Efficient Formal Safety Analysis of Neural Networks. - Shiqi Wang 002; Kexin Pei; Justin Whitehouse; Junfeng Yang; Suman Jana (NeurIPS, 2018)

Formal Security Analysis of Neural Networks using Symbolic Intervals. - Shiqi Wang 002; Kexin Pei; Justin Whitehouse; Junfeng Yang; Suman Jana (USENIX Security Symposium, 2018)

Bringing Engineering Rigor to Deep Learning. - Kexin Pei; Shiqi Wang 002; Yuchi Tian; Justin Whitehouse; Carl Vondrick; Yinzhi Cao; Baishakhi Ray; Suman Jana; Junfeng Yang (ACM SIGOPS Oper. Syst. Rev., 2019)

Optimal Resource Allocation for Elastic and Inelastic Jobs. - Benjamin Berg; Mor Harchol-Balter; Benjamin Moseley; Weina Wang 001; Justin Whitehouse (SPAA, 2020)

Brownian Noise Reduction: Maximizing Privacy Subject to Accuracy Constraints. - Justin Whitehouse; Aaditya Ramdas; Zhiwei Steven Wu; Ryan M. Rogers (NeurIPS, 2022)

The case for phase-aware scheduling of parallelizable jobs. - Benjamin Berg; Justin Whitehouse; Benjamin Moseley; Weina Wang 001; Mor Harchol-Balter (Perform. Evaluation, 2022)

Fully-Adaptive Composition in Differential Privacy. - Justin Whitehouse; Aaditya Ramdas; Ryan Rogers 002; Steven Wu 001 (ICML, 2023)

Adaptive Principal Component Regression with Applications to Panel Data. - Anish Agarwal; Keegan Harris; Justin Whitehouse; Zhiwei Steven Wu (NeurIPS, 2023)

On the Sublinear Regret of GP-UCB. - Justin Whitehouse; Aaditya Ramdas; Zhiwei Steven Wu (NeurIPS, 2023)

Improved Self-Normalized Concentration in Hilbert Spaces: Sublinear Regret for GP-UCB. - Justin Whitehouse; Zhiwei Steven Wu; Aaditya Ramdas (CoRR, 2023)

Mutli-Armed Bandits with Network Interference. - Abhineet Agarwal; Anish Agarwal; Lorenzo Masoero; Justin Whitehouse (NeurIPS, 2024)

Multi-Armed Bandits with Network Interference. - Abhineet Agarwal; Anish Agarwal; Lorenzo Masoero; Justin Whitehouse (CoRR, 2024)

Orthogonal Causal Calibration. - Justin Whitehouse; Christopher Jung 001; Vasilis Syrgkanis; Bryan Wilder; Zhiwei Steven Wu (CoRR, 2024)

Orthogonal Causal Calibration (Extended Abstract). - Justin Whitehouse; Christopher Jung 001; Vasilis Syrgkanis; Bryan Wilder; Zhiwei Steven Wu (COLT, 2025)

Time-Uniform Self-Normalized Concentration for Vector-Valued Processes (Extended Abstract). - Justin Whitehouse; Zhiwei Steven Wu; Aaditya Ramdas (COLT, 2025)

Inference on Optimal Policy Values and Other Irregular Functionals via Smoothing. - Justin Whitehouse; Morgane Austern; Vasilis Syrgkanis (CoRR, 2025)