Sijia Liu

According to our database1, Sijia Liu authored at least 100 papers between 2012 and 2020.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Online presence:

On csauthors.net:

Bibliography

2020
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications.
IEEE Signal Process. Mag., 2020

Training Stronger Baselines for Learning to Optimize.
CoRR, 2020

Higher-Order Certification for Randomized Smoothing.
CoRR, 2020

TimeAutoML: Autonomous Representation Learning for Multivariate Irregularly Sampled Time Series.
CoRR, 2020

Learned Fine-Tuner for Incongruous Few-Shot Learning.
CoRR, 2020

Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization.
CoRR, 2020

The Lottery Ticket Hypothesis for Pre-trained BERT Networks.
CoRR, 2020

Proper Network Interpretability Helps Adversarial Robustness in Classification.
CoRR, 2020

Can 3D Adversarial Logos Cloak Humans?
CoRR, 2020

Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case.
CoRR, 2020

Solving Constrained CASH Problems with ADMM.
CoRR, 2020

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning.
CoRR, 2020

Rethinking Randomized Smoothing for Adversarial Robustness.
CoRR, 2020

Defending against Backdoor Attack on Deep Neural Networks.
CoRR, 2020

SS-Auto: A Single-Shot, Automatic Structured Weight Pruning Framework of DNNs with Ultra-High Efficiency.
CoRR, 2020

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices.
CoRR, 2020

Privacy-Preserving Energy Scheduling for Smart Grid With Renewables.
IEEE Access, 2020

AutoAI: Automating the End-to-End AI Lifecycle with Humans-in-the-Loop.
Proceedings of the IUI '20: 25th International Conference on Intelligent User Interfaces, 2020

Survey on Automated End-to-End Data Science?
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Sign-OPT: A Query-Efficient Hard-label Adversarial Attack.
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

Adversarial T-Shirt! Evading Person Detectors in a Physical World.
Proceedings of the Computer Vision - ECCV 2020, 2020

Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases.
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

Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning.
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

Towards Certificated Model Robustness Against Weight Perturbations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

An ADMM Based Framework for AutoML Pipeline Configuration.
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

Towards Verifying Robustness of Neural Networks Against Semantic Perturbations.
CoRR, 2019

How can AI Automate End-to-End Data Science?
CoRR, 2019

Evading Real-Time Person Detectors by Adversarial T-shirt.
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

Reweighted Proximal Pruning for Large-Scale Language Representation.
CoRR, 2019

Beyond Adversarial Training: Min-Max Optimization in Adversarial Attack and Defense.
CoRR, 2019

Automated Machine Learning via ADMM.
CoRR, 2019

Interpreting Adversarial Examples by Activation Promotion and Suppression.
CoRR, 2019

Second Rethinking of Network Pruning in the Adversarial Setting.
CoRR, 2019

Progressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM.
CoRR, 2019

ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization.
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

Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective.
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

signSGD via Zeroth-Order Oracle.
Proceedings of the 7th International Conference on Learning Representations, 2019

On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization.
Proceedings of the 7th International Conference on Learning Representations, 2019

Generation of Low Distortion Adversarial Attacks via Convex Programming.
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

Adversarial Robustness vs. Model Compression, or Both?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Latent Heterogeneous Multilayer Community Detection.
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
Optimal Sensor Collaboration for Parameter Tracking Using Energy Harvesting Sensors.
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

Progressive Weight Pruning of Deep Neural Networks 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

Multi-Layer Relevance Networks.
Proceedings of the 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2018

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks.
Proceedings of the 2018 ACM Multimedia Conference on Multimedia Conference, 2018

Zeroth-Order Diffusion Adaptation Over Networks.
Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

First-Order Bifurcation Detection for Dynamic Complex Networks.
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

Zeroth-Order Stochastic Projected Gradient Descent for Nonconvex Optimization.
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
Bias-Variance Tradeoff of Graph Laplacian Regularizer.
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

A Memristor-Based Optimization Framework for AI Applications.
CoRR, 2017

Ultra-fast robust compressive sensing based on memristor crossbars.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Distributed sensor selection for field estimation.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Distributed optimization for evolving networks of growing connectivity.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Learning sparse graphs under smoothness prior.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Semiblind subgraph reconstruction in Gaussian graphical models.
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
Measurement Matrix Design for Compressed Detection With Secrecy Guarantees.
IEEE Wirel. Commun. Lett., 2016

Optimized Sensor Collaboration for Estimation of Temporally Correlated Parameters.
IEEE Trans. Signal Process., 2016

Sensor Selection for Estimation with Correlated Measurement Noise.
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

Sensor placement for field estimation via Poisson disk sampling.
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
Sparsity-Aware Sensor Collaboration for Linear Coherent Estimation.
IEEE Trans. Signal Process., 2015

Measurement Matrix Design for Compressive Detection with Secrecy Guarantees.
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

Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks.
Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, 2015

2014
Optimal Periodic Sensor Scheduling in Networks of Dynamical Systems.
IEEE Trans. Signal Process., 2014

Sensor selection for nonlinear systems in large sensor networks.
IEEE Trans. Aerosp. Electron. Syst., 2014

Energy-Aware Sensor Selection in Field Reconstruction.
IEEE Signal Process. Lett., 2014

On optimal sensor collaboration topologies for linear coherent estimation.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Sparsity-aware field estimation via ordinary Kriging.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Optimal Periodic Sensor Scheduling in Large-Scale Dynamical Networks
CoRR, 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


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