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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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portfolio
Portfolio item number 1
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Portfolio item number 2
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publications
publicationsCombinatorics
Exact and Approximate Results on the Least Size of a Graph with a Given Degree Set
Published in Discrete Applied Mathematics, with Aditya Sahdev and Amitabha Tripathi.
Recommended citation: Jai Moondra, Aditya Sahdev, Amitabha Tripathi. (2023). "Exact and approximate results on the least size of a graph with a given degree set." arXiv. https://arxiv.org/abs/2009.10294
New Proofs for the Disjunctive Rado Number of the Equations $x_1 - x_2 = a$ and $x_1 - x_2 = b$
Published in Graphs and Combinatorics, with A. Dileep and Amitabha Tripathi.
Recommended citation: A. Dileep, Jai Moondra, Amitabha Tripathi. (2022). "New Proofs for the Disjunctive Rado Number of the Equations $x_1 - x_2 = a$ and $x_1 - x_2 = b$." Graphs and Combinatorics 38:38. https://link.springer.com/article/10.1007/s00373-021-02400-y
On Disjunctive Rado Numbers for Some Sets of Equations
Published in The Electronic Journal of Combinatorics, with A. Dileep and Amitabha Tripathi.
Recommended citation: A. Dileep, Jai Moondra, Amitabha Tripathi. (2024). "On Disjunctive Rado Numbers for Some Sets of Equations." The Electronic Journal of Combinatorics 31:1. https://www.combinatorics.org/ojs/index.php/eljc/article/view/v31i1p69
publicationsDiscreteOptimization
Multi Purpose Routing: New Perspectives and Approximation Algorithms
Published in arXiv, 2022
Recommended citation: Majid Farhadi, Jai Moondra, Prasad Tetali, Alejandro Toriello. (2022). "Multi Purpose Routing: New Perspectives and Approximation Algorithms." arXiv. https://arxiv.org/abs/2208.04410
Which $L_p$ norm is the fairest? Approximations for fair facility location across all “$p$”
Published in Economics and Computation (EC), 2023
Recommended citation: Swati Gupta, Jai Moondra, Mohit Singh. (July 2023). " Which $L_p$ norm is the fairest? Approximations for fair facility location across all "$p$"." In Proceedings of the 24th ACM Conference on Economics and Computation (EC) 2023 https://arxiv.org/abs/2211.14873
Balancing Notions of Equity: Trade-offs Between Fair Portfolio Sizes and Achievable Guarantees
Published in SODA 2025 (Accepted), 2024
Abstract: Motivated by fairness concerns, we study the `portfolio problem’: given an optimization problem with set D of feasible solutions, a class $\mathbf{C}$ of fairness objective functions on $D$, and an approximation factor $\alpha \ge 1$, a set $X \subseteq D$ of feasible solutions is an $\alpha$-approximate portfolio if for each objective $f \in \mathbf{C}$, there is an $\alpha$-approximation for $f$ in $X$. Choosing the classes of top-$k$ norms, ordered norms, and symmetric monotonic norms as our equity objectives, we study the trade-off between the size of the portfolio and its approximation factor α for various combinatorial problems. For the problem of scheduling identical jobs on unidentical machines, we characterize this trade-off for ordered norms and give an exponential improvement in size for symmetric monotonic norms over the general upper bound. We generalize this result as the OrderAndCount framework that obtains an exponential improvement in portfolio sizes for covering polyhedra with a constant number of constraints. Our framework is based on a novel primal-dual counting technique that may be of independent interest. We also introduce a general IterativeOrdering framework for simultaneous approximations or portfolios of size 1 for symmetric monotonic norms, which generalizes and extends existing results for problems such as scheduling, $k$-clustering, set cover, and routing.
Recommended citation: Swati Gupta, Jai Moondra, Mohit Singh. Symposium on Discrete Algorithms (Accepted, October 2024). "Balancing Notions of Equity: Trade-offs Between Fair Portfolio Sizes and Achievable Guarantees" https://arxiv.org/abs/2311.03230
publicationsMachineLearning
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes
Published in NeurIPS, with Hasan Mortagy and Swati Gupta.
Recommended citation: Jai Moondra, Hassan Mortagy, Swati Gupta. (2021). "Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes." In proceedings of the 34th conference on Neural Information Processing Systems (NeurIPS). https://proceedings.neurips.cc/paper/2021/file/d58f36f7679f85784d8b010ff248f898-Paper.pdf
publicationsQuantumComputing
Generating Target Graph Couplings for QAOA from Native Quantum Hardware Couplings
Published in Physical Review A, with Joel Rajakumar, Bryan Gard, Swati Gupta, and Creston D. Herold.
Recommended citation: Joel Rajakumar, Jai Moondra, Bryan Gard, Swati Gupta, Creston D. Herold. (August 2022). "Generating Target Graph Couplings for QAOA from Native Quantum Hardware Couplings." Physical Review A 106.2 https://arxiv.org/abs/2011.08165
Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson’s Max-Cut at Low Circuit Depths
Published in Quantum, with Reuben Tate, Bryan Gard, Greg Mohler, and Swati Gupta.
Recommended citation: Reuben Tate, Jai Moondra, Bryan Gard, Greg Mohler, Swati Gupta. (September 2023). "Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson’s Max-Cut at Low Circuit Depths" https://arxiv.org/abs/2112.11354
Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations
Published in arXiv, with Philip C. Lotshaw, Greg Mohler, and Swati Gupta.
Recommended citation: Jai Moondra, Philip C. Lotshaw, Greg Mohler, Swati Gupta. (June 2024). "Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations ." In arXiv https://arxiv.org/abs/2406.14330
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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