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2020 – today
- 2023
[j27]Manish Raghavan
, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
Greedy Algorithm Almost Dominates in Smoothed Contextual Bandits. SIAM J. Comput. 52(2): 487-524 (2023)- [c59]Aleksandrs Slivkins, Karthik Abinav Sankararaman, Dylan J. Foster:
Contextual Bandits with Packing and Covering Constraints: A Modular Lagrangian Approach via Regression. COLT 2023: 4633-4656 - [c58]Jason Gaitonde, Yingkai Li, Bar Light, Brendan Lucier, Aleksandrs Slivkins:
Budget Pacing in Repeated Auctions: Regret and Efficiency Without Convergence. ITCS 2023: 52:1-52:1 - [i58]Brendan Lucier, Sarath Pattathil, Aleksandrs Slivkins, Mengxiao Zhang:
Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics. CoRR abs/2301.13306 (2023) - [i57]Kiarash Banihashem, MohammadTaghi Hajiaghayi, Suho Shin, Aleksandrs Slivkins:
Bandit Social Learning: Exploration under Myopic Behavior. CoRR abs/2302.07425 (2023) - [i56]Lequn Wang, Akshay Krishnamurthy, Aleksandrs Slivkins:
Oracle-Efficient Pessimism: Offline Policy Optimization in Contextual Bandits. CoRR abs/2306.07923 (2023) - [i55]Yiding Feng, Brendan Lucier, Aleksandrs Slivkins:
Strategic Budget Selection in a Competitive Autobidding World. CoRR abs/2307.07374 (2023) - [i54]Keegan Harris, Nicole Immorlica, Brendan Lucier, Aleksandrs Slivkins:
Algorithmic Persuasion Through Simulation: Information Design in the Age of Generative AI. CoRR abs/2311.18138 (2023) - 2022
- [j26]Yishay Mansour, Alex Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu:
Bayesian Exploration: Incentivizing Exploration in Bayesian Games. Oper. Res. 70(2): 1105-1127 (2022) - [j25]Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins:
Adversarial Bandits with Knapsacks. J. ACM 69(6): 40:1-40:47 (2022) - [c57]Xinyan Hu, Dung Daniel T. Ngo, Aleksandrs Slivkins, Zhiwei Steven Wu:
Incentivizing Combinatorial Bandit Exploration. NeurIPS 2022 - [c56]Moshe Babaioff, Ronny Lempel, Brendan Lucier, Ishai Menache, Aleksandrs Slivkins, Sam Chiu-wai Wong:
Truthful Online Scheduling of Cloud Workloads under Uncertainty. WWW 2022: 151-161 - [i53]Yingkai Li, Aleksandrs Slivkins:
Incentivizing Participation in Clinical Trials. CoRR abs/2202.06191 (2022) - [i52]Moshe Babaioff, Ronny Lempel, Brendan Lucier, Ishai Menache, Aleksandrs Slivkins, Sam Chiu-wai Wong:
Truthful Online Scheduling of Cloud Workloads under Uncertainty. CoRR abs/2203.01213 (2022) - [i51]Jason Gaitonde, Yingkai Li, Bar Light, Brendan Lucier, Aleksandrs Slivkins:
Budget Pacing in Repeated Auctions: Regret and Efficiency without Convergence. CoRR abs/2205.08674 (2022) - [i50]Xinyan Hu, Dung Daniel T. Ngo, Aleksandrs Slivkins, Zhiwei Steven Wu:
Incentivizing Combinatorial Bandit Exploration. CoRR abs/2206.00494 (2022) - [i49]Aleksandrs Slivkins, Dylan J. Foster:
Efficient Contextual Bandits with Knapsacks via Regression. CoRR abs/2211.07484 (2022) - 2021
- [c55]Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Aleksandrs Slivkins, Amit Sharma:
Sayer: Using Implicit Feedback to Optimize System Policies. SoCC 2021: 273-288 - [c54]Thodoris Lykouris, Max Simchowitz, Alex Slivkins, Wen Sun:
Corruption-robust exploration in episodic reinforcement learning. COLT 2021: 3242-3245 - [c53]Chara Podimata, Alex Slivkins:
Adaptive Discretization for Adversarial Lipschitz Bandits. COLT 2021: 3788-3805 - [c52]Karthik Abinav Sankararaman, Aleksandrs Slivkins:
Bandits with Knapsacks beyond the Worst Case. NeurIPS 2021: 23191-23204 - [c51]Mark Sellke, Aleksandrs Slivkins:
The Price of Incentivizing Exploration: A Characterization via Thompson Sampling and Sample Complexity. EC 2021: 795-796 - [c50]Mahsa Derakhshan, David M. Pennock, Aleksandrs Slivkins:
Beating Greedy For Approximating Reserve Prices in Multi-Unit VCG Auctions. SODA 2021: 1099-1118 - [i48]Max Simchowitz, Aleksandrs Slivkins:
Exploration and Incentives in Reinforcement Learning. CoRR abs/2103.00360 (2021) - [i47]Mathias Lécuyer, Sang Hoon Kim, Mihir Nanavati, Junchen Jiang, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins:
Sayer: Using Implicit Feedback to Optimize System Policies. CoRR abs/2110.14874 (2021) - 2020
- [j24]Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis:
Bayesian Incentive-Compatible Bandit Exploration. Oper. Res. 68(4): 1132-1161 (2020) - [j23]Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins, Chicheng Zhang:
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting. J. Mach. Learn. Res. 21: 137:1-137:45 (2020) - [j22]Aleksandrs Slivkins:
Book announcement: Introduction to Multi-Armed Bandits. SIGecom Exch. 18(1): 28-30 (2020) - [j21]Aaron Roth, Aleksandrs Slivkins, Jonathan R. Ullman, Zhiwei Steven Wu:
Multidimensional Dynamic Pricing for Welfare Maximization. ACM Trans. Economics and Comput. 8(1): 6:1-6:35 (2020) - [c49]Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun:
Constrained episodic reinforcement learning in concave-convex and knapsack settings. NeurIPS 2020 - [c48]Maryam Majzoubi, Chicheng Zhang, Rajan Chari, Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins:
Efficient Contextual Bandits with Continuous Actions. NeurIPS 2020 - [c47]Nicole Immorlica, Jieming Mao, Aleksandrs Slivkins, Zhiwei Steven Wu:
Incentivizing Exploration with Selective Data Disclosure. EC 2020: 647-648 - [i46]Karthik Abinav Sankararaman, Aleksandrs Slivkins:
Advances in Bandits with Knapsacks. CoRR abs/2002.00253 (2020) - [i45]Mark Sellke, Aleksandrs Slivkins:
Sample Complexity of Incentivized Exploration. CoRR abs/2002.00558 (2020) - [i44]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
Greedy Algorithm almost Dominates in Smoothed Contextual Bandits. CoRR abs/2005.10624 (2020) - [i43]Kianté Brantley, Miroslav Dudík, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, Wen Sun:
Constrained episodic reinforcement learning in concave-convex and knapsack settings. CoRR abs/2006.05051 (2020) - [i42]Maryam Majzoubi, Chicheng Zhang, Rajan Chari, Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins:
Efficient Contextual Bandits with Continuous Actions. CoRR abs/2006.06040 (2020) - [i41]Chara Podimata, Aleksandrs Slivkins:
Adaptive Discretization for Adversarial Bandits with Continuous Action Spaces. CoRR abs/2006.12367 (2020) - [i40]Guy Aridor, Yishay Mansour, Aleksandrs Slivkins, Zhiwei Steven Wu:
Competing Bandits: The Perils of Exploration Under Competition. CoRR abs/2007.10144 (2020) - [i39]Mahsa Derakhshan, David M. Pennock, Aleksandrs Slivkins:
Beating Greedy For Approximating Reserve Prices in Multi-Unit VCG Auctions. CoRR abs/2007.12653 (2020)
2010 – 2019
- 2019
- [j20]Aleksandrs Slivkins:
Introduction to Multi-Armed Bandits. Found. Trends Mach. Learn. 12(1-2): 1-286 (2019) - [j19]Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal:
Bandits and Experts in Metric Spaces. J. ACM 66(4): 30:1-30:77 (2019) - [c46]Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins, Chicheng Zhang:
Contextual bandits with continuous actions: Smoothing, zooming, and adapting. COLT 2019: 2025-2027 - [c45]Guy Aridor, Kevin Liu, Aleksandrs Slivkins, Zhiwei Steven Wu:
The Perils of Exploration under Competition: A Computational Modeling Approach. EC 2019: 171-172 - [c44]Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins:
Adversarial Bandits with Knapsacks. FOCS 2019: 202-219 - [c43]Nicole Immorlica, Jieming Mao, Aleksandrs Slivkins, Zhiwei Steven Wu:
Bayesian Exploration with Heterogeneous Agents. WWW 2019: 751-761 - [i38]Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins, Chicheng Zhang:
Contextual Bandits with Continuous Actions: Smoothing, Zooming, and Adapting. CoRR abs/1902.01520 (2019) - [i37]Guy Aridor, Kevin Liu, Aleksandrs Slivkins, Zhiwei Steven Wu:
Competing Bandits: The Perils of Exploration under Competition. CoRR abs/1902.05590 (2019) - [i36]Nicole Immorlica, Jieming Mao, Aleksandrs Slivkins, Zhiwei Steven Wu:
Bayesian Exploration with Heterogeneous Agents. CoRR abs/1902.07119 (2019) - [i35]Aleksandrs Slivkins:
Introduction to Multi-Armed Bandits. CoRR abs/1904.07272 (2019) - [i34]Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins, Wen Sun:
Corruption Robust Exploration in Episodic Reinforcement Learning. CoRR abs/1911.08689 (2019) - 2018
- [j18]Ashwinkumar Badanidiyuru, Robert Kleinberg, Aleksandrs Slivkins:
Bandits with Knapsacks. J. ACM 65(3): 13:1-13:55 (2018) - [c42]Karthik Abinav Sankararaman, Aleksandrs Slivkins:
Combinatorial Semi-Bandits with Knapsacks. AISTATS 2018: 1760-1770 - [c41]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
The Externalities of Exploration and How Data Diversity Helps Exploitation. COLT 2018: 1724-1738 - [c40]Yishay Mansour, Aleksandrs Slivkins, Zhiwei Steven Wu:
Competing Bandits: Learning Under Competition. ITCS 2018: 48:1-48:27 - [i33]Manish Raghavan, Aleksandrs Slivkins, Jennifer Wortman Vaughan, Zhiwei Steven Wu:
The Externalities of Exploration and How Data Diversity Helps Exploitation. CoRR abs/1806.00543 (2018) - [i32]Nicole Immorlica, Jieming Mao, Aleksandrs Slivkins, Zhiwei Steven Wu:
Incentivizing Exploration with Unbiased Histories. CoRR abs/1811.06026 (2018) - [i31]Nicole Immorlica, Karthik Abinav Sankararaman, Robert E. Schapire, Aleksandrs Slivkins:
Adversarial Bandits with Knapsacks. CoRR abs/1811.11881 (2018) - 2017
- [j17]Aleksandrs Slivkins:
Incentivizing exploration via information asymmetry. XRDS 24(1): 38-41 (2017) - [c39]Mathias Lécuyer, Joshua Lockerman, Lamont Nelson, Siddhartha Sen, Amit Sharma, Aleksandrs Slivkins:
Harvesting Randomness to Optimize Distributed Systems. HotNets 2017: 178-184 - [c38]Aaron Roth, Aleksandrs Slivkins, Jonathan R. Ullman, Zhiwei Steven Wu:
Multidimensional Dynamic Pricing for Welfare Maximization. EC 2017: 519-536 - [c37]Soheil Behnezhad, Mahsa Derakhshan, Mohammad Taghi Hajiaghayi, Aleksandrs Slivkins:
A Polynomial Time Algorithm for Spatio-Temporal Security Games. EC 2017: 697-714 - [i30]Yishay Mansour, Aleksandrs Slivkins, Zhiwei Steven Wu:
Competing Bandits: Learning under Competition. CoRR abs/1702.08533 (2017) - [i29]Karthik Abinav Sankararaman, Aleksandrs Slivkins:
Semi-Bandits with Knapsacks. CoRR abs/1705.08110 (2017) - [i28]Soheil Behnezhad, Mahsa Derakhshan, MohammadTaghi Hajiaghayi, Aleksandrs Slivkins:
A Polynomial Time Algorithm for Spatio-Temporal Security Games. CoRR abs/1706.05711 (2017) - 2016
- [j16]Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems. J. Artif. Intell. Res. 55: 317-359 (2016) - [j15]David Kempe, Jon M. Kleinberg, Sigal Oren, Aleksandrs Slivkins:
Selection and influence in cultural dynamics. Netw. Sci. 4(1): 1-27 (2016) - [c36]Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu:
Bayesian Exploration: Incentivizing Exploration in Bayesian Games. EC 2016: 661 - [c35]Ittai Abraham, Omar Alonso, Vasilis Kandylas, Rajesh Patel, Steven Shelford, Aleksandrs Slivkins:
How Many Workers to Ask?: Adaptive Exploration for Collecting High Quality Labels. SIGIR 2016: 473-482 - [i27]Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis, Zhiwei Steven Wu:
Bayesian Exploration: Incentivizing Exploration in Bayesian Games. CoRR abs/1602.07570 (2016) - [i26]Alekh Agarwal, Sarah Bird, Markus Cozowicz, Luong Hoang, John Langford, Stephen Lee, Jiaji Li, I. Dan Melamed, Gal Oshri, Oswaldo Ribas, Siddhartha Sen, Alex Slivkins:
A Multiworld Testing Decision Service. CoRR abs/1606.03966 (2016) - [i25]Aaron Roth, Aleksandrs Slivkins, Jonathan R. Ullman, Zhiwei Steven Wu:
Multidimensional Dynamic Pricing for Welfare Maximization. CoRR abs/1607.05397 (2016) - 2015
- [j14]Moshe Babaioff, Robert D. Kleinberg, Aleksandrs Slivkins:
Truthful Mechanisms with Implicit Payment Computation. J. ACM 62(2): 10:1-10:37 (2015) - [j13]Ittai Abraham, Shiri Chechik, David Kempe, Aleksandrs Slivkins:
Low-Distortion Inference of Latent Similarities from a Multiplex Social Network. SIAM J. Comput. 44(3): 617-668 (2015) - [j12]Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan:
Incentivizing high quality crowdwork. SIGecom Exch. 14(2): 26-34 (2015) - [j11]Moshe Babaioff, Shaddin Dughmi, Robert D. Kleinberg, Aleksandrs Slivkins:
Dynamic Pricing with Limited Supply. ACM Trans. Economics and Comput. 3(1): 4:1-4:26 (2015) - [c34]Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi:
Contextual Dueling Bandits. COLT 2015: 563-587 - [c33]Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis:
Bayesian Incentive-Compatible Bandit Exploration. EC 2015: 565-582 - [c32]Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan:
Incentivizing High Quality Crowdwork. WWW 2015: 419-429 - [i24]Yishay Mansour, Aleksandrs Slivkins, Vasilis Syrgkanis:
Bayesian Incentive-Compatible Bandit Exploration. CoRR abs/1502.04147 (2015) - [i23]Miroslav Dudík, Katja Hofmann, Robert E. Schapire, Aleksandrs Slivkins, Masrour Zoghi:
Contextual Dueling Bandits. CoRR abs/1502.06362 (2015) - [i22]Chien-Ju Ho, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan:
Incentivizing High Quality Crowdwork. CoRR abs/1503.05897 (2015) - 2014
- [j10]Aleksandrs Slivkins:
Contextual bandits with similarity information. J. Mach. Learn. Res. 15(1): 2533-2568 (2014) - [j9]Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins:
Characterizing Truthful Multi-armed Bandit Mechanisms. SIAM J. Comput. 43(1): 194-230 (2014) - [c31]Alekh Agarwal, Ashwinkumar Badanidiyuru, Miroslav Dudík, Robert E. Schapire, Aleksandrs Slivkins:
Robust Multi-objective Learning with Mentor Feedback. COLT 2014: 726-741 - [c30]Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins:
Resourceful Contextual Bandits. COLT 2014: 1109-1134 - [c29]Ittai Abraham, Omar Alonso, Vasilis Kandylas, Rajesh Patel, Steven Shelford, Aleksandrs Slivkins:
Using Worker Quality Scores to Improve Stopping Rules. HCOMP 2014: 2-3 - [c28]Yevgeny Seldin, Aleksandrs Slivkins:
One Practical Algorithm for Both Stochastic and Adversarial Bandits. ICML 2014: 1287-1295 - [c27]Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Adaptive contract design for crowdsourcing markets: bandit algorithms for repeated principal-agent problems. EC 2014: 359-376 - [i21]Ashwinkumar Badanidiyuru, John Langford, Aleksandrs Slivkins:
Resourceful Contextual Bandits. CoRR abs/1402.6779 (2014) - [i20]Chien-Ju Ho, Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problems. CoRR abs/1405.2875 (2014) - [i19]Ittai Abraham, Omar Alonso, Vasilis Kandylas, Rajesh Patel, Steven Shelford, Aleksandrs Slivkins:
Using Worker Quality Scores to Improve Stopping Rules. CoRR abs/1411.0149 (2014) - 2013
- [j8]Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi:
Ranked bandits in metric spaces: learning diverse rankings over large document collections. J. Mach. Learn. Res. 14(1): 399-436 (2013) - [j7]Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Online decision making in crowdsourcing markets: theoretical challenges. SIGecom Exch. 12(2): 4-23 (2013) - [c26]Ittai Abraham, Omar Alonso, Vasilis Kandylas, Aleksandrs Slivkins:
Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem. COLT 2013: 882-910 - [c25]Ashwinkumar Badanidiyuru, Robert Kleinberg, Aleksandrs Slivkins:
Bandits with Knapsacks. FOCS 2013: 207-216 - [c24]Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins:
Multi-parameter mechanisms with implicit payment computation. EC 2013: 35-52 - [c23]David Kempe, Jon M. Kleinberg, Sigal Oren, Aleksandrs Slivkins:
Selection and influence in cultural dynamics. EC 2013: 585-586 - [c22]Ittai Abraham, Shiri Chechik, David Kempe, Aleksandrs Slivkins:
Low-distortion Inference of Latent Similarities from a Multiplex Social Network. SODA 2013: 1853-1872 - [i18]Ittai Abraham, Omar Alonso, Vasilis Kandylas, Aleksandrs Slivkins:
Adaptive Crowdsourcing Algorithms for the Bandit Survey Problem. CoRR abs/1302.3268 (2013) - [i17]Moshe Babaioff, Robert Kleinberg, Aleksandrs Slivkins:
Multi-parameter Mechanisms with Implicit Payment Computation. CoRR abs/1302.4138 (2013) - [i16]David Kempe, Jon M. Kleinberg, Sigal Oren, Aleksandrs Slivkins:
Selection and Influence in Cultural Dynamics. CoRR abs/1304.7468 (2013) - [i15]Ashwinkumar Badanidiyuru, Robert Kleinberg, Aleksandrs Slivkins:
Bandits with Knapsacks. CoRR abs/1305.2545 (2013) - [i14]Aleksandrs Slivkins:
Dynamic Ad Allocation: Bandits with Budgets. CoRR abs/1306.0155 (2013) - [i13]Aleksandrs Slivkins, Jennifer Wortman Vaughan:
Online Decision Making in Crowdsourcing Markets: Theoretical Challenges (Position Paper). CoRR abs/1308.1746 (2013) - [i12]Robert Kleinberg, Aleksandrs Slivkins, Eli Upfal:
Bandits and Experts in Metric Spaces. CoRR abs/1312.1277 (2013) - 2012
- [c21]Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins:
Dynamic pricing with limited supply. EC 2012: 74-91 - [c20]Sébastien Bubeck, Aleksandrs Slivkins:
The Best of Both Worlds: Stochastic and Adversarial Bandits. COLT 2012: 42.1-42.23 - [i11]Ittai Abraham, Shiri Chechik, David Kempe, Aleksandrs Slivkins:
Low-distortion Inference of Latent Similarities from a Multiplex Social Network. CoRR abs/1202.0922 (2012) - [i10]Sébastien Bubeck, Aleksandrs Slivkins:
The best of both worlds: stochastic and adversarial bandits. CoRR abs/1202.4473 (2012) - 2011
- [c19]Aleksandrs Slivkins:
Multi-armed bandits on implicit metric spaces. NIPS 2011: 1602-1610 - [c18]Aleksandrs Slivkins:
Contextual Bandits with Similarity Information. COLT 2011: 679-702 - [c17]Aleksandrs Slivkins:
Monotone multi-armed bandit allocations. COLT 2011: 829-834 - [i9]Moshe Babaioff, Shaddin Dughmi, Robert Kleinberg, Aleksandrs Slivkins:
Dynamic Pricing with Limited Supply. CoRR abs/1108.4142 (2011) - 2010
- [j6]Aleksandrs Slivkins:
Parameterized Tractability of Edge-Disjoint Paths on Directed Acyclic Graphs. SIAM J. Discret. Math. 24(1): 146-157 (2010) - [c16]Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi:
Learning optimally diverse rankings over large document collections. ICML 2010: 983-990 - [c15]Moshe Babaioff, Robert D. Kleinberg, Aleksandrs Slivkins:
Truthful mechanisms with implicit payment computation. EC 2010: 43-52 - [c14]Robert Kleinberg, Aleksandrs Slivkins:
Sharp Dichotomies for Regret Minimization in Metric Spaces. SODA 2010: 827-846 - [i8]Moshe Babaioff, Robert D. Kleinberg, Aleksandrs Slivkins:
Truthful Mechanisms with Implicit Payment Computation. CoRR abs/1004.3630 (2010) - [i7]Aleksandrs Slivkins, Filip Radlinski, Sreenivas Gollapudi:
Learning optimally diverse rankings over large document collections. CoRR abs/1005.5197 (2010) - [i6]Umar Syed, Aleksandrs Slivkins, Nina Mishra:
Adapting to the Shifting Intent of Search Queries. CoRR abs/1007.3799 (2010)
2000 – 2009
- 2009
- [j5]Aleksandrs Slivkins, Jehoshua Bruck:
Interleaving schemes on circulant graphs with two offsets. Discret. Math. 309(13): 4384-4398 (2009) - [j4]Jon M. Kleinberg, Aleksandrs Slivkins, Tom Wexler:
Triangulation and embedding using small sets of beacons. J. ACM 56(6): 32:1-32:37 (2009) - [j3]T.-H. Hubert Chan, Kedar Dhamdhere, Anupam Gupta, Jon M. Kleinberg, Aleksandrs Slivkins:
Metric Embeddings with Relaxed Guarantees. SIAM J. Comput. 38(6): 2303-2329 (2009) - [c13]Umar Syed, Aleksandrs Slivkins, Nina Mishra:
Adapting to the Shifting Intent of Search Queries. NIPS 2009: 1829-1837 - [c12]Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins:
Characterizing truthful multi-armed bandit mechanisms: extended abstract. EC 2009: 79-88 - [i5]