Scholars@Duke

• Background
• 

  Education, Training, & Certifications

  • Ph.D., Stanford University 2003
  • M.S., Stanford University 2002
• 

  Previous Appointments & Affiliations

  • Associate Professor of Computer Science, Computer Science, Trinity College of Arts & Sciences 2011 - 2016
  • Director of Graduate Studies of Computer Science, Computer Science, Trinity College of Arts & Sciences 2012 - 2015
  • Associate Director of Graduate Studies of the Master, Computer Science, Trinity College of Arts & Sciences 2014 - 2015
  • Assistant Professor of Computer Science, Computer Science, Trinity College of Arts & Sciences 2004 - 2010
• Recognition
• 

  Awards & Honors

  • Sloan Research Fellowship-Computer Science. Alfred P. Sloan Foundation. 2009
  • Faculty Early Career Development (CAREER) Program. National Science Foundation. 2008
• Research
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  Selected Grants

  • AF: Small: Algorithm and Incentive Design for Modern Resource Allocation Platforms awarded by  National Science Foundation 2021 - 2024
  • HDR TRIPODS: Innovations in Data Science: Integrating Stochastic Modeling, Data Representation, and Algorithms awarded by  National Science Foundation 2019 - 2023
  • Game-theoretic mechanisms for group decision making awarded by Stanford University 2019 - 2022
  • Automated Moderation of Small Group Deliberation awarded by Stanford University 2019 - 2021
  • AitF: Collaborative Research: Fair and Efficient Societal Decision Making via Collaborative Convex Optimization awarded by  National Science Foundation 2016 - 2021
  • BIGDATA: F: DKA: Collaborative Research: Sublinear Approach to Big Social Data Problems awarded by  National Science Foundation 2014 - 2020
  • AF: Medium: Collaborative Research: Multi-dimensional Scheduling and Resource Allocation in Data Centers awarded by  National Science Foundation 2014 - 2020
  • Foundations of Sequential Learning awarded by Defense Advanced Research Projects Agency 2016 - 2017
  • CCF:AF:EAGER Algorithmic Paradigms for Big Data Computation awarded by  National Science Foundation 2013 - 2015
  • Information Dynamics in Networks: Models and Algorithms awarded by Army Research Office 2014 - 2015
  • AF:Small:Auction Design in Constrained Settings awarded by  National Science Foundation 2010 - 2015
  • Simplifying Database Management with Automated Experimentation awarded by  National Science Foundation 2010 - 2015
  • CAREER: Light-weight Near-optimal Stochastic Control Policies for Information Acquisition and Exploitation awarded by  National Science Foundation 2008 - 2015
  • missing activity
• Publications & Artistic Works
• 

  Selected Publications

  • Academic Articles

    • Alijani, R., Banerjee, S., Munagala, K., & Wang, K. (2022). The Limits of an Information Intermediary in Auction Design. Ec 2022  Proceedings of the 23rd Acm Conference on Economics and Computation, 849–868. https://doi.org/10.1145/3490486.3538370
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    • Lyu, L., Fain, B., Munagala, K., & Wang, K. (2021). Centrality with Diversity. Wsdm 2021  Proceedings of the 14th Acm International Conference on Web Search and Data Mining, 644–652. https://doi.org/10.1145/3437963.3441789
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    • Munagala, K., Shen, Z., & Wang, K. (2021). Optimal Algorithms for Multiwinner Elections and the Chamberlin-Courant Rule. Ec 2021  Proceedings of the 22nd Acm Conference on Economics and Computation, 697–717. https://doi.org/10.1145/3465456.3467624
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    • Agarwal, P. K., Chang, H. C., Munagala, K., Taylor, E., & Welzl, E. (2020). Clustering under perturbation stability in near-linear time. Leibniz International Proceedings in Informatics, Lipics, 182. https://doi.org/10.4230/LIPIcs.FSTTCS.2020.8
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    • Alijani, R., Banerjee, S., Gollapudi, S., Munagala, K., & Wang, K. (2020). Predict and Match: Prophet Inequalities with Uncertain Supply. Performance Evaluation Review, 48(1), 13–14. https://doi.org/10.1145/3393691.3394212
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    • Im, S., Moseley, B., Munagala, K., & Pruhs, K. (2020). Dynamic Weighted Fairness with Minimal Disruptions. Sigmetrics Performance 2020  Abstracts of the 2020 Sigmetrics/Performance Joint International Conference on Measurement and Modeling of Computer Systems, 5–6. https://doi.org/10.1145/3393691.3394184
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    • Jiang, Z., Munagala, K., & Wang, K. (2020). Approximately stable committee selection. Proceedings of the Annual Acm Symposium on Theory of Computing, 463–472. https://doi.org/10.1145/3357713.3384238
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    • Fain, B., Fan, W., & Munagala, K. (2020). Concentration of distortion: The value of extra voters in randomized social choice. Ijcai International Joint Conference on Artificial Intelligence, 2021-January, 110–116.
    • Alijani, R., Banerjee, S., Gollapudi, S., Kollias, K., & Munagala, K. (2019). The Segmentation-Thickness Tradeoff in Online Marketplaces. Proceedings of the Acm on Measurement and Analysis of Computing Systems, 3(1), 1–26. https://doi.org/10.1145/3322205.3311089
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    • Garg, N., Kamble, V., Goel, A., Marn, D., & Munagala, K. (2019). Iterative local voting for collective decision-making in continuous spaces. Journal of Artificial Intelligence Research, 64, 315–355. https://doi.org/10.1613/jair.1.11358
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    • Chen, X., Fain, B., Lyu, L., & Munagala, K. (2019). Proportionally fair clustering. 36th International Conference on Machine Learning, Icml 2019, 2019-June, 1782–1791.
    • Sungjin, I. M., Munagala, K., & Kulkarni, J. (2017). Competitive algorithms from competitive equilibria: Non-clairvoyant scheduling under polyhedral constraints. Journal of the Acm, 65(1). https://doi.org/10.1145/3136754
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    • Haghpanah, N., Immorlica, N., Mirrokni, V., & Munagala, K. (2013). Optimal Auctions with Positive Network Externalities. Acm Transactions on Economics and Computation, 1(2), 1–24. https://doi.org/10.1145/2465769.2465778
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    • Haghpanah, N., Immorlica, N., Mirrokni, V., & Munagala, K. (2012). How to approximate optimal auctions. Acm Sigecom Exchanges, 11(1), 30–33. https://doi.org/10.1145/2325713.2325719
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    • Manweiler, J., Santhapuri, N., Sen, S., Choudhury, R. R., Nelakuditi, S., & Munagala, K. (2012). Order matters: Transmission reordering in wireless networks. Ieee/Acm Transactions on Networking, 20(2), 353–366. https://doi.org/10.1109/TNET.2011.2164264
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    • Guha, S., & Munagala, K. (2012). Adaptive uncertainty resolution in bayesian combinatorial optimization problems. Acm Transactions on Algorithms, 8(1). https://doi.org/10.1145/2071379.2071380
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    • Ahmad, M., Aboulnaga, A., Babu, S., & Munagala, K. (2011). Interaction-aware scheduling of report-generation workloads. Vldb Journal, 20(4), 589–615. https://doi.org/10.1007/s00778-011-0217-y
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    • Guha, S., Munagala, K., & Shi, P. (2010). Approximation algorithms for restless bandit problems. Journal of the Acm, 58(1). https://doi.org/10.1145/1870103.1870106
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    • Goel, A., Guha, S., & Munagala, K. (2010). How to probe for an extreme value. Acm Transactions on Algorithms, 7(1). https://doi.org/10.1145/1868237.1868250
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    • Guha, S., Meyerson, A., & Munagala, K. (2009). A constant factor approximation for the single sink edge installation problem. Siam Journal on Computing, 38(6), 2426–2442. https://doi.org/10.1137/050643635
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    • Ahmad, M., Aboulnaga, A., Babu, S., & Munagala, K. (2008). QShuffler: Getting the query mix right. Proceedings  International Conference on Data Engineering, 1415–1417. https://doi.org/10.1109/ICDE.2008.4497574
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    • Guha, S., Munagala, K., & Sarkar, S. (2008). Information Acquisition and Exploitation in Multichannel Wireless Networks.
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    • Meyerson, A., Munagala, K., & Plotkin, S. (2008). Cost-Distance: Two Metric Network Design. Siam Journal on Computing, 38(4), 1648–1659. https://doi.org/10.1137/050629665
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    • Goel, A., Guha, S., & Munagala, K. (2006). Asking the right questions: Model-driven optimization using probes. Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems, 203–212. https://doi.org/10.1145/1142351.1142380
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    • Silberstein, A., Munagala, K., & Yang, J. (2006). Energy-efficient monitoring of extreme values in sensor networks. Proceedings of the Acm Sigmod International Conference on Management of Data, 169–180. https://doi.org/10.1145/1142473.1142493
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    • Silberstein, A., Braynard, R., Ellis, C., Munagala, K., & Yang, J. (2006). A sampling-based approach to optimizing top-k queries in sensor networks. Proceedings  International Conference on Data Engineering, 2006, 68. https://doi.org/10.1109/ICDE.2006.10
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    • Guha, S., Munagala, K., & Sarkar, S. (2006). Optimizing transmission rate in wireless channels using adaptive probes. Performance Evaluation Review, 34(1), 381–382. https://doi.org/10.1145/1140103.1140330
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    • Flikkema, P. G., Agarwal, P. K., Clark, J. S., Ellis, C., Gelfand, A., Munagala, K., & Yang, J. (2006). Model-driven dynamic control of embedded wireless sensor networks. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3993 LNCS-III, 409–416. https://doi.org/10.1007/11758532_55
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    • Babu, S., Munagala, K., Widom, J., & Motwani, R. (2005). Adaptive caching for continuous queries. Proceedings  International Conference on Data Engineering, 118–129. https://doi.org/10.1109/ICDE.2005.15
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    • Munagala, K., Babu, S., Motwani, R., & Widom, J. (2005). The pipelined set cover problem. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3363 LNCS, 83–98. https://doi.org/10.1007/978-3-540-30570-5_6
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    • Srivastaya, U., Munagala, K., & Widom, J. (2005). Operator placement for in-network stream query processing. Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems, 250–258.
    • Munagala, K., Yang, J., & Yu, H. (2005). Online view maintenance under a response-time constraint. Lecture Notes in Computer Science, 3669, 677–688. https://doi.org/10.1007/11561071_60
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    • Arya, V., Garg, N., Khandekar, R., Meyerson, A., Munagala, K., & Pandit, V. (2004). Local search heuristics for k-median and facility location problems. Siam Journal on Computing, 33(3), 544–562. https://doi.org/10.1137/S0097539702416402
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    • Munagala, K., Tibshirani, R., & Brown, P. O. (2004). Cancer characterization and feature set extraction by discriminative margin clustering. Bmc Bioinformatics, 5, 21. https://doi.org/10.1186/1471-2105-5-21
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    • Babu, S., Motwani, R., Munagala, K., Nishizawa, I., & Widom, J. (2004). Adaptive ordering of pipelined stream filters. Proceedings of the Acm Sigmod International Conference on Management of Data, 407–418. https://doi.org/10.1145/1007568.1007615
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    • Guha, S., Krishnan, S., Munagala, K., & Venkatasubramanian, S. (2003). Application of the two-sided depth test to CSG rendering. Proceedings of the Symposium on Interactive 3d Graphics, 177–180. https://doi.org/10.1145/641508.641513
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    • Guha, S., Meyerson, A., & Munagala, K. (2003). A constant factor approximation algorithm for the fault-tolerant facility location problem. Journal of Algorithms, 48(2), 429–440. https://doi.org/10.1016/S0196-6774(03)00056-7
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    • Goel, A., & Munagala, K. (2002). Extending greedy multicast routing to delay sensitive applications. Algorithmica (New York), 33(3), 335–352. https://doi.org/10.1007/s00453-001-0122-7
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  • Book Sections

    • Yang, J., Munagala, K., & Silberstein, A. (2018). Data Aggregation in Sensor Networks. In Encyclopedia of Database Systems (pp. 725–730). Springer New York. https://doi.org/10.1007/978-1-4614-8265-9_93
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    • Munagala, K. (2016). Local Search for K-medians and Facility Location. In Encyclopedia of Algorithms (pp. 1139–1143). Springer New York. https://doi.org/10.1007/978-1-4939-2864-4_212
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    • Yang, J., Munagala, K., & Silberstein, A. (2009). Data Aggregation in Sensor Networks. In Encyclopedia of Database Systems (pp. 552–557). Springer US. https://doi.org/10.1007/978-0-387-39940-9_93
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    • Munagala, K. (2008). Local Search for K-medians and Facility Location. In Encyclopedia of Algorithms (pp. 470–473). Springer US. https://doi.org/10.1007/978-0-387-30162-4_212
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  • Reports

    • Guha, S., & Munagala, K. (2013). Approximation Algorithms for Bayesian Multi-Armed Bandit Problems.
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    • Goel, A., & Munagala, K. (2012). Complexity Measures for Map-Reduce, and Comparison to Parallel Computing.
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  • Conference Papers

    • Ko, S. H., & Munagala, K. (2022). Optimal Price Discrimination for Randomized Mechanisms. In Ec 2022  Proceedings of the 23rd Acm Conference on Economics and Computation (pp. 477–496). https://doi.org/10.1145/3490486.3538335
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    • Munagala, K., Shen, Y., & Wang, K. (2022). Auditing for Core Stability in Participatory Budgeting. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13778 LNCS, pp. 292–310). https://doi.org/10.1007/978-3-031-22832-2_17
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    • Munagala, K., Shen, Y., Wang, K., & Wang, Z. (2022). Approximate Core for Committee Selection via Multilinear Extension and Market Clearing. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (Vol. 2022-January, pp. 2229–2252).
    • Cheng, Y., Gravin, N., Munagala, K., & Wang, K. (2021). A Simple Mechanism for a Budget-Constrained Buyer. In Acm Transactions on Economics and Computation (Vol. 9). https://doi.org/10.1145/3434419
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    • Shen, Z., Gelauff, L., Goel, A., Korolova, A., & Munagala, K. (2021). Robust Allocations with Diversity Constraints. In Advances in Neural Information Processing Systems (Vol. 35, pp. 29684–29696).
    • Cheng, Y., Jiang, Z., Munagala, K., & Wang, K. (2020). Group Fairness in Committee Selection. In Acm Transactions on Economics and Computation (Vol. 8). https://doi.org/10.1145/3417750
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    • Im, S., Moseley, B., Munagala, K., & Pruhs, K. (2020). Dynamic Weighted Fairness with Minimal Disruptions. In Performance Evaluation Review (Vol. 48, pp. 5–6). https://doi.org/10.1145/3393691.3379485
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    • Bhaskara, A., Gollapudi, S., Kollias, K., & Munagala, K. (2020). Adaptive probing policies for shortest path routing. In Advances in Neural Information Processing Systems (Vol. 2020-December).
    • Alijani, R., Banerjee, S., Gollapudi, S., Kollias, K., & Munagala, K. (2019). The Segmentation-Thickness Tradeoff in Online Marketplaces. In Performance Evaluation Review (Vol. 47, pp. 31–32). https://doi.org/10.1145/3309697.3331519
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    • Cheng, Y., Jiang, Z., Munagala, K., & Wang, K. (2019). Group fairness in committee selection. In Acm Ec 2019  Proceedings of the 2019 Acm Conference on Economics and Computation (pp. 263–279). https://doi.org/10.1145/3328526.3329577
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    • Munagala, K., & Wang, K. (2019). Improved metric distortion for deterministic social choice rules. In Acm Ec 2019  Proceedings of the 2019 Acm Conference on Economics and Computation (pp. 245–262). https://doi.org/10.1145/3328526.3329550
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    • Chen, X., Fain, B., Lyu, L., & Munagala, K. (2019). Proportionally Fair Clustering. In K. Chaudhuri & R. Salakhutdinov (Eds.), Icml (Vol. 97, pp. 1032–1041). PMLR.
    • Fain, B., Goel, A., Munagala, K., & Prabhu, N. (2019). Random dictators with a random referee: Constant sample complexity mechanisms for social choice. In 33rd Aaai Conference on Artificial Intelligence, Aaai 2019, 31st Innovative Applications of Artificial Intelligence Conference, Iaai 2019 and the 9th Aaai Symposium on Educational Advances in Artificial Intelligence, Eaai 2019 (pp. 1893–1900).
    • Fain, B., Munagala, K., & Shah, N. (2018). Fair allocation of indivisible public goods. In Acm Ec 2018  Proceedings of the 2018 Acm Conference on Economics and Computation (pp. 575–592). https://doi.org/10.1145/3219166.3219174
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    • Agarwal, P. K., Fox, K., Munagala, K., Nath, A., Pan, J., & Taylor, E. (2018). Subtrajectory clustering: Models and algorithms. In Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems (pp. 75–87). https://doi.org/10.1145/3196959.3196972
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    • Cheng, Y., Gravin, N., Munagala, K., & Wang, K. (2018). A simple mechanism for a budget-constrained buyer. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11316 LNCS, pp. 96–110). https://doi.org/10.1007/978-3-030-04612-5_7
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    • Goel, A., Krishnaswamy, A. K., & Munagala, K. (2017). Metric distortion of social choice rules: Lower bounds and fairness properties. In Ec 2017  Proceedings of the 2017 Acm Conference on Economics and Computation (pp. 287–304). https://doi.org/10.1145/3033274.3085138
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    • Kunjir, M., Fain, B., Munagala, K., & Babu, S. (2017). ROBUS: Fair cache allocation for data-parallel workloads. In Proceedings of the Acm Sigmod International Conference on Management of Data (Vol. Part F127746, pp. 219–234). https://doi.org/10.1145/3035918.3064018
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    • Banerjee, S., Gollapudi, S., Kollias, K., & Munagala, K. (2017). Segmenting two-sided markets. In 26th International World Wide Web Conference, Www 2017 (pp. 63–72). https://doi.org/10.1145/3038912.3052578
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    • Fain, B., Goel, A., Munagala, K., & Sakshuwong, S. (2017). Sequential deliberation for social choice. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10660 LNCS, pp. 177–190). https://doi.org/10.1007/978-3-319-71924-5_13
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    • Garg, N., Kamble, V., Goel, A., Marn, D., & Munagala, K. (2017). Collaborative optimization for collective decision-making in continuous spaces. In 26th International World Wide Web Conference, Www 2017 (pp. 617–626). https://doi.org/10.1145/3038912.3052690
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    • Kunjir, M., Fain, B., Munagala, K., & Babu, S. (2017). ROBUS: Fair Cache Allocation for Data-parallel Workloads. In S. Salihoglu, W. Zhou, R. Chirkova, J. Yang, & D. Suciu (Eds.), Sigmod Conference (pp. 219–234). ACM.
    • Nath, A., Fox, K., Agarwal, P. K., & Munagala, K. (2016). Massively parallel algorithms for computing TIN DEMs and contour trees for large terrains. In Gis: Proceedings of the Acm International Symposium on Advances in Geographic Information Systems. https://doi.org/10.1145/2996913.2996952
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    • Im, S., Kulkarni, J., & Munagala, K. (2016). Competitive analysis of constrained queueing systems. In Leibniz International Proceedings in Informatics, Lipics (Vol. 55). https://doi.org/10.4230/LIPIcs.ICALP.2016.143
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    • Agarwal, P. K., Fox, K., Munagala, K., & Nath, A. (2016). Parallel algorithms for constructing range and nearest-neighbor searching data structures. In Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems (Vol. 26-June-01-July-2016, pp. 429–440). https://doi.org/10.1145/2902251.2902303
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    • Fain, B., Goel, A., & Munagala, K. (2016). The core of the participatory budgeting problem. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10123 LNCS, pp. 384–399). https://doi.org/10.1007/978-3-662-54110-4_27
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    • Im, S., Kulkarni, J., Moseley, B., & Munagala, K. (2016). A Competitive Flow Time Algorithm for Heterogeneous Clusters Under Polytope Constraints. In K. Jansen, C. Mathieu, J. D. P. Rolim, & C. Umans (Eds.), Approx Random (Vol. 60, pp. 10:1-10:1). Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik.
    • Im, S., Kulkarni, J., & Munagala, K. (2015). Competitive Flow Time Algorithms for Polyhedral Scheduling. In Proceedings  Annual Ieee Symposium on Foundations of Computer Science, Focs (Vol. 2015-December, pp. 506–524). https://doi.org/10.1109/FOCS.2015.38
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    • Cao, Q., Sirivianos, M., Yang, X., & Munagala, K. (2015). Combating Friend Spam Using Social Rejections. In Proceedings  International Conference on Distributed Computing Systems (Vol. 2015-July, pp. 235–244). https://doi.org/10.1109/ICDCS.2015.32
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    • Goel, A., Munagala, K., Sharma, A., & Zhang, H. (2015). A note on modeling retweet cascades on Twitter. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9479, pp. 119–131). https://doi.org/10.1007/978-3-319-26784-5_10
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    • Im, S., Kulkarni, J., Munagala, K., & Pruhs, K. (2014). SelfishMigrate: A scalable algorithm for non-clairvoyantly scheduling heterogeneous processors. In Proceedings  Annual Ieee Symposium on Foundations of Computer Science, Focs (pp. 531–540). https://doi.org/10.1109/FOCS.2014.63
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    • Bahmani, B., Goel, A., & Munagala, K. (2014). Efficient primal-dual graph algorithms for MapReduce. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8882, pp. 59–78). https://doi.org/10.1007/978-3-319-13123-8_6
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    • Bhattacharya, S., Im, S., Kulkarni, J., & Munagala, K. (2014). Coordination mechanisms from (almost) all scheduling policies. In Itcs 2014  Proceedings of the 2014 Conference on Innovations in Theoretical Computer Science (pp. 121–133). https://doi.org/10.1145/2554797.2554811
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    • Das, A., Gollapudi, S., & Munagala, K. (2014). Modeling opinion dynamics in social networks. In Wsdm 2014  Proceedings of the 7th Acm International Conference on Web Search and Data Mining (pp. 403–412). https://doi.org/10.1145/2556195.2559896
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    • Guha, S., & Munagala, K. (2014). Stochastic regret minimization via Thompson Sampling. In Journal of Machine Learning Research (Vol. 35, pp. 317–338).
    • Im, S., Kulkarni, J., & Munagala, K. (2014). Competitive algorithms from competitive equilibria: Non-clairvoyant scheduling under polyhedral constraints. In Proceedings of the Annual Acm Symposium on Theory of Computing (pp. 313–322). https://doi.org/10.1145/2591796.2591814
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    • Im, S., Kulkarni, J., & Munagala, K. (2014). Competitive algorithms from competitive equilibria: non-clairvoyant scheduling under polyhedral constraints. In D. B. Shmoys (Ed.), Stoc (pp. 313–322). ACM.
    • Munagala, K., & Xu, X. (2014). Value-based network externalities and optimal auction design. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8877, pp. 147–160). https://doi.org/10.1007/978-3-319-13129-0_11
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    • Kulkarni, J., & Munagala, K. (2013). Algorithms for cost-aware scheduling. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7846 LNCS, pp. 201–214). https://doi.org/10.1007/978-3-642-38016-7_17
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    • Guha, S., & Munagala, K. (2013). Approximate indexability and bandit problems with concave rewards and delayed feedback. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8096 LNCS, pp. 189–204). https://doi.org/10.1007/978-3-642-40328-6_14
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    • Bhawalkar, K., Gollapudi, S., & Munagala, K. (2013). Coevolutionary opinion formation games. In Proceedings of the Annual Acm Symposium on Theory of Computing (pp. 41–50). https://doi.org/10.1145/2488608.2488615
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    • Bhalgat, A., Gollapudi, S., & Munagala, K. (2013). Optimal auctions via the multiplicative weight method. In M. J. Kearns, R. P. McAfee, & É. Tardos (Eds.), Ec (pp. 73–90). ACM.
    • Bosagh Zadeh, R., Goel, A., Munagala, K., & Sharma, A. (2013). On the precision of social and information networks. In Cosn 2013  Proceedings of the 2013 Conference on Online Social Networks (pp. 63–74). https://doi.org/10.1145/2512938.2512955
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    • Bhalgat, A., Gollapudi, S., & Munagala, K. (2012). Mechanisms and allocations with positive network externalities. In Proceedings of the Acm Conference on Electronic Commerce (pp. 179–196). https://doi.org/10.1145/2229012.2229029
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    • Bhattacharya, S., Gollapudi, S., & Munagala, K. (2011). Consideration set generation in commerce search. In Proceedings of the 20th International Conference on World Wide Web, Www 2011 (pp. 317–326). https://doi.org/10.1145/1963405.1963452
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    • Zhang, Y., Munagala, K., & Yang, J. (2011). Storing matrices on disk: Theory and practice revisited. In Proceedings of the Vldb Endowment (Vol. 4, pp. 1075–1086).
    • Haghpanah, N., Immorlica, N., Mirrokni, V., & Munagala, K. (2011). Optimal auctions with positive network externalities. In Proceedings of the Acm Conference on Electronic Commerce (pp. 11–20). https://doi.org/10.1145/1993574.1993577
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    • Bhattacharya, S., Conitzer, V., & Munagala, K. (2011). Approximation algorithm for security games with costly resources. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7090 LNCS, pp. 13–24). https://doi.org/10.1007/978-3-642-25510-6_2
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    • Bhattacharya, S., Kulkarni, J., Munagala, K., & Xu, X. (2011). On Allocations with Negative Externalities. In N. Chen, E. Elkind, & E. Koutsoupias (Eds.), Wine (Vol. 7090, pp. 25–36). Springer.
    • Bhattacharya, S., Kulkarni, J., Munagala, K., & Xu, X. (2011). On allocations with negative externalities. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7090 LNCS, pp. 25–36). https://doi.org/10.1007/978-3-642-25510-6_3
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    • Conitzer, V., Immorlica, N., Letchford, J., Munagala, K., & Wagman, L. (2010). False-name-proofness in social networks. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6484 LNCS, pp. 209–221). https://doi.org/10.1007/978-3-642-17572-5_17
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    • Bhattacharya, S., Goel, G., Gollapudi, S., & Munagala, K. (2010). Budget constrained auctions with heterogeneous items. In Proceedings of the Annual Acm Symposium on Theory of Computing (pp. 379–387). https://doi.org/10.1145/1806689.1806743
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    • Bhattacharya, S., Conitzer, V., Munagala, K., & Xia, L. (2010). Incentive compatible budget elicitation in multi-unit auctions. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (pp. 554–572). https://doi.org/10.1137/1.9781611973075.47
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    • Letchford, J., Conitzer, V., & Munagala, K. (2009). Learning and approximating the optimal strategy to commit to. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5814 LNCS, pp. 250–262). https://doi.org/10.1007/978-3-642-04645-2_23
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    • Goel, A., & Munagala, K. (2009). Hybrid keyword search auctions. In Www’09  Proceedings of the 18th International World Wide Web Conference (pp. 221–230). https://doi.org/10.1145/1526709.1526740
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    • Manweiler, J., Santhapuri, N., Sen, S., Choudhury, R. R., Nelakuditi, S., & Munagala, K. (2009). Order matters: Transmission reordering in wireless networks. In Proceedings of the Annual International Conference on Mobile Computing and Networking, Mobicom (pp. 61–72). https://doi.org/10.1145/1614320.1614328
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    • Guha, S., & Munagala, K. (2009). Multi-armed bandits with metric switching costs. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5556 LNCS, pp. 496–507). https://doi.org/10.1007/978-3-642-02930-1_41
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    • Guha, S., & Munagala, K. (2009). Exceeding expectations and clustering uncertain data. In Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems (pp. 269–277). https://doi.org/10.1145/1559795.1559836
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    • Duan, S., Babu, S., & Munagala, K. (2009). Fa: A system for automating failure diagnosis. In Proceedings  International Conference on Data Engineering (pp. 1012–1023). https://doi.org/10.1109/ICDE.2009.115
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    • Babu, S., Guha, S., & Munagala, K. (2009). Large-scale uncertainty management systems: Learning and exploiting your data. In Sigmod Pods’09  Proceedings of the International Conference on Management of Data and 28th Symposium on Principles of Database Systems (pp. 995–998). https://doi.org/10.1145/1559845.1559964
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    • Guha, S., Munagala, K., & Shi, P. (2009). Approximation algorithms for restless bandit problems. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (pp. 28–37). https://doi.org/10.1137/1.9781611973068.4
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    • Ahmad, M., Aboulanaga, A., Babu, S., & Munagala, K. (2008). Modeling and exploiting query interactions in database systems. In International Conference on Information and Knowledge Management, Proceedings (pp. 183–192). https://doi.org/10.1145/1458082.1458109
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    • Babu, S., Duan, S., & Munagala, K. (2008). Processing diagnosis queries: A principled and scalable approach. In Proceedings  International Conference on Data Engineering (pp. 1468–1470). https://doi.org/10.1109/ICDE.2008.4497592
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    • Munagala, K., & Shi, P. (2008). The stochastic machine replenishment problem. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5035 LNCS, pp. 169–183). https://doi.org/10.1007/978-3-540-68891-4_12
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    • Santhapuri, N., Manweiler, J., Sen, S., Choudhury, R. R., Nelakuduti, S., & Munagala, K. (2008). Message in Message (MIM): A Case for Reordering Transmissions in Wireless Networks. In 7th Acm Workshop on Hot Topics in Networks, Hotnets 2008 (pp. 25–30).
    • Guha, S., & Munagala, K. (2007). Approximation algorithms for partial-information based stochastic control with Markovian rewards. In Proceedings  Annual Ieee Symposium on Foundations of Computer Science, Focs (pp. 483–493). https://doi.org/10.1109/FOCS.2007.4389518
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    • Silberstein, A., Braynard, R., Filpus, G., Puggioni, G., Gelfand, A., Munagala, K., & Yang, J. (2007). Data-driven processing in sensor networks. In Cidr 2007  3rd Biennial Conference on Innovative Data Systems Research (pp. 10–21).
    • Guha, S., & Munagala, K. (2007). Approximation algorithms for budgeted learning problems. In Proceedings of the Annual Acm Symposium on Theory of Computing (pp. 104–113). https://doi.org/10.1145/1250790.1250807
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    • Munagala, K., Srivastava, U., & Widom, J. (2007). Optimization of continuous queries with shared expensive filters. In Proceedings of the Acm Sigact Sigmod Sigart Symposium on Principles of Database Systems (pp. 215–224). https://doi.org/10.1145/1265530.1265561
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    • Fischer, E., Matsliah, A., & Shapira, A. (2007). Approximate Hypergraph Partitioning and Applications. In 48th Annual Ieee Symposium on Foundations of Computer Science (Focs’07). IEEE. https://doi.org/10.1109/focs.2007.12
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    • Guha, S., & Munagala, K. (2007). Approximation Algorithms for Partial-Information Based Stochastic Control with Markovian Rewards. In 48th Annual Ieee Symposium on Foundations of Computer Science (Focs’07). IEEE. https://doi.org/10.1109/focs.2007.23
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    • Flikkema, P. G., Agarwal, P. K., Clark, J. S., Ellis, C., Gelfand, A., Munagala, K., & Yang, J. (2007). From data reverence to data relevance: Model-mediated wireless sensing of the physical environment. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4487 LNCS, pp. 988–994). https://doi.org/10.1007/978-3-540-72584-8_130
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    • Guha, S., & Munagala, K. (2007). Model-driven optimization using adaptive probes. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (Vol. 07-09-January-2007, pp. 308–317).
    • Silberstein, A., Gelfand, A. E., Munagala, K., Puggioni, G., & Yang, J. (2007). Making Sense of Suppressions and Failures in Sensor Data: A Bayesian Approach. In C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, … E. J. Neuhold (Eds.), Vldb (pp. 842–853). ACM.
    • Silberstein, A., Puggioni, G., Gelfand, A., Munagala, K., & Yang, J. (2007). Suppression and failures in sensor networks: A Bayesian approach. In 33rd International Conference on Very Large Data Bases, Vldb 2007  Conference Proceedings (pp. 842–853).
    • Guha, S., Munagala, K., & Sarkar, S. (2006). Approximation Schemes for Information Acquisition and Exploitation in Multichannel Wireless Networks. In 44th Annual Allerton Conference on Communication, Control, and Computing 2006 (Vol. 1, pp. 85–90).
    • Guha, S., Munagala, K., & Sarkar, S. (2006). Jointly optimal transmission and probing strategies for multichannel wireless systems. In 2006 Ieee Conference on Information Sciences and Systems, Ciss 2006  Proceedings (pp. 955–960). https://doi.org/10.1109/CISS.2006.286604
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    • Guha, S., Munagala, K., & Sarkar, S. (2006). Optimizing transmission rate in wireless channels using adaptive probes. In R. A. Marie, P. B. Key, & E. Smirni (Eds.), Sigmetrics/Performance (pp. 381–382). ACM.
    • Srivastava, U., Munagala, K., Widom, J., & Motwani, R. (2006). Query optimization over Web Services. In Vldb 2006  Proceedings of the 32nd International Conference on Very Large Data Bases (pp. 355–366).
    • Guha, S., & Munagala, K. (2002). Improved algorithms for the data placement problem. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (Vol. 06-08-January-2002, pp. 106–107).
    • Guha, S., & Munagala, K. (2002). Generalized clustering. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (Vol. 06-08-January-2002, pp. 484–485).
    • Guha, S., Meyerson, A., & Munagala, K. (2001). Improved algorithms for fault tolerant facility location. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (pp. 636–641).
    • Meyerson, A., Munagala, K., & Plotkin, S. (2001). Web caching using access statistics. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (pp. 354–363).
    • Guha, S., Meyerson, A., & Munagala, K. (2001). A constant factor approximation for the single sink edge installation problem. In Conference Proceedings of the Annual Acm Symposium on Theory of Computing (pp. 383–388).
    • Arya, V., Garg, N., Khandekar, R., Meyerson, A., Munagala, K., & Pandit, V. (2001). Local search heuristics for k-median and facility location problems. In Conference Proceedings of the Annual Acm Symposium on Theory of Computing (pp. 21–29).
    • Meyerson, A., Munagala, K., & Plotkin, S. (2001). Designing networks incrementally. In Annual Symposium on Foundations of Computer Science  Proceedings (pp. 406–415). https://doi.org/10.1109/sfcs.2001.959915
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    • Guha, S., Meyerson, A., & Munagala, K. (2000). Hierarchical placement and network design problems. In Annual Symposium on Foundations of Computer Science  Proceedings (pp. 603–612).
    • Meyerson, A., Munagala, K., & Plotkin, S. (2000). COST-DISTANCE: Two metric network design. In Annual Symposium on Foundations of Computer Science  Proceedings (pp. 624–630).
    • Andrews, M., & Munagala, K. (2000). Online algorithms for caching multimedia streams. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1879, pp. 64–75). https://doi.org/10.1007/3-540-45253-2_7
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    • Goel, A., & Munagala, K. (2000). Balancing Steiner trees and shortest path trees online. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (pp. 562–563).
    • Munagala, K., & Ranade, A. (1999). I/O-complexity of graph algorithms. In Proceedings of the Annual Acm Siam Symposium on Discrete Algorithms (pp. 687–694).

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