Adversarial Machine Learning

• P. Zhao, L. Lai, L. Shen, Q. Li, J. Wu and Z. Liu, “A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy“,  Conference on Neural Information Processing Systems (NeurIPS), 2024.
• G. Liu, Z. Zhou, H. Liu and L. Lai, “Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty“. Transactions on Machine Learning Research. 2024.
• C. Yang, G. Liu and L. Lai, “Stochastic Bandits with Non-stationary Rewards: Reward Attack and Defense,” IEEE Transactions on Signal Processing. To appear. 
• G. Liu and L. Lai, “Efficient Adversarial Attacks on Online Multi-agent Reinforcement Learning“,  Conference on Neural Information Processing Systems (NeurIPS), 2023.
• Y. Jin and L. Lai, “Fairness-aware Regression Robust to Adversarial Attacks“. IEEE Transactions on Signal Processing, 2023.
• G. Liu and L. Lai, “Provably Efficient Black-Box Action Poisoning Attacks Against Reinforcement Learning“,  Conference on Neural Information Processing Systems (NeurIPS), 2021
• G. Liu and L. Lai, “Action Poisoning Attacks on Linear Contextual Bandits“. Transactions on Machine Learning Research.
• Y. Jin and L. Lai, “Optimal Accuracy-Privacy Trade-off of Inference as Service,” IEEE Transactions on Signal Processing. 
• F. Li, L. Lai and S. Cui, “Optimal Feature Manipulation Attacks Against Linear Regression,” IEEE Transactions on Signal Processing. 
• F. Li, L. Lai and S. Cui, “On the Adversarial Robustness of LASSO Based Feature Selection,” IEEE Transactions on Signal Processing. 
• Y. Jin and L. Lai, “On the Adversarial Robustness of Hypothesis Testing,” IEEE Transactions on Signal Processing, vol. 69, pp. 515-530, 2021.
• X. Cao and L. Lai, “Distributed Approximate Newton’s Method Robust to Byzantine Attackers,” IEEE Transactions on Signal Processing, vol. 68, pp. 6011-6025, 2020.
• G. Liu and L. Lai, “Action-Manipulation Attacks Against Stochastic Bandits: Attacks and Defense,” IEEE Transactions on Signal Processing, vol. 68, pp. 5152-5165, 2020.
• L. Lai and E. Bayraktar, ”On the Adversarial Robustness of Robust Estimators“. IEEE Transactions on Information Theory, vol. 66, no. 8, pp. 5097- 5109, Aug. 2020.
• F. Li, L. Lai and S. Cui, “On the Adversarial Robustness of Subspace Learning,” IEEE Transactions on Signal Processing, vol. 68, pp. 1470-1483, Mar. 2020.
• X. Cao and L. Lai, “Distributed Gradient Descent Algorithm Robust to an Arbitrary Number of Byzantine Attackers,” IEEE Transactions on Signal Processing, vol.67, no. 22, pp. 5850-5864, Nov. 2019.
• G. Fellouris, E. Bayraktar and L. Lai, “Efficient Byzantine Sequential Change Detection,” IEEE Transactions on Information Theory, vol. 64, no. 5, pp. 3346- 3360, May 2018.
• E. Bayraktar and L. Lai, “Byzantine Fault Tolerant Distributed Quickest Change Detection,” SIAM Journal on Control and Optimization, vol. 53, no. 2, pp. 575-591, Mar. 2015.

Statistical Inference

• Y. Jin, K. Balasubramanian, L. Lai, “Provable In-context Learning for Mixture of Linear Regressions using Transformers”. Submitted. 
• H. Liang, K. Balasubramanian, L. Lai, “Transformers Handle Endogeneity in In-Context Linear Regression”. Submitted. 
• P. Zhao and L. Lai, “Minimax Optimal Q Learning with Nearest Neighbors,” IEEE Transactions on Information Theory. Submitted. 
• X. Ma, L. Lai and S. Cui, “Bayesian Two-stage Sequential Change Diagnosis Via Sensor Arrays“. IEEE Transactions on Information Theory.
• M. Huang, K. Ji, S. Ma and L. Lai, “Efficiently Escaping Saddle Points in Bilevel Optimization“. Journal on Machine Learning Research. Submitted.
• M. Huang, S. Ma and L. Lai, “On the Convergence of Projected Alternating Maximization for Equitable and Optimal Transport“. Journal on Machine Learning Research. 2024.
• P. Zhao and L. Lai, “Analysis of KNN Density Estimation,” IEEE Transactions on Information Theory. 
• X. Ma, L. Lai and S. Cui, “Two-Stage Bayesian Sequential Change Diagnosis,” IEEE Transactions on Signal Processing. 
• M. Huang, S. Ma and L. Lai, “A Riemannian Block Coordinate Descent Method for Computing the Projection Robust Wasserstein Distance,” International Conference on Machine Learning (ICML), 2021.
• M. Huang, S. Ma and L. Lai, “Projection Robust Wasserstein Barycenter,” International Conference on Machine Learning (ICML), 2021.
• M. Huang, S. Ma and L. Lai, “Robust Low-rank Matrix Completion via an Alternating Manifold Proximal Gradient Continuation Method,” IEEE Transactions on Signal Processing. 
• P. Zhao and L. Lai, “Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression,” IEEE Transactions on Information Theory. 
• M. Cho, L. Lai and W. Xu, “Distributed Dual Coordinate Ascent in General Tree Networks and Communication Network Effect on Synchronous Machine Learning,” IEEE JSAC Series on Machine Learning for Communications and Networks. 
• P. Zhao and L. Lai, “Efficient Classification with Adaptive KNN,” AAAI Conference on Articial Intelligence (AAAI), Feb. 2021.
• P. Zhao and L. Lai, “Minimax Optimal Estimation of KL Divergence for Continuous Distributions,” IEEE Transactions on Information Theory, vol. 66, no. 12, pp. 7787- 7811, Dec. 2020.
• P. Zhao and L. Lai, “Analysis of KNN Information Estimators for Smooth Distributions,” IEEE Transactions on Information Theory, vol. 66, no. 6, pp. 3798-3826, June 2020.
• J. Geng, B. Zhang, L. Huie and L. Lai, “Online Change-Point Detection of Linear Regression Models,” IEEE Transactions on Signal Processing, vol, 67, no. 12, pp. 3316-3329, June 2019.
• W. Zhao and L. Lai, “Distributed Testing With Cascaded Encoders“, IEEE Transactions on Information Theory, vol. 64, no. 11, pp. 7339- 7348, Nov. 2018.
• M. El Gamal and L. Lai, “On Rate Requirements for Achieving the Centralized Performance in Distributed Estimation,” IEEE Transactions on Signal Processing, vol. 65, no. 8, pp. 2020- 2032, Apr. 2017.
• W. Zhao and L. Lai, “Distributed Detection with Vector Quantizer,” IEEE Transactions on Signal and Information Processing over Networks, vol.2, no. 2, pp. 105-119, June 2016.
• B. Zhang, J. Geng and L. Lai, “Multiple Change-Points Estimation in Linear Regression Models via Sparse Group Lasso,” IEEE Transactions on Signal Processing, vol. 63, no. 9, pp. 2209-2224, May 2015.

Sequential Analysis and Applications

• X. Ni and L. Lai, “Risk-Sensitive Reinforcement Learning with Phi-Divergence-Risk,” IEEE Transactions on Information Theory. Submitted. 
• X. Ni, G. Liu and L. Lai, “Risk-Sensitive Reward-Free Reinforcement Learning with CVaR“,  International Conference on Machine Learning (ICML), 2024.
• X. Ma, L. Lai and S. Cui, “Bayesian Two-stage Sequential Change Diagnosis Via Sensor Arrays“. IEEE Transactions on Information Theory.
• X. Ma, L. Lai and S. Cui, “Two-Stage Bayesian Sequential Change Diagnosis,” IEEE Transactions on Signal Processing. 
• J. Geng, B. Zhang, L. Huie and L. Lai, “Online Change-Point Detection of Linear Regression Models,” IEEE Transactions on Signal Processing, vol, 67, no. 12, pp. 3316-3329, June 2019.
• G. Fellouris, E. Bayraktar and L. Lai, “Efficient Byzantine Sequential Change Detection,” IEEE Transactions on Information Theory, vol. 64, no. 5, pp. 3346- 3360, May 2018.
• C. Tsinos, F. Foukalas, T. Khattab and L. Lai, “On Channel Selection for Carrier Aggregation Systems,” IEEE Transactions on Communications, vol. 66, no. 2, pp. 808-818, Feb. 2018.
• J. Geng, W. Xu and L. Lai, “Quickest Sequential Muti-Band Spectrum Sensing with Mixed Observations,” IEEE Transactions on Signal Processing, vol. 64, no. 22, pp. 5861-5874, Nov. 2016.
• E. Bayraktar and L. Lai, “Byzantine Fault Tolerant Distributed Quickest Change Detection,” SIAM Journal on Control and Optimization, vol. 53, no. 2, pp. 575-591, Mar. 2015.
• J. Geng, E. Bayraktar and L. Lai, “Bayesian Quickest Change Point Detection with Sampling Right Constraints,” IEEE Transactions on Information Theory, vol. 60, no. 10, pp.6474-6490, Oct. 2014.
• R. Caromi, S. Mohan and L. Lai, “Optimal Sequential Channel Estimation and Probing for Multiband Cognitive Radio Systems,” IEEE Transactions on Communications, vol. 62, no. 8, pp. 2696-2708, Aug. 2014.
• Y. Xin, H. Zhang and L. Lai, “A Low-Complexity Sequential Spectrum Sensing Algorithm for Cognitive Radio,” IEEE Journal on Selected Areas in Communications: Cognitive Radio Series, vol. 32, no. 3, pp. 387-399, Mar. 2014.
• J. Geng and L. Lai, “Non-Bayesian Quickest Change Detection with Stochastic Sample Right Constraints,” IEEE Transactions on Signal Processing, vol. 61, no. 20, pp. 5090-5102, Oct. 2013.
• R. Caromi, Y. Xin and L. Lai, “Fast Multi-band Spectrum Scanning for Cognitive Radio Systems,” IEEE Transactions on Communications, vol. 61, no. 1, pp. 63-75, Jan. 2013.
• L. Lai , H. Vincent Poor, Y. Xin and G. Georgiadis, “Quickest Search over Multiple Sequences,” IEEE Transactions on Information Theory, vol. 57, no. 8, pp. 5375 -5386, Aug. 2011.
• Y. Liang, L. Lai  and J. Halloran, “Distributed Cognitive Radio Network Management via Algorithms in Probabilistic Graphical Models,” IEEE Journal on Selected Areas in Communications, Special Issue on Advances in Cognitive Radio Networking and Communications, vol. 29, no. 2, pp. 338-348, Feb. 2011.
• L. Lai , H. El Gamal, H. Jiang and H. Vincent Poor, “Cognitive Medium Access: Exploration, Exploitation and Competition,” IEEE Transactions on Mobile Computing, vol. 10, no. 2, pp. 239-253, Feb. 2011.
• H. Jiang, L. Lai , R. Fan and H. Vincent Poor, “Optimal Selection of Channel Sensing Order in Cognitive Radios,” IEEE Transactions on Wireless Communications , vol. 8, no. 1, pp. 297-307, Jan. 2009.

Information Theoretic Security

• W. Tu and L. Lai, “On Function Computation with Privacy and Secrecy Constraints,” IEEE Transactions on Information Theory, vol. 65, no. 10, pp. 6716-6733, Oct. 2019.
• W. Tu and L. Lai, “Keyless Authentication and Authenticated Capacity,” IEEE Transactions on Information Theory, vol. 64, no. 5, pp. 3696- 3714, May 2018.
• S. Zou, Y. Liang, L. Lai, H. V. Poor and S. Shamai (Shitz), “Degraded Broadcast Channel with Secrecy Outside a Bounded Range,” IEEE Transactions on Information Theory, vol. 64, no. 3, pp. 2104-2120, Mar. 2018.
• S. Zou, Y. Liang, L. Lai  and S. Shamai (Shitz), “An Information Theoretic Approach to Secret Sharing,” IEEE Transactions on Information Theory, vol. 61, no. 6, pp. 3121-3136, June 2015.
• Y. Liang, L. Lai , H. Vincent Poor and S. Shamai (Shitz), “A Broadcast Approach for Fading Gaussian Wiretap Channels,” IEEE Transactions on Information Theory, vol. 60, no. 2, pp. 842-858, Feb. 2014.
• O. O. Koyluoglu, H. El Gamal, L. Lai  and H. Vincent Poor, “Interference Alignment for Secrecy,” IEEE Transactions on Information Theory, vol. 57, no. 6, pp. 3323 – 3332, June 2011.
• L. Lai , S.-W. Ho and H. Vincent Poor, “Privacy-Security Tradeoff in Biometric Security Systems Part II: Multiple Uses Case,” IEEE Transactions on Information Forensics and Security, vol. 6, no. 1, pp. 140-151, Mar. 2011.
• L. Lai , S.-W. Ho and H. Vincent Poor, “Privacy-Security Tradeoff in Biometric Security Systems Part I: Single Use Case,” IEEE Transactions on Information Forensics and Security, vol. 6, no. 1, pp. 122-139, Mar. 2011.
• L. Lai , H. El Gamal and H. Vincent Poor, “Authentication over Noisy Channels,” IEEE Transactions on Information Theory, vol. 55, no. 2, pp. 906-916, Feb. 2009.
• L. Lai , H. El Gamal and H. Vincent Poor, “The Wiretap Channel with Feedback: Encryption over the Channel,”IEEE Transactions on Information Theory, vol. 54, no. 11, pp. 5059 – 5067, Nov. 2008.
• P. K. Gopala, L. Lai  and H. El Gamal, “On the Secrecy Capacity of Fading Channels,” IEEE Transactions on Information Theory, vol. 54, no. 10, pp. 4687 – 4698, Oct. 2008.
• L. Lai  and H. El Gamal, “The Relay-Eavesdropper Channel: Cooperation for Secrecy,” IEEE Transactions on Information Theory , vol. 54, no. 9, pp. 4005 – 4019, Sept. 2008.

Secret Key Generation

• H. Zhang, Y. Liang, L. Lai  and S. Shamai (Shitz), “Multi-Key Generation over a Cellular Model with a Helper,” IEEE Transactions on Information Theory, vol. 63, no. 6, pp. 3804- 3822, June 2017.
• W. Tu, M. Goldenbaum, L. Lai  and H. V. Poor, “On Simultaneously Generating Multiple Keys in Joint Source-Channel Model,” IEEE Transactions on Information Forensics and Security, vol. 12, no. 2, pp. 298-308, Feb. 2017.
• L. Lai  and S.-W. Ho, “Key Generation Algorithms for Pairwise Independent Networks Based on Graphical Models,” IEEE Transactions on Information Theory, vol. 61, no. 9, pp. 4828-4837, Sept. 2015.
• H. Zhang, L. Lai , Y. Liang and H. Wang, “The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation,” IEEE Transactions on Information Theory, vol. 60, no. 10, pp.6389-6398, Oct. 2014.
• H. Zhou, L. Huie and L. Lai, “Secret Key Generation in the Two-Way Relay Channel with Active Attackers,” IEEE Transactions on Information Forensics and Security, vol. 9, no. 3, pp. 476-488, Mar. 2014.
• L. Lai , Y. Liang and W. Du, “Cooperative Key Generation in Wireless Networks,” IEEE Journal on Selected Areas in Communications, Special Issue on Theories and Methods for Advanced Wireless Relays, vol. 30, no. 8, pp. 1578 – 1588, Sept. 2012.
• L. Lai , Y. Liang and H. Vincent Poor, “A Unified Framework for Key Agreement over Wireless Fading Channels,” IEEE Transactions on Information Forensics and Security, vol 7, no. 2, pp. 480 – 490, Apr. 2012.