

Learning to Schedule Learning rate with Graph Neural NetworksYuanhao Xiong, Li-Cheng Lan, Xiangning Chen, Ruochen Wang, Cho-Jui Hsieh. iclr 2022: [doi]

Weight Perturbation as Defense against Adversarial Word SubstitutionsJianhan Xu, Linyang Li, Jiping Zhang, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh, Xuanjing Huang. emnlp 2022: 7054-7063 [doi]

Towards Adversarially Robust Text Classifiers by Learning to Reweight Clean ExamplesJianhan Xu, Cenyuan Zhang, Xiaoqing Zheng, Linyang Li, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang. acl 2022: 1694-1707 [doi]

On the Sensitivity and Stability of Model Interpretations in NLPFan Yin, Zhouxing Shi, Cho-Jui Hsieh, Kai-Wei Chang. acl 2022: 2631-2647 [doi]

ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty EstimationFan Yin, Yao Li, Cho-Jui Hsieh, Kai-Wei Chang. emnlp 2022: 6567-6584 [doi]

PECOS: Prediction for Enormous and Correlated Output SpacesHsiang-Fu Yu, Jiong Zhang, Wei-Cheng Chang, Jyun-Yu Jiang, Wei Li, Cho-Jui Hsieh. kdd 2022: 4848-4849 [doi]

Improving the Adversarial Robustness of NLP Models by Information BottleneckCenyuan Zhang, Xiang Zhou, Yixin Wan, Xiaoqing Zheng, Kai-Wei Chang, Cho-Jui Hsieh. acl 2022: 3588-3598 [doi]

A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU NetworksHuan Zhang, Shiqi Wang 0002, Kaidi Xu, Yihan Wang, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter. icml 2022: 26591-26604 [doi]

General Cutting Planes for Bound-Propagation-Based Neural Network VerificationHuan Zhang, Shiqi Wang, Kaidi Xu, Linyi Li, Bo Li, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter. nips 2022: [doi]

2021

An Efficient Algorithm For Generalized Linear Bandit: Online Stochastic Gradient Descent and Thompson SamplingQin Ding 0002, Cho-Jui Hsieh, James Sharpnack. aistats 2021: 1585-1593 [doi]

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Neural Network Robustness VerificationShiqi Wang 0002, Huan Zhang 0001, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter. nips 2021: 29909-29921 [doi]

Learnable Fourier Features for Multi-dimensional Spatial Positional EncodingYang Li 0058, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio. nips 2021: 15816-15829 [doi]

Overcoming Catastrophic Forgetting by Bayesian Generative RegularizationPei-Hung Chen, Wei Wei 0025, Cho-Jui Hsieh, Bo Dai. icml 2021: 1760-1770 [doi]

DRONE: Data-aware Low-rank Compression for Large NLP ModelsPatrick H. Chen, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh. nips 2021: 29321-29334 [doi]

DrNAS: Dirichlet Neural Architecture SearchXiangning Chen, Ruochen Wang, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh. iclr 2021: [doi]

Robust and Accurate Object Detection via Adversarial LearningXiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong. cvpr 2021: 16622-16631 [doi]

Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021)Pin-Yu Chen, Cho-Jui Hsieh, Bo Li, Sijia Liu. kdd 2021: 4112-4113 [doi]

Self-Progressing Robust TrainingMinhao Cheng, Pin-Yu Chen, Sijia Liu 0001, Shiyu Chang, Cho-Jui Hsieh, Payel Das. AAAI 2021: 7107-7115 [doi]

Measures and Best Practices for Responsible AISunipa Dev, Mehrnoosh Sameki, Jwala Dhamala, Cho-Jui Hsieh. kdd 2021: 4118 [doi]

Evaluations and Methods for Explanation through Robustness AnalysisCheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh. iclr 2021: [doi]

Learning to Stop: Dynamic Simulation Monte-Carlo Tree SearchLi-Cheng Lan, Ti-Rong Wu, I-Chen Wu, Cho-Jui Hsieh. AAAI 2021: 259-267 [doi]

Searching for an Effective Defender: Benchmarking Defense against Adversarial Word SubstitutionZongyi Li, Jianhan Xu, Jiehang Zeng, Linyang Li, Xiaoqing Zheng, Qi Zhang, Kai-Wei Chang, Cho-Jui Hsieh. emnlp 2021: 3137-3147 [doi]

Towards Robustness of Deep Neural Networks via RegularizationYao Li, Martin Renqiang Min, Thomas C. M. Lee, Wenchao Yu, Erik Kruus, Wei Wang, Cho-Jui Hsieh. iccv 2021: 7476-7485 [doi]

Label Disentanglement in Partition-based Extreme Multilabel ClassificationXuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon. nips 2021: 15359-15369 [doi]

Multi-Proxy Wasserstein Classifier for Image ClassificationBenlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou 0001, Cho-Jui Hsieh. AAAI 2021: 8618-8626 [doi]

DynamicViT: Efficient Vision Transformers with Dynamic Token SparsificationYongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou 0001, Cho-Jui Hsieh. nips 2021: 13937-13949 [doi]

RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object DetectionYongming Rao, Benlin Liu, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie Zhou 0001. iccv 2021: 3263-3272 [doi]

Fast Certified Robust Training with Short WarmupZhouxing Shi, Yihan Wang, Huan Zhang 0001, Jinfeng Yi, Cho-Jui Hsieh. nips 2021: 18335-18349 [doi]

RANK-NOSH: Efficient Predictor-Based Architecture Search via Non-Uniform Successive HalvingRuochen Wang, Xiangning Chen, Minhao Cheng, Xiaocheng Tang, Cho-Jui Hsieh. iccv 2021: 10357-10366 [doi]

Rethinking Architecture Selection in Differentiable NASRuochen Wang, Minhao Cheng, Xiangning Chen, Xiaocheng Tang, Cho-Jui Hsieh. iclr 2021: [doi]

Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete VerifiersKaidi Xu, Huan Zhang, Shiqi Wang 0002, Yihan Wang, Suman Jana, Xue Lin, Cho-Jui Hsieh. iclr 2021: [doi]

Communication-avoiding kernel ridge regression on parallel and distributed systemsYang You, Jingyue Huang, Cho-Jui Hsieh, Richard W. Vuduc, James Demmel. ccfthpc, 3(3):252-270, 2021. [doi]

On the Transferability of Adversarial Attacks against Neural Text ClassifierLiping Yuan, Xiaoqing Zheng, Yi Zhou, Cho-Jui Hsieh, Kai-Wei Chang. emnlp 2021: 1612-1625 [doi]

Double Perturbation: On the Robustness of Robustness and Counterfactual Bias EvaluationChong Zhang, Jieyu Zhao, Huan Zhang 0001, Kai-Wei Chang, Cho-Jui Hsieh. naacl 2021: 3899-3916 [doi]

Robust Reinforcement Learning on State Observations with Learned Optimal AdversaryHuan Zhang, Hongge Chen, Duane S. Boning, Cho-Jui Hsieh. iclr 2021: [doi]

Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood EnsembleYi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-Wei Chang, Xuanjing Huang. acl 2021: 5482-5492 [doi]

2020

Stabilizing Differentiable Architecture Search via Perturbation-based RegularizationXiangning Chen, Cho-Jui Hsieh. icml 2020: 1554-1565 [doi]

Multi-Stage Influence FunctionHongge Chen, Si Si, Yang Li 0058, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh. nips 2020: [doi]

Clustering and Constructing User Coresets to Accelerate Large-scale Top-K Recommender SystemsJyun-Yu Jiang, Patrick H. Chen, Cho-Jui Hsieh, Wei Wang 0010. WWW 2020: 2177-2187 [doi]

What Does BERT with Vision Look At?Liunian Harold Li, Mark Yatskar, Da Yin, Cho-Jui Hsieh, Kai-Wei Chang. acl 2020: 5265-5275 [doi]

Learning to Encode Position for Transformer with Continuous Dynamical ModelXuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh. icml 2020: 6327-6335 [doi]

How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE FrameworkXuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh. cvpr 2020: 279-287 [doi]

Elastic-InfoGAN: Unsupervised Disentangled Representation Learning in Class-Imbalanced DataUtkarsh Ojha, Krishna Kumar Singh, Cho-Jui Hsieh, Yong Jae Lee. nips 2020: [doi]

Learning to Learn by Zeroth-Order OracleYangjun Ruan, Yuanhao Xiong, Sashank J. Reddi, Sanjiv Kumar, Cho-Jui Hsieh. iclr 2020: [doi]

SSE-PT: Sequential Recommendation Via Personalized TransformerLiwei Wu, Shuqing Li, Cho-Jui Hsieh, James Sharpnack. recsys 2020: 328-337 [doi]

Improved Adversarial Training via Learned OptimizerYuanhao Xiong, Cho-Jui Hsieh. eccv 2020: 85-100 [doi]

Automatic Perturbation Analysis for Scalable Certified Robustness and BeyondKaidi Xu, Zhouxing Shi, Huan Zhang 0001, Yihan Wang, Kai-Wei Chang, Minlie Huang, Bhavya Kailkhura, Xue Lin, Cho-Jui Hsieh. nips 2020: [doi]

An Efficient Adversarial Attack for Tree EnsemblesChong Zhang, Huan Zhang 0001, Cho-Jui Hsieh. nips 2020: [doi]

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