Publications

• H. D. Kaushik, S. Samadi, and F. Yousefian, An Incremental Gradient Method for Optimization Problems with Variational Inequality Constraints, IEEE Transactions on Automatic Control, April 2023. [arXiv]

• A. Al-Tawaha, H. D. Kaushik, and M. Jin, Decision-focused learning for inverse noncooperative games: Generalization bounds and convergence analysis, accepted for IFAC World Congress, March 2023. 

• M. Jin, V. Khattar, H. D. Kaushik, B. Sel, and R. Jia, On Solution Functions of Optimization: Universal Approximation and Covering Number Bounds, accepted at the 36th AAAI Conference on Artificial Intelligence (AAAI-23), January 2023.

• H. D. Kaushik and M. Jin, Iterative Implicit Gradients for Nonconvex Optimization with Variational Inequality Constraints, submitted March. 2022. [arXiv]

• H. D. Kaushik and F. Yousefian, A Method with Convergence Rates for Optimization Problems with Variational Inequality Constraints, SIAM Journal on Optimization, 31 (3), 2171–2198, 2021. doi:  10.1137/20M1357378 . [Link]

• H. D. Kaushik and F. Yousefian, An Incremental Gradient Method for Large-scale Distributed Nonlinearly Constrained Optimization, 2021 American Control Conference (ACC), 2021, pp. 953–958. [Link]

• H. D. Kaushik and F. Yousefian, A Randomized Block Coordinate Iterative Regularized Subgradient Method for High-dimensional Ill-posed Convex Optimization, in 2019 American Control Conference (ACC), Philadelphia, PA, USA, 2019, pp. 3420–3425. [Link]

• F. Yousefian, J. Yevale, and H. D. Kaushik, Distributed Randomized Block Stochastic Gradient Tracking Method, submitted Oct. 2021. [arXiv]

• P. Ramu and H. D. Kaushik, A log-third order polynomial normal transformation approach for high-reliability estimation with scarce samples, International Journal of Reliability and Safety, 14 (1), 14–38, 2020. [Link]

• H. D. Kaushik, R. Mohan, and K.A. Prakash, Utilization of wind shear for powering unmanned aerial vehicles in surveillance application: A numerical optimization study, Energy Procedia, 90, 349–359, 2016. [Link]

Conference Presentations

• Decision-focused utility learning”, INFORMS Annual Meeting 2022, Indianapolis, IN (Oct. 16th, 2022). 

• Guest Lecture for an Advanced Machine Learning Course, ECE 5424 - Virginia Tech (April 21st, 2022). 

• “Decision-focused Utility Learning”, Poster presentation at the CPES-PEC Conference, Virginia Tech (April 14th, 2022).

• "Distributed optimization problems with variational inequality constraints: algorithms, complexity analysis, and applications", INFORMS Annual Meeting 2021, online (Oct 24th, 2021).

• "An incremental gradient method for large-scale distributed nonlinearly constrained optimization", American Control Conference 2021, online (May 25th, 2021).

• "An incremental gradient method for large-scale distributed nonlinearly constrained optimization", INFORMS Annual Meeting 2020 (Nov. 13th, 2020).

• "First-order methods for optimization over the solution set of variational inequality problems", INFORMS Annual Meeting 2019, Seattle, WA (Oct. 22nd, 2019).

• "A randomized block coordinate iterative regularized subgradient method for high-dimensional ill-posed convex optimization", American Control Conference 2019 , Philadelphia, PA (Jul. 11th, 2019).

• "A first order method for high-dimensional ill-posed optimization problems", INFORMS Annual Meeting 2018, Phoenix, AZ (Nov. 5th, 2018).

• "Utilization of wind shear for powering unmanned aerial vehicles in surveillance application: A numerical optimization study", 5th International Conference on Advances in Energy Research, ICAER 2015, Mumbai, India (Dec. 16th, 2015).