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Harish Chandramouleeswaran

Publications and source records attributed to Harish Chandramouleeswaran.

3 recordsLinked to original sources

Nonexistence of Simultaneously EF1 and Pareto Optimal Allocations for Submodular Valuations

The existence of allocations of indivisible goods that are simultaneously fair (envy-free up to one item (EF1)) and efficient (Pareto optimal (PO)) when agents have monotone submodular valuations has been a longstanding open problem. We settle this question negatively by giving an example with two agents where no allocation is simultaneously EF1 and PO. We also show that determining the existence of such allocations is NP-hard for monotone submodular valuations. Our example uses (unweighted) coverage valuations, which is a strict subclass of monotone submodular valuations. Since EF1+PO allocations are known to always exist for additive valuations via the maximization of Nash Social Welfare (Caragiannis et al. (ACM TEAC 2019)), and for matroid-rank valuations (Benabbou et al. (ACM TEAC 2021)), nonexistence was known only for monotone subadditive valuations (Caragiannis et al. (ACM TEAC 2019)). Our work moves the nonexistence frontier to unweighted coverage valuations. We also show that the example we designed for goods also proves nonexistence of EF1+PO in general, for chores with unweighted coverage costs, by interpreting the valuations as disutilities.

cs.GT↗

Fair Division in a Variable Setting

We study fair division of indivisible items under a variable input setting, where the set of agents or items may change over time. Starting from an arbitrary allocation, the goal is to restore envy-freeness up to one item (EF1) through item transfers while causing as little disruption as possible. We formalize this via `valid transfers' and introduce the EF1-Restoration problem. We give efficient algorithms for EF1-Restoration when agents have identical monotone valuations and the items are either all goods or all chores. In contrast, even for identical additive valuations, we prove that optimizing the number of valid transfers is NP-hard. For the stronger notion of EFX, we show that deciding whether EFX-Restoration admits any positive solution is weakly NP-hard for identical additive valuations. We also show that, unlike the pure goods and pure chores cases, EF1-Restoration may be impossible for mixed manna. For additive binary valuations, we prove that deciding whether EF1-Restoration is possible is NP-hard, and so is finding the minimum number of valid transfers when restoration is possible. We complement these hardness results with a polynomial-time algorithm for the subclass of additive binary valuations defined using multigraphs, introduced by Christodoulou et al. (EC 2023), when allocations are required to be orientations. Finally, for monotone binary valuations, we prove that deciding whether EF1-Restoration is possible is PSPACE-complete. Together, our results give a broad complexity landscape for restoring EF1 under variable inputs across several natural valuation classes.

cs.GT↗

Testing forbidden order-pattern properties on hypergrids

We study testing $π$-freeness of functions $f:[n]^d\to\mathbb{R}$, where $f$ is $π$-free if there there are no $k$ indices $x_1\prec\cdots\prec x_k\in [n]^d$ such that $f(x_i) 2$. We initiate a systematic study of pattern freeness on higher-dimensional grids. For $d=2$ and all permutations of size $k=3$, we design an adaptive one-sided tester with query complexity $O(n^{4/5+o(1)})$. We also prove general lower bounds for $k=3$: every nonadaptive tester requires $Ω(n)$ queries, and every adaptive tester requires $Ω(\sqrt{n})$ queries, yielding the first super-logarithmic lower bounds for $π$-freeness. For the monotone patterns $π=(1,2,3)$ and $(3,2,1)$, we present a nonadaptive tester with polylogarithmic query complexity, giving an exponential separation between monotone and nonmonotone patterns (unlike the one-dimensional case). A key ingredient in our $π$-freeness testers is new erasure-resilient ($δ$-ER) $ε$-testers for monotonicity over $[n]^d$ with query complexity $O(\log^{O(d)}n/(ε(1-δ)))$, where $0<δ<1$ is an upper bound on the fraction of erasures. Prior ER testers worked only for $δ=O(ε/d)$. Our nonadaptive monotonicity tester is nearly optimal via a matching lower bound due to Pallavoor, Raskhodnikova, and Waingarten (Random Struct. Algorithms, 2022). Finally, we show that current techniques cannot yield sublinear-query testers for patterns of length $4$ even on two-dimensional hypergrids.

cs.DS↗