Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Yogeshwer Sharma

dblp:44/3609 · DBLP profile ↗
← Back
8ranked-venue papers
3as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 5 · 2 first-authorArtificial intelligence and machine learning · 4 · 1 first-authorComputer networks · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
4 papers
Algorithmic game theory and mechanism design · 89% Approximation and online algorithms · 5% Mathematical optimization · 5%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Artificial intelligence
2 papers
Reinforcement learning · 100%

Topics — the 18 heaviest of 19, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › multi-armed bandit
multi-armed bandit mechanism
0.322014
Characterizing Truthful Multi-armed Bandit Mechanisms · SIAM J. Comput. 2014
Characterizing truthful multi-armed bandit mechanisms: extended abstract · EC 2009
Algorithmic game theory and mechanism design › auction theory › advertising auctions
pay-per-click auction
0.322014
Characterizing Truthful Multi-armed Bandit Mechanisms · SIAM J. Comput. 2014
Characterizing truthful multi-armed bandit mechanisms: extended abstract · EC 2009
Distributed systems › replication
geo-replication
0.212015
Wormhole: Reliable Pub-Sub to Support Geo-replicated Internet Services · NSDI 2015
Distributed systems
publish/subscribe systems
0.212015
Wormhole: Reliable Pub-Sub to Support Geo-replicated Internet Services · NSDI 2015
Machine learning › Reinforcement learning
multi-armed bandit
0.212014
Characterizing Truthful Multi-armed Bandit Mechanisms · SIAM J. Comput. 2014
Machine learning › Reinforcement learning
regret minimization
0.212014
Characterizing Truthful Multi-armed Bandit Mechanisms · SIAM J. Comput. 2014
Algorithmic game theory and mechanism design › mechanism design
auction design
0.212014
Characterizing Truthful Multi-armed Bandit Mechanisms · SIAM J. Comput. 2014
Algorithmic game theory and mechanism design › mechanism design
truthful mechanism design
0.212014
Characterizing Truthful Multi-armed Bandit Mechanisms · SIAM J. Comput. 2014
Algorithmic game theory and mechanism design › mechanism design › auction design
truthful auction
0.112009
Characterizing truthful multi-armed bandit mechanisms: extended abstract · EC 2009
Algorithmic game theory and mechanism design
welfare maximization
0.112009
Characterizing truthful multi-armed bandit mechanisms: extended abstract · EC 2009
Machine learning › Reinforcement learning
bandit
0.112008
Regret Bounds for Sleeping Experts and Bandits · COLT 2008
Algorithmic game theory and mechanism design
price of anarchy
0.112007
Stackelberg thresholds in network routing games or the value of altruism · EC 2007
Approximation and online algorithms
prize-collecting problems
0.112007
Approximation algorithms for prize collecting forest problems with submodular penalty functions · SODA 2007
Algorithmic game theory and mechanism design › congestion games
selfish routing
0.112007
Stackelberg thresholds in network routing games or the value of altruism · EC 2007
Algorithmic game theory and mechanism design › stackelberg game
stackelberg routing
0.112007
Stackelberg thresholds in network routing games or the value of altruism · EC 2007
Mathematical optimization
submodular optimization
0.112007
Approximation algorithms for prize collecting forest problems with submodular penalty functions · SODA 2007
Distributed systems › fault tolerance
reliable communication
0.112015
Wormhole: Reliable Pub-Sub to Support Geo-replicated Internet Services · NSDI 2015
Distributed systems
replication
0.112015
Wormhole: Reliable Pub-Sub to Support Geo-replicated Internet Services · NSDI 2015

Methods — techniques the papers use, named apart from their topics

regret lower bound · 0.4dominant-strategy truthfulness · 0.2dominant strategy truthfulness · 0.2online learning · 0.1dominant strategy mechanism design · 0.1primal-dual approximation · 0.1optimization · 0.1game theory · 0.1LP rounding · 0.1
YearPublicationVenuePosition
2015 Wormhole: Reliable Pub-Sub to Support Geo-replicated Internet Services
Yogeshwer Sharma, Philippe Ajoux, Petchean Ang, David Callies, Abhishek Choudhary, Laurent Demailly, Thomas Fersch, Liat Atsmon Guz, Andrzej Kotulski, Sachin Kulkarni, Harry C. Li, Evgeniy Makeev, Kowshik Prakasam, Robbert van Renesse, Sabyasachi Roy, Pratyush Seth, Yee Jiun Song, Benjamin Wester, Kaushik Veeraraghavan, Peter Xie
NSDI1
2014 Characterizing Truthful Multi-armed Bandit Mechanisms
abstract
We consider a multiround auction setting motivated by pay-per-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. Initially, neither the auctioneer nor the advertisers have any information about the likelihood of clicks on the advertisements. The auctioneer's goal is to design a (dominant strategies) truthful mechanism that (approximately) maximizes the social welfare. If the advertisers bid their true private values, our problem is equivalent to the multi-armed bandit problem, and thus can be viewed as a strategic version of the latter. In particular, for both problems the quality of an algorithm can be characterized by regret, the difference in social welfare between the algorithm and the benchmark which always selects the same “best” advertisement. We investigate how the design of multi-armed bandit algorithms is affected by the restriction that the resulting mechanism must be truthful. We find that deterministic truthful mechanisms have certain strong structural properties---essentially, they must separate exploration from exploitation---and they incur much higher regret than the optimal multi-armed bandit algorithms. Moreover, we provide a truthful mechanism which (essentially) matches our lower bound on regret.
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
SIAM J. Comput.2
2010 Regret bounds for sleeping experts and bandits
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yogeshwer Sharma
Mach. Learn.3
2009 Characterizing truthful multi-armed bandit mechanisms: extended abstract
abstract
We consider a multi-round auction setting motivated by pay-per-click auctions for Internet advertising. In each round the auctioneer selects an advertiser and shows her ad, which is then either clicked or not. An advertiser derives value from clicks; the value of a click is her private information. Initially, neither the auctioneer nor the advertisers have any information about the likelihood of clicks on the advertisements. The auctioneer's goal is to design a (dominant strategies) truthful mechanism that (approximately) maximizes the social welfare.
Moshe Babaioff, Yogeshwer Sharma, Aleksandrs Slivkins
EC2
2008 Regret Bounds for Sleeping Experts and Bandits
Robert D. Kleinberg, Alexandru Niculescu-Mizil, Yogeshwer Sharma
COLT3
2008 Approximation Algorithms for Prize-Collecting Network Design Problems with General Connectivity Requirements
Chandrashekhar Nagarajan, Yogeshwer Sharma, David P. Williamson
WAOA2
2007 Stackelberg thresholds in network routing games or the value of altruism
abstract
Noncooperative network routing games are a natural model of userstrying to selfishly route flow through a network in order to minimize their own delays. It is well known that the solution resulting from this selfish routing (called the Nash equilibrium) can have social cost strictly higher than the cost of the optimum solution. One way to improve the quality of the resulting solution is to centrally control a fraction of the flow. A natural problem for the network administrator then is to route the centrally controlled flow in such a way that the overall cost of the solution is minimized after the remaining fraction has routed itself selfishl.
Yogeshwer Sharma, David P. Williamson
EC1
2007 Approximation algorithms for prize collecting forest problems with submodular penalty functions
Yogeshwer Sharma, Chaitanya Swamy, David P. Williamson
SODA1