40 citations · 47 across the 14 of their papers we have counts for
14 papers
Why Global LLM Leaderboards Are Misleading: Small Portfolios for Heterogeneous Supervised ML
Jai Moondra, Ayela Chughtai, Bhargavi Lanka +1
Ranking LLMs via pairwise human feedback underpins current leaderboards for open-ended tasks, such as creative writing and problem-solving. We analyze ~89K comparisons in 116 langu…
Many Preferences, Few Policies: Compact Portfolios for Multi-Objective LLM Alignment
Cheol Woo Kim, Jai Moondra, Roozbeh Nahavandi +3
Aligning large language models (LLMs) requires balancing competing objectives such as helpfulness, harmlessness, and conciseness. The appropriate balance varies across users and ap…
Stochastic Function Certification with Correlations
Rohan Ghuge, Jai Moondra, Mohit Singh
We study the Stochastic Boolean Function Certification (SBFC) problem, where we are given Bernoulli random variables on a ground set of elements with…
Block-Norm Geometries for Online Mirror Descent with Sparse Losses
Swati Gupta, Jai Moondra, Mohit Singh
The performance of online mirror descent depends critically on the geometry induced by its mirror map, yet standard algorithms largely rely on two canonical choices: Euclidean and…
Provably Small Portfolios for Multiobjective Optimization with Application to Subsidized Facility Location
Swati Gupta, Jai Moondra, Mohit Singh
Many multiobjective real-world problems, such as facility location and bus routing, become more complex when optimizing the priorities of multiple stakeholders. These are often mod…
Navigating the Social Welfare Frontier: Portfolios for Multi-objective Reinforcement Learning
Cheol Woo Kim, Jai Moondra, Shresth Verma +4
In many real-world applications of reinforcement learning (RL), deployed policies have varied impacts on different stakeholders, creating challenges in reaching consensus on how to…
Promise of Graph Sparsification and Decomposition for Noise Reduction in QAOA: Analysis for Trapped-Ion Compilations
Jai Moondra, Phillip C. Lotshaw, Greg Mohler +1
We develop new approximate compilation schemes that significantly reduce the expense of compiling the Quantum Approximate Optimization Algorithm (QAOA) for solving the Max-Cut prob…
Balancing Notions of Equity: Trade-offs Between Fair Portfolio Sizes and Achievable Guarantees
Swati Gupta, Jai Moondra, Mohit Singh
Motivated by fairness concerns, we study the `portfolio problem': given an optimization problem with set of feasible solutions, a class of fairness objective funct…
Which norm is the fairest? Approximations for fair facility location across all ""
Swati Gupta, Jai Moondra, Mohit Singh
Fair facility location problems try to balance access costs to open facilities borne by different groups of people by minimizing the norm of these group distances. However, t…
Multi Purpose Routing: New Perspectives and Approximation Algorithms
Majid Farhadi, Jai Moondra, Prasad Tetali +1
The cost due to delay in services may be intrinsically different for various applications of vehicle routing such as medical emergencies, logistical operations, and ride-sharing. W…
Warm-Started QAOA with Custom Mixers Provably Converges and Computationally Beats Goemans-Williamson's Max-Cut at Low Circuit Depths
Reuben Tate, Jai Moondra, Bryan Gard +2
We generalize the Quantum Approximate Optimization Algorithm (QAOA) of Farhi et al. (2014) to allow for arbitrary separable initial states with corresponding mixers such that the s…
Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes
Jai Moondra, Hassan Mortagy, Swati Gupta
Optimization algorithms such as projected Newton's method, FISTA, mirror descent, and its variants enjoy near-optimal regret bounds and convergence rates, but suffer from a computa…
Generating Target Graph Couplings for QAOA from Native Quantum Hardware Couplings
Joel Rajakumar, Jai Moondra, Bryan Gard +2
We present methods for constructing any target coupling graph using limited global controls in an Ising-like quantum spin system. Our approach is motivated by implementing the quan…
On the least size of a graph with a given degree set -- II
Jai Moondra, Aditya Sahdev, Amitabha Tripathi
The degree set of a finite simple graph is the set of distinct degrees of vertices of . A theorem of Kapoor, Polimeni & Wall asserts that the least order of a graph with a g…