WINE 2009


Although, the detailed reviews will come on Monday, the WINE2009 paper list is out:

Long papers:
  1. Martin Hoefer, Vahab Mirrokni, Heiko Röglin and Shang-Hua Teng. Competitive Routing over Time
  2. Pinyan Lu. On 2-Player Randomized Mechanisms for Scheduling
  3. Patrick Briest, Martin Hoefer, Luciano Guala and Carmine Ventre. On Stackelberg Pricing with Computationally Bounded Consumers
  4. Angelo Fanelli and Luca Moscardelli. On Best Response Dynamics in Weighted Congestion Games with Polynomial Delays
  5. Leah Epstein, Elena Kleiman and Julian Mestre. Parametric Packing of Selfish Items and the Subset Sum Algorithm
  6. Sourav Chakraborty and Nikhil Devanur. An Online Multi-unit Auction with Improved Competitive Ratio
  7. Peng Shi, Vincent Conitzer and Mingyu Guo. Prediction Mechanisms That Do Not Incentivize Undesirable Actions
  8. David Arthur, Rajeev Motwani, Aneesh Sharma and Ying Xu. Pricing strategies for viral marketing on Social Networks
  9. Ola Rozenfeld and Moshe Tennenholtz. Consistent Continuous Trust-Based Recommendation Systems
  10. Jean Cardinal, Erik D. Demaine, Samuel Fiorini, Gwenaël Joret, Ilan Newman and Oren Weimann. The Stackelberg Minimum Spanning Tree Game on Planar and Bounded-Treewidth Graphs
  11. Pinyan Lu, Yajun Wang and Yuan Zhou. Tighter Bounds for Facility Games
  12. Claudia Lindner and Joerg Rothe. Degrees of Guaranteed Envy-Freeness in Finite Bounded Cake-Cutting Protocols
  13. Thanh Nguyen and Eva Tardos. Approximate Pure Nash Equilibria via Lov\'asz Local Lemma
  14. Renato Gomes, Nicole Immorlica and Evangelos Markakis. Externalities in Keyword Auctions: an Empirical and Theoretical Assessment
  15. Martin Gairing. Covering Games: Approximation through Non-Cooperation
  16. Sharad Goel, Sebastien Lahaie and Sergei Vassilvitskii. Contract Auctions for Sponsored Search
  17. Arpita Ghosh, Preston McAfee, Kishore Papineni and Sergei Vassilvitskii. Bidding for Representative Allocations for Display Advertising
  18. Esteban Arcaute and Sergei Vassilvitskii. Social Networks and Stable Matchings in the Job Market
  19. Leah Epstein, Elena Kleiman and Rob van Stee. Maximizing the Minimum Load: The Cost of Selfishness
  20. Mingyu Guo, Vincent Conitzer and Daniel Reeves. Competitive Repeated Allocation Without Payments
  21. Paolo Penna, Florian Schoppmann, Riccardo Silvestri and Peter Widmayer. Pseudonyms in cost-sharing games
  22. Michal Feldman and Yuval Emek. Computing Optimal Contracts in Series-Parallel Heterogeneous Combinatorial Agencies
  23. Rainer Feldmann, Marios Mavronicolas and Burkhard Monien. Nash Equilibria for Voronoi Games on Transitive Graphs
  24. Laurent Gourves, Jerome Monnot and Orestis Telelis. Selfish Scheduling with Setup Times
  25. Nithum Thain and Adrian Vetta. Computational Aspects of Multimarket Price Wars
  26. Dimitris Fotakis, Vasilis Gkatzelis, Alexis Kaporis and Paul Spirakis. The Impact of Social Ignorance on Weighted Congestion Games
  27. Christopher Wilkens. The Complexity of Models of International Trade
  28. Angelina Vidali. The Geometry of Truthfulness
  29. Michal Feldman, Ran Tessler and Yoav Wilf. Optimal Incentives for Participation with Type-Dependent Externalities
  30. Anand Bhalgat, Tanmoy Chakraborty and Sanjeev Khanna. Nash Dynamics in Congestion Games with Similar Resources
  31. Jon Feldman, Nitish Korula, Vahab Mirrokni, S. Muthukrishnan and Martin Pal. Online Ad Assignment with Free Disposal
  32. Devansh Dikshit and Narahari Yadati. Truthful and Quality Conscious Query Incentive Networks
  33. Saeed Alaei and Azarakhsh Malekian. An Analysis of Troubled Assets Reverse Auction
  34. Xiaotie Deng, Qi Qi and Jie Zhang. Direction Preserving Zero Point Computing and Applications
Short papers
  1. Vijay Vazirani and Lei Wang. Continuity Properties of Equilibria in Some Fisher and Arrow-Debreu Market Models
  2. Dömötör Pálvölgyi. 2D-TUCKER is PPAD-complete
  3. Joud Khoury, Chaouki Abdallah and Kate Krause. Route Distribution Incentives
  4. Paul Duetting, Monika Henzinger and Ingmar Weber. Bidder Optimal Assignments for General Utilities
  5. Joshua R. Davis, David Liben-Nowell, Alexa Sharp and Tom Wexler. Mediated Equilibria in Load-Balancing Games
  6. Ashwinkumar B.V. and Robert Kleinberg. Randomized Online Algorithms for the Buyback Problem
  7. Thomas Voice, Maria Polukarov, Andrew Byde and Nicholas R. Jennings. On the Impact of Strategy and Utility Structures on Congestion-Averse Games
  8. Sunghoon Hong. Hacking-Proofness and Stability in a Model of Information Security Networks
  9. David Kempe, Ahuva Mu'alem and Mahyar Salek. Envy-Free Allocations for Budgeted Bidders
  10. Jiajin Yu and Xiaotie Deng. A New Ranking Scheme of the GSP Mechanism with Markovian Users
  11. Taiki Todo, Atsushi Iwasaki and Makoto Yokoo. Characterization of Strategy-proof, Revenue Monotone Combinatorial Auction Mechanisms and Connection with False-name-proofness
  12. Laurent Gourves and Jerome Monnot. On Strong Equilibria in the Max Cut Game
  13. Martin Hoefer and Alexander Skopalik. Stability and Convergence in Selfish Scheduling with Altruistic Agents
  14. Arash Asadpour and Amin Saberi. On the Inefficiency Ratio of Stable Equilibria in Congestion Games
  15. Mangesh Gupte, MohammadTaghi Hajiaghayi, Lu Han, Liviu Iftode, Pravin Shankar and Raluca Ursu. News Posting by Stragetic Users in a Social Network
  16. Xi Gao, Yiling Chen and David M. Pennock. Betting on Real Line
  17. Rahul Savani, Haris Aziz, Mike Paterson and Oded Lachish. Wiretapping a hidden network
  18. Qianya Lin and Yiling Chen. Gaming Dynamic Parimutuel Markets
  19. Ning Chen, Edith Elkind and Nikolay Gravin. Refining the Cost of Cheap Labor in Set System Auctions
  20. Josep Diaz, Dieter Mitsche, Navin Rustagi and Jared Saia. Fear in Mediation: Exploiting the "Windfall of Malice"
  21. Tobias Harks, Max Klimm and Rolf H. Moehring. Strong Nash Equilibria in Games with the Lexicographical Improvement Property
  22. Ilan Adler, Constantinos Daskalakis and Christos Papadimitriou. A Note on Strictly Competitive Games
  23. Ioannis Caragiannis, Christos Kaklamanis, Panagiotis Kanellopoulos and Maria Kyropoulou. The efficiency of fair division
  24. Krzysztof Apt and Evangelos Markakis. Sequential Bidding in the Bailey-Cavallo Mechanism
  25. Stanko Dimitrov, Rahul Sami and Marina Epelman. Subsidized Prediction Markets for Risk Averse Traders
  26. Amiram Wingarten and Amos Fiat. Envy, Multi Envy, and Revenue Maximization
  27. Jacomo Corbo and Yevgeniy Vorobeychik. Quality and Price Effects on Technology Adoption
  28. Ravi Kumar, Mohammad Mahdian and Amin Sayedi. Mechanism Design for Complexity-Constrained Bidders
  29. Xiaotie Deng and Qi Qi. Priority Right Auction for Komi Setting
Keynote speakers:
  1. Muthu Muthukrishnan, Google Inc.
  2. H. Peyton-Young, U. of Oxford and Johns Hopkins U.
  3. Eva Tardos, Cornell U.

Tutorial speakers:
  1. Andrei Broder, Yahoo! Research
  2. Kamal Jain / Nikhil Devanur, Microsoft Research
  3. Tim Roughgarden, Stanford U.

Comments

Post a Comment

Popular posts from this blog

Smart Lotteries in School Choice Ex-ante Pareto-Improvement with Ex-post Stability

Image
Working Paper: https://cgi.cse.unsw.edu.au/~haziz/PIRMES.pdf  Abstract: In a typical school choice application, the students have strict preferences over the schools while the schools have coarse priorities over the students based on their distance and their enrolled siblings. The outcome of a centralized admission mechanism is then usually obtained by the Deferred Acceptance (DA) algorithm with random tie-breaking. Therefore, every possible outcome of this mechanism is a stable solution for the coarse priorities that will arise with certain probability. This implies a probabilistic assignment, where the admission probability for each student-school pair is specified. In this paper, we propose a new efficiency-improving stable `smart lottery' mechanism. We aim to improve the probabilistic assignment ex-ante in a stochastic dominance sense, while ensuring that the improved random matching is still ex-post stable, meaning that it can be decomposed into stable matchings regarding the ...
Read more

Proportionally Representative Clustering

Image
H. Aziz, B. Lee, S. Morota Chu, and J. Vollen. Proportionally Representative Clustering.  WINE 2024 .  [  Pdf  ]  In recent years, there has been a surge in effort to formalize notions of fairness in machine learning. We focus on centroid clustering— one of the fundamental tasks in unsupervised machine learning. We pro- pose a new axiom “proportionally representative fairness” (PRF) that is designed for clustering problems where the selection of centroids re- flects the distribution of data points and how tightly they are clustered together. Our fairness concept is not satisfied by existing fair cluster- ing algorithms. We design efficient algorithms to achieve PRF both for unconstrained and discrete clustering problems. Our algorithm for the unconstrained setting is also the first known polynomial-time approxi- mation algorithm for the well-studied Proportional Fairness (PF) axiom [ 13 ]. Our algorithm for the discrete setting also matches the best kn...
Read more

Fair budgets from ranked ballots: PB-EAR

How do you split a shared budget fairly when people rank projects that cost very different amounts? PB-EAR, from our AAAI 2021 paper  Proportionally Representative Participatory Budgeting with Ordinal Preferences  ( AAAI version ), gives every voter an equal slice of the budget and lets groups pool their slices to fund the projects they rank highest, looking further down the ballots only when nothing is yet affordable. Every cohesive group is guaranteed its proportional share, and the rule extends our  Expanding Approvals Rule  for elections to budgets with project costs, ties and unequal voter weights.  That makes it a natural fit for DAO grant rounds such as   TheDAO Security Fund 's ETHSecurity Initiatives, where badge holders will rank the security initiatives listed on   the app  to allocate the fund's budget. The two-minute video below walks through a worked example. Here's an educational tool someone built to show how PB-EAR works. 
Read more