Sijia Liu
Orcid: 0009-0000-1213-6974Affiliations:
- Michigan State University, Department of Computer Science and Engineering, East Lansing, USA
- IBM Research, MIT-IBM Watson AI Lab, Cambridge, MA, USA (2018 - 2020)
- University of Michigan, Ann Arbor, MI, USA (2016 - 2017)
- Syracuse University, NY, USA (PhD 2016)
According to our database1,
Sijia Liu
authored at least 215 papers
between 2012 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Stochastic inexact augmented Lagrangian method for nonconvex expectation constrained optimization.
Comput. Optim. Appl., January, 2024
Found. Trends Priv. Secur., 2024
Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency.
CoRR, 2024
UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models.
CoRR, 2024
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark.
CoRR, 2024
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024
2023
Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations.
Proc. ACM Hum. Comput. Interact., 2023
Tracing Hyperparameter Dependencies for Model Parsing via Learnable Graph Pooling Network.
CoRR, 2023
CoRR, 2023
More Samples or More Prompt Inputs? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering.
CoRR, 2023
From Trojan Horses to Castle Walls: Unveiling Bilateral Backdoor Effects in Diffusion Models.
CoRR, 2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration.
CoRR, 2023
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation.
CoRR, 2023
To Generate or Not? Safety-Driven Unlearned Diffusion Models Are Still Easy To Generate Unsafe Images ... For Now.
CoRR, 2023
Tensor-Compressed Back-Propagation-Free Training for (Physics-Informed) Neural Networks.
CoRR, 2023
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning.
CoRR, 2023
Robust Mode Connectivity-Oriented Adversarial Defense: Enhancing Neural Network Robustness Against Diversified 𝓁<sub>p</sub> Attacks.
CoRR, 2023
Proceedings of the IEEE International Conference on Software Analysis, 2023
Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the International Conference on Machine Learning, 2023
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Exploring Diversified Adversarial Robustness in Neural Networks via Robust Mode Connectivity.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Proceedings of the 28th Asia and South Pacific Design Automation Conference, 2023
Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration.
ACM Trans. Design Autom. Electr. Syst., 2022
IEEE Trans. Neural Networks Learn. Syst., 2022
Trans. Mach. Learn. Res., 2022
Zeroth-Order SciML: Non-intrusive Integration of Scientific Software with Deep Learning.
CoRR, 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
CoRR, 2022
Artif. Intell., 2022
Proceedings of the Uncertainty in Artificial Intelligence, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
The Fourth Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2022).
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization.
Proceedings of the International Conference on Machine Learning, 2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling.
Proceedings of the International Conference on Machine Learning, 2022
Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
How unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
When Does Backdoor Attack Succeed in Image Reconstruction? A Study of Heuristics vs. Bi-Level Solution.
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Improved Linear Convergence of Training CNNs With Generalizability Guarantees: A One-Hidden-Layer Case.
IEEE Trans. Neural Networks Learn. Syst., 2021
To Supervise or Not: How to Effectively Learn Wireless Interference Management Models?
CoRR, 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks.
CoRR, 2021
On Instabilities of Conventional Multi-Coil MRI Reconstruction to Small Adverserial Perturbations.
CoRR, 2021
CoRR, 2021
To Supervise or Not to Supervise: How to Effectively Learn Wireless Interference Management Models?
Proceedings of the 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2021
Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search.
Proceedings of the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Third Workshop on Adversarial Learning Methods for Machine Learning and Data Mining (AdvML 2021).
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
The Lottery Tickets Hypothesis for Supervised and Self-Supervised Pre-Training in Computer Vision Models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
Instabilities in Conventional Multi-Coil MRI Reconstruction with Small Adversarial Perturbations.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications.
IEEE Signal Process. Mag., 2020
Zeroth-Order Hybrid Gradient Descent: Towards A Principled Black-Box Optimization Framework.
CoRR, 2020
6.7ms on Mobile with over 78% ImageNet Accuracy: Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration.
CoRR, 2020
TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series.
CoRR, 2020
Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization.
CoRR, 2020
CoRR, 2020
SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency.
CoRR, 2020
CoRR, 2020
IEEE Access, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the IUI '20: 25th International Conference on Intelligent User Interfaces, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case.
Proceedings of the 37th International Conference on Machine Learning, 2020
Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Towards an Efficient and General Framework of Robust Training for Graph Neural Networks.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Decentralized Min-Max Optimization: Formulations, Algorithms and Applications in Network Poisoning Attack.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Guaranteed Convergence of Training Convolutional Neural Networks via Accelerated Gradient Descent.
Proceedings of the 54th Annual Conference on Information Sciences and Systems, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Guest Editorial Special Issue on AI Enabled Cognitive Communication and Networking for IoT.
IEEE Internet Things J., 2019
CoRR, 2019
An Information-Theoretic Perspective on the Relationship Between Fairness and Accuracy.
CoRR, 2019
Min-Max Optimization without Gradients: Convergence and Applications to Adversarial ML.
CoRR, 2019
CoRR, 2019
CoRR, 2019
Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications.
Proceedings of the 36th International Conference on Machine Learning, 2019
Structured Adversarial Attack: Towards General Implementation and Better Interpretability.
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019
Proceedings of the IEEE International Conference on Acoustics, 2019
ADMM attack: an enhanced adversarial attack for deep neural networks with undetectable distortions.
Proceedings of the 24th Asia and South Pacific Design Automation Conference, 2019
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
2018
IEEE Trans. Signal Process., 2018
Accelerated Distributed Dual Averaging Over Evolving Networks of Growing Connectivity.
IEEE Trans. Signal Process., 2018
A Unified Framework of DNN Weight Pruning and Weight Clustering/Quantization Using ADMM.
CoRR, 2018
Is Ordered Weighted ℓ<sub>1</sub> Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR.
CoRR, 2018
Structured Adversarial Attack: Towards General Implementation and Better Interpretability.
CoRR, 2018
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018
Is Ordered Weighted ℓ1 Regularized Regression Robust to Adversarial Perturbation? A Case Study on OSCAR.
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018
Proceedings of the 2018 IEEE Global Conference on Signal and Information Processing, 2018
Zeroth-Order Online Alternating Direction Method of Multipliers: Convergence Analysis and Applications.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
IEEE Signal Process. Lett., 2017
Model Reduction in Chemical Reaction Networks: A Data-Driven Sparse-Learning Approach.
CoRR, 2017
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks.
CoRR, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017
Algorithm-hardware co-optimization of the memristor-based framework for solving SOCP and homogeneous QCQP problems.
Proceedings of the 22nd Asia and South Pacific Design Automation Conference, 2017
2016
IEEE Wirel. Commun. Lett., 2016
IEEE Trans. Signal Process., 2016
IEEE Trans. Signal Process., 2016
Towards an online energy allocation policy for distributed estimation with sensor collaboration using energy harvesting sensors.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016
Optimal energy allocation and storage control for distributed estimation with sensor collaboration.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016
2015
IEEE Trans. Signal Process., 2015
CoRR, 2015
Sensor selection with correlated measurements for target tracking in wireless sensor networks.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
Sparsity-promoting sensor management for estimation: An energy balance point of view.
Proceedings of the 18th International Conference on Information Fusion, 2015
Design of transmit-diversity schemes in detection networks under secrecy constraints.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015
On optimal sensor collaboration for distributed estimation with individual power constraints.
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015
2014
IEEE Trans. Signal Process., 2014
IEEE Trans. Aerosp. Electron. Syst., 2014
IEEE Signal Process. Lett., 2014
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014
Proceedings of the IEEE International Conference on Acoustics, 2014
2013
On optimal periodic sensor scheduling for field estimation in wireless sensor networks.
Proceedings of the IEEE Global Conference on Signal and Information Processing, 2013
Adaptive non-myopic quantizer design for target tracking in wireless sensor networks.
Proceedings of the 2013 Asilomar Conference on Signals, 2013
2012
Temporally staggered sensing for field estimation with quantized data in wireless sensor networks.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012