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</p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gupta%2C+A">Anupam Gupta</a>, <a href="/search/cs?searchtype=author&query=Hu%2C+J">Jinqiao Hu</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Levin%2C+R">Roie Levin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2406.15876v1-abstract-short" style="display: inline;"> We study online contention resolution schemes (OCRSs) and prophet inequalities for non-product distributions. Specifically, when the active set is sampled according to a pairwise-independent (PI) distribution, we show a $(1-o_k(1))$-selectable OCRS for uniform matroids of rank $k$, and $惟(1)$-selectable OCRSs for laminar, graphic, cographic, transversal, and regular matroids. These imply prophet i… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.15876v1-abstract-full').style.display = 'inline'; document.getElementById('2406.15876v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2406.15876v1-abstract-full" style="display: none;"> We study online contention resolution schemes (OCRSs) and prophet inequalities for non-product distributions. Specifically, when the active set is sampled according to a pairwise-independent (PI) distribution, we show a $(1-o_k(1))$-selectable OCRS for uniform matroids of rank $k$, and $惟(1)$-selectable OCRSs for laminar, graphic, cographic, transversal, and regular matroids. These imply prophet inequalities with the same ratios when the set of values is drawn according to a PI distribution. Our results complement recent work of Dughmi, Kalayci, and Patel (STOC '24) showing that no $蠅(1/k)$-selectable OCRS exists in the PI setting for general matroids of rank $k$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2406.15876v1-abstract-full').style.display = 'none'; document.getElementById('2406.15876v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 June, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Contains new results on t-wise independent CRSs</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2404.14679">arXiv:2404.14679</a> <span> [<a href="https://arxiv.org/pdf/2404.14679">pdf</a>, <a href="https://arxiv.org/ps/2404.14679">ps</a>, <a href="https://arxiv.org/format/2404.14679">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> </div> </div> <p class="title is-5 mathjax"> A Multi-Dimensional Online Contention Resolution Scheme for Revenue Maximization </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Chawla%2C+S">Shuchi Chawla</a>, <a href="/search/cs?searchtype=author&query=Christou%2C+D">Dimitris Christou</a>, <a href="/search/cs?searchtype=author&query=Dang%2C+T">Trung Dang</a>, <a href="/search/cs?searchtype=author&query=Huang%2C+Z">Zhiyi Huang</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Rezvan%2C+R">Rojin Rezvan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2404.14679v1-abstract-short" style="display: inline;"> We study multi-buyer multi-item sequential item pricing mechanisms for revenue maximization with the goal of approximating a natural fractional relaxation -- the ex ante optimal revenue. We assume that buyers' values are subadditive but make no assumptions on the value distributions. While the optimal revenue, and therefore also the ex ante benchmark, is inapproximable by any simple mechanism in t… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.14679v1-abstract-full').style.display = 'inline'; document.getElementById('2404.14679v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2404.14679v1-abstract-full" style="display: none;"> We study multi-buyer multi-item sequential item pricing mechanisms for revenue maximization with the goal of approximating a natural fractional relaxation -- the ex ante optimal revenue. We assume that buyers' values are subadditive but make no assumptions on the value distributions. While the optimal revenue, and therefore also the ex ante benchmark, is inapproximable by any simple mechanism in this context, previous work has shown that a weaker benchmark that optimizes over so-called ``buy-many" mechanisms can be approximable. Approximations are known, in particular, for settings with either a single buyer or many unit-demand buyers. We extend these results to the much broader setting of many subadditive buyers. We show that the ex ante buy-many revenue can be approximated via sequential item pricings to within an $O(\log^2 m)$ factor, where $m$ is the number of items. We also show that a logarithmic dependence on $m$ is necessary. Our approximation is achieved through the construction of a new multi-dimensional Online Contention Resolution Scheme (OCRS), that provides an online rounding of the optimal ex ante solution. Chawla et al. arXiv:2204.01962 previously constructed an OCRS for revenue for unit-demand buyers, but their construction relied heavily on the ``almost single dimensional" nature of unit-demand values. Prior to that work, OCRSes have only been studied in the context of social welfare maximization for single-parameter buyers. For the welfare objective, constant-factor approximations have been demonstrated for a wide range of combinatorial constraints on item allocations and classes of buyer valuation functions. Our work opens up the possibility of a similar success story for revenue maximization. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.14679v1-abstract-full').style.display = 'none'; document.getElementById('2404.14679v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">39 pages</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.15657">arXiv:2306.15657</a> <span> [<a href="https://arxiv.org/pdf/2306.15657">pdf</a>, <a href="https://arxiv.org/ps/2306.15657">ps</a>, <a href="https://arxiv.org/format/2306.15657">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> </div> </div> <p class="title is-5 mathjax"> The Distortion of Binomial Voting Defies Expectation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gonczarowski%2C+Y+A">Yannai A. Gonczarowski</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Procaccia%2C+A+D">Ariel D. Procaccia</a>, <a href="/search/cs?searchtype=author&query=Schiffer%2C+B">Ben Schiffer</a>, <a href="/search/cs?searchtype=author&query=Zhang%2C+S">Shirley Zhang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.15657v2-abstract-short" style="display: inline;"> In computational social choice, the distortion of a voting rule quantifies the degree to which the rule overcomes limited preference information to select a socially desirable outcome. This concept has been investigated extensively, but only through a worst-case lens. Instead, we study the expected distortion of voting rules with respect to an underlying distribution over voter utilities. Our main… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.15657v2-abstract-full').style.display = 'inline'; document.getElementById('2306.15657v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.15657v2-abstract-full" style="display: none;"> In computational social choice, the distortion of a voting rule quantifies the degree to which the rule overcomes limited preference information to select a socially desirable outcome. This concept has been investigated extensively, but only through a worst-case lens. Instead, we study the expected distortion of voting rules with respect to an underlying distribution over voter utilities. Our main contribution is the design and analysis of a novel and intuitive rule, binomial voting, which provides strong distribution-independent guarantees for both expected distortion and expected welfare. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.15657v2-abstract-full').style.display = 'none'; document.getElementById('2306.15657v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 27 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">NeurIPS 2023</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2304.02063">arXiv:2304.02063</a> <span> [<a href="https://arxiv.org/pdf/2304.02063">pdf</a>, <a href="https://arxiv.org/ps/2304.02063">ps</a>, <a href="https://arxiv.org/format/2304.02063">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Data Structures and Algorithms">cs.DS</span> </div> </div> <p class="title is-5 mathjax"> Set Covering with Our Eyes Wide Shut </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gupta%2C+A">Anupam Gupta</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Levin%2C+R">Roie Levin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2304.02063v1-abstract-short" style="display: inline;"> In the stochastic set cover problem (Grandoni et al., FOCS '08), we are given a collection $\mathcal{S}$ of $m$ sets over a universe $\mathcal{U}$ of size $N$, and a distribution $D$ over elements of $\mathcal{U}$. The algorithm draws $n$ elements one-by-one from $D$ and must buy a set to cover each element on arrival; the goal is to minimize the total cost of sets bought during this process. A un… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.02063v1-abstract-full').style.display = 'inline'; document.getElementById('2304.02063v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2304.02063v1-abstract-full" style="display: none;"> In the stochastic set cover problem (Grandoni et al., FOCS '08), we are given a collection $\mathcal{S}$ of $m$ sets over a universe $\mathcal{U}$ of size $N$, and a distribution $D$ over elements of $\mathcal{U}$. The algorithm draws $n$ elements one-by-one from $D$ and must buy a set to cover each element on arrival; the goal is to minimize the total cost of sets bought during this process. A universal algorithm a priori maps each element $u \in \mathcal{U}$ to a set $S(u)$ such that if $U \subseteq \mathcal{U}$ is formed by drawing $n$ times from distribution $D$, then the algorithm commits to outputting $S(U)$. Grandoni et al. gave an $O(\log mN)$-competitive universal algorithm for this stochastic set cover problem. We improve unilaterally upon this result by giving a simple, polynomial time $O(\log mn)$-competitive universal algorithm for the more general prophet version, in which $U$ is formed by drawing from $n$ different distributions $D_1, \ldots, D_n$. Furthermore, we show that we do not need full foreknowledge of the distributions: in fact, a single sample from each distribution suffices. We show similar results for the 2-stage prophet setting and for the online-with-a-sample setting. We obtain our results via a generic reduction from the single-sample prophet setting to the random-order setting; this reduction holds for a broad class of minimization problems that includes all covering problems. We take advantage of this framework by giving random-order algorithms for non-metric facility location and set multicover; using our framework, these automatically translate to universal prophet algorithms. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2304.02063v1-abstract-full').style.display = 'none'; document.getElementById('2304.02063v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 April, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2211.15608">arXiv:2211.15608</a> <span> [<a href="https://arxiv.org/pdf/2211.15608">pdf</a>, <a href="https://arxiv.org/format/2211.15608">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> </div> </div> <p class="title is-5 mathjax"> Representation with Incomplete Votes </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Halpern%2C+D">Daniel Halpern</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Procaccia%2C+A+D">Ariel D. Procaccia</a>, <a href="/search/cs?searchtype=author&query=Tucker-Foltz%2C+J">Jamie Tucker-Foltz</a>, <a href="/search/cs?searchtype=author&query=W%C3%BCthrich%2C+M">Manuel W眉thrich</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2211.15608v4-abstract-short" style="display: inline;"> Platforms for online civic participation rely heavily on methods for condensing thousands of comments into a relevant handful, based on whether participants agree or disagree with them. These methods should guarantee fair representation of the participants, as their outcomes may affect the health of the conversation and inform impactful downstream decisions. To that end, we draw on the literature… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.15608v4-abstract-full').style.display = 'inline'; document.getElementById('2211.15608v4-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2211.15608v4-abstract-full" style="display: none;"> Platforms for online civic participation rely heavily on methods for condensing thousands of comments into a relevant handful, based on whether participants agree or disagree with them. These methods should guarantee fair representation of the participants, as their outcomes may affect the health of the conversation and inform impactful downstream decisions. To that end, we draw on the literature on approval-based committee elections. Our setting is novel in that the approval votes are incomplete since participants will typically not vote on all comments. We prove that this complication renders non-adaptive algorithms impractical in terms of the amount of information they must gather. Therefore, we develop an adaptive algorithm that uses information more efficiently by presenting incoming participants with statements that appear promising based on votes by previous participants. We prove that this method satisfies commonly used notions of fair representation, even when participants only vote on a small fraction of comments. Finally, an empirical evaluation using real data shows that the proposed algorithm provides representative outcomes in practice. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2211.15608v4-abstract-full').style.display = 'none'; document.getElementById('2211.15608v4-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 28 November, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2111.06842">arXiv:2111.06842</a> <span> [<a href="https://arxiv.org/pdf/2111.06842">pdf</a>, <a href="https://arxiv.org/ps/2111.06842">ps</a>, <a href="https://arxiv.org/format/2111.06842">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Data Structures and Algorithms">cs.DS</span> </div> </div> <p class="title is-5 mathjax"> Random Order Set Cover is as Easy as Offline </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Gupta%2C+A">Anupam Gupta</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Levin%2C+R">Roie Levin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2111.06842v2-abstract-short" style="display: inline;"> We give a polynomial-time algorithm for OnlineSetCover with a competitive ratio of $O(\log mn)$ when the elements are revealed in random order, essentially matching the best possible offline bound of $O(\log n)$ and circumventing the $惟(\log m \log n)$ lower bound known in adversarial order. We also extend the result to solving pure covering IPs when constraints arrive in random order. The algor… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.06842v2-abstract-full').style.display = 'inline'; document.getElementById('2111.06842v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2111.06842v2-abstract-full" style="display: none;"> We give a polynomial-time algorithm for OnlineSetCover with a competitive ratio of $O(\log mn)$ when the elements are revealed in random order, essentially matching the best possible offline bound of $O(\log n)$ and circumventing the $惟(\log m \log n)$ lower bound known in adversarial order. We also extend the result to solving pure covering IPs when constraints arrive in random order. The algorithm is a multiplicative-weights-based round-and-solve approach we call LearnOrCover. We maintain a coarse fractional solution that is neither feasible nor monotone increasing, but can nevertheless be rounded online to achieve the claimed guarantee (in the random order model). This gives a new offline algorithm for SetCover that performs a single pass through the elements, which may be of independent interest. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2111.06842v2-abstract-full').style.display = 'none'; document.getElementById('2111.06842v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 12 November, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">minor correction to potential argument</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2106.13882">arXiv:2106.13882</a> <span> [<a href="https://arxiv.org/pdf/2106.13882">pdf</a>, <a href="https://arxiv.org/format/2106.13882">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computer Science and Game Theory">cs.GT</span> </div> </div> <p class="title is-5 mathjax"> Can Buyers Reveal for a Better Deal? </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Halpern%2C+D">Daniel Halpern</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Tucker-Foltz%2C+J">Jamie Tucker-Foltz</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2106.13882v2-abstract-short" style="display: inline;"> We study market interactions in which buyers are allowed to credibly reveal partial information about their types to the seller. Previous recent work has studied the special case of one buyer and one good, showing that such communication can simultaneously improve social welfare and ex ante buyer utility. However, with multiple buyers, we find that the buyer-optimal signalling schemes from the one… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2106.13882v2-abstract-full').style.display = 'inline'; document.getElementById('2106.13882v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2106.13882v2-abstract-full" style="display: none;"> We study market interactions in which buyers are allowed to credibly reveal partial information about their types to the seller. Previous recent work has studied the special case of one buyer and one good, showing that such communication can simultaneously improve social welfare and ex ante buyer utility. However, with multiple buyers, we find that the buyer-optimal signalling schemes from the one-buyer case are actually harmful to buyer welfare. Moreover, we prove several impossibility results showing that, with either multiple i.i.d. buyers or multiple i.i.d. goods, maximizing buyer utility can be at odds with social efficiency, which is surprising in contrast with the one-buyer, one-good case. Finally, we investigate the computational tractability of implementing desirable equilibrium outcomes. We find that, even with one buyer and one good, optimizing buyer utility is generally NP-hard but tractable in a practical restricted setting. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2106.13882v2-abstract-full').style.display = 'none'; document.getElementById('2106.13882v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 3 May, 2022; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 25 June, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2011.06108">arXiv:2011.06108</a> <span> [<a href="https://arxiv.org/pdf/2011.06108">pdf</a>, <a href="https://arxiv.org/ps/2011.06108">ps</a>, <a href="https://arxiv.org/format/2011.06108">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Data Structures and Algorithms">cs.DS</span> </div> </div> <p class="title is-5 mathjax"> An Optimal Rounding for Half-Integral Weighted Minimum Strongly Connected Spanning Subgraph </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Hershkowitz%2C+D+E">D Ellis Hershkowitz</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Ravi%2C+R">R. Ravi</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2011.06108v1-abstract-short" style="display: inline;"> In the weighted minimum strongly connected spanning subgraph (WMSCSS) problem we must purchase a minimum-cost strongly connected spanning subgraph of a digraph. We show that half-integral linear program (LP) solutions for WMSCSS can be efficiently rounded to integral solutions at a multiplicative $1.5$ cost. This rounding matches a known $1.5$ integrality gap lower bound for a half-integral instan… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2011.06108v1-abstract-full').style.display = 'inline'; document.getElementById('2011.06108v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2011.06108v1-abstract-full" style="display: none;"> In the weighted minimum strongly connected spanning subgraph (WMSCSS) problem we must purchase a minimum-cost strongly connected spanning subgraph of a digraph. We show that half-integral linear program (LP) solutions for WMSCSS can be efficiently rounded to integral solutions at a multiplicative $1.5$ cost. This rounding matches a known $1.5$ integrality gap lower bound for a half-integral instance. More generally, we show that LP solutions whose non-zero entries are at least a value $f > 0$ can be rounded at a multiplicative cost of $2 - f$. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2011.06108v1-abstract-full').style.display = 'none'; document.getElementById('2011.06108v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 November, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2020. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2002.06160">arXiv:2002.06160</a> <span> [<a href="https://arxiv.org/pdf/2002.06160">pdf</a>, <a href="https://arxiv.org/format/2002.06160">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">stat.ML</span> </div> </div> <p class="title is-5 mathjax"> The Phantom Steering Effect in Q&A Websites </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Hoernle%2C+N">Nicholas Hoernle</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a>, <a href="/search/cs?searchtype=author&query=Procaccia%2C+A+D">Ariel D. Procaccia</a>, <a href="/search/cs?searchtype=author&query=Gal%2C+K">Kobi Gal</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2002.06160v2-abstract-short" style="display: inline;"> Badges are commonly used in online platforms as incentives for promoting contributions. It is widely accepted that badges "steer" people's behavior toward increasing their rate of contributions before obtaining the badge. This paper provides a new probabilistic model of user behavior in the presence of badges. By applying the model to data from thousands of users on the Q&A site Stack Overflow, we… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.06160v2-abstract-full').style.display = 'inline'; document.getElementById('2002.06160v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2002.06160v2-abstract-full" style="display: none;"> Badges are commonly used in online platforms as incentives for promoting contributions. It is widely accepted that badges "steer" people's behavior toward increasing their rate of contributions before obtaining the badge. This paper provides a new probabilistic model of user behavior in the presence of badges. By applying the model to data from thousands of users on the Q&A site Stack Overflow, we find that steering is not as widely applicable as was previously understood. Rather, the majority of users remain apathetic toward badges, while still providing a substantial number of contributions to the site. An interesting statistical phenomenon, termed "Phantom Steering," accounts for the interaction data of these users and this may have contributed to some previous conclusions about steering. Our results suggest that a small population, approximately 20%, of users respond to the badge incentives. Moreover, we conduct a qualitative survey of the users on Stack Overflow which provides further evidence that the insights from the model reflect the true behavior of the community. We argue that while badges might contribute toward a suite of effective rewards in an online system, research into other aspects of reward systems such as Stack Overflow reputation points should become a focus of the community. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.06160v2-abstract-full').style.display = 'none'; document.getElementById('2002.06160v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 August, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 14 February, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">To appear in IEEE ICDM2020</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1810.01834">arXiv:1810.01834</a> <span> [<a href="https://arxiv.org/pdf/1810.01834">pdf</a>, <a href="https://arxiv.org/ps/1810.01834">ps</a>, <a href="https://arxiv.org/format/1810.01834">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Data Structures and Algorithms">cs.DS</span> </div> </div> <p class="title is-5 mathjax"> Reverse Greedy is Bad for k-Center </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Hershkowitz%2C+D+E">D Ellis Hershkowitz</a>, <a href="/search/cs?searchtype=author&query=Kehne%2C+G">Gregory Kehne</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1810.01834v5-abstract-short" style="display: inline;"> We show the reverse greedy algorithm is between a $(2k-2)$- and a $2k$-approximation for $k$-center. </span> <span class="abstract-full has-text-grey-dark mathjax" id="1810.01834v5-abstract-full" style="display: none;"> We show the reverse greedy algorithm is between a $(2k-2)$- and a $2k$-approximation for $k$-center. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1810.01834v5-abstract-full').style.display = 'none'; document.getElementById('1810.01834v5-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 December, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 3 October, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Fixed a couple minor typos</span> </p> </li> </ol> <div class="is-hidden-tablet"> <!-- feedback for mobile only --> <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a> </span> </div> </div> </main> <footer> <div class="columns is-desktop" role="navigation" aria-label="Secondary"> <!-- MetaColumn 1 --> <div class="column"> <div class="columns"> <div class="column"> <ul class="nav-spaced"> <li><a href="https://info.arxiv.org/about">About</a></li> <li><a href="https://info.arxiv.org/help">Help</a></li> </ul> </div> <div class="column"> <ul class="nav-spaced"> <li> <svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" class="icon filter-black" role="presentation"><title>contact arXiv</title><desc>Click here to contact arXiv</desc><path d="M502.3 190.8c3.9-3.1 9.7-.2 9.7 4.7V400c0 26.5-21.5 48-48 48H48c-26.5 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