Category Archives: microsoft

Microsoft Researchers co-authored 21% of papers at the ACM Conference on Economics and Computation

Twenty-six researchers from Microsoft Research labs in Boston, China, India, Israel, New York City, Redmond, Silicon Valley, and the United Kingdom co-authored a remarkable seventeen of the eighty papers published in the 2014 ACM Conference on Economics and Computation (EC’14).

Moshe Babaioff served as General Chair for the conference and many other Microsoft Researchers served roles including (senior) PC members, workshop organizers, and tutorial speakers.

For research at the intersection of economics and computation, IMHO there’s no stronger “department” in the world than MSR.

Sébastien Lahaie and Jennifer Wortman Vaughan co-authored three papers each. Remarkably, Jenn accomplished that feat and gave birth!

The full list of authors are: Shipra Agrawal, Moshe Babaioff, Yoram Bachrach, Wei Chen, Sofia Ceppi, Nikhil R. Devanur, Fernando Diaz, Hu Fu, Rafael Frongillo, Daniel Goldstein, Nicole Immorlica, Ian Kash, Peter Key, Sébastien Lahaie, Tie-Yan Liu, Brendan Lucier, Yishay Mansour, Preston McAfee, Noam Nisan, David M. Pennock, Tao Qin, Justin Rao, Aleksandrs Slivkins, Siddharth Suri, Jennifer Wortman Vaughan, and Duncan Watts.

The full list of papers are:

Optimal Auctions for Correlated Bidders with Sampling
Hu Fu, Nima Haghpanah, Jason Hartline and Robert Kleinberg

Generalized Second Price Auction with Probabilistic Broad Match
Wei Chen, Di He, Tie-Yan Liu, Tao Qin, Yixin Tao and Liwei Wang

Optimising Trade‐offs Among Stakeholders in Ad Auctions
Yoram Bachrach, Sofia Ceppi, Ian Kash, Peter Key and David Kurokaw

Neutrality and Geometry of Mean Voting
Sébastien Lahaie and Nisarg Shah

Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal‐Agent Problems
Chien-Ju Ho, Aleksandrs Slivkins and Jennifer Wortman Vaughan

Removing Arbitrage from Wagering Mechanisms
Yiling Chen, Nikhil R. Devanur, David M. Pennock and Jennifer Wortman Vaughan

Information Aggregation in Exponential Family Markets
Jacob Abernethy, Sindhu Kutty, Sébastien Lahaie and Rahul Sami

A General Volume‐ Parameterized Market Making Framework
Jacob Abernethy, Rafael Frongillo, Xiaolong Li and Jennifer Wortman Vaughan

Reasoning about Optimal Stable Matchings under Partial Information
Baharak Rastegari, Anne Condon, Nicole Immorlica, Robert Irving and Kevin Leyton-Brown

The Wisdom of Smaller, Smarter Crowds
Daniel Goldstein, Preston McAfee and Siddharth Suri

Incentivized Optimal Advert Assignment via Utility Decomposition
Frank Kelly, Peter Key and Neil Walton

Whole Page Optimization: How Page Elements Interact with the Position Auction
Pavel Metrikov, Fernando Diaz, Sébastien Lahaie and Justin Rao

Local Computation Mechanism Design
Shai Vardi, Avinatan Hassidim and Yishay Mansour

On the Efficiency of the Walrasian Mechanism
Moshe Babaioff, Brendan Lucier, Noam Nisan and Renato Paes Leme

Long‐run Learning in Games of Cooperation
Winter Mason, Siddharth Suri and Duncan Watts

Contract Complexity
Moshe Babaioff and Eyal Winter

Bandits with concave rewards and convex knapsacks
Shipra Agrawal and Nikhil R. Devanur

Last call: Postdoc positions at Microsoft Research NYC

Microsoft Research New York City seeks outstanding applicants for 2-year postdoctoral researcher positions. We welcome applicants with a strong academic record in one of the following areas:

We will also consider applicants in other focus areas of the lab, including information retrieval, and behavioral & empirical economics. Additional information about these areas is included below. Please submit all application materials by January 11, 2013 for full consideration. Instructions are here.


COMPUTATIONAL SOCIAL SCIENCE

With an increasing amount of data on every aspect of our daily activities — from what we buy, to where we travel, to who we know — we are able to measure human behavior with precision largely thought impossible just a decade ago. Lying at the intersection of computer science, statistics and the social sciences, the emerging field of computational social science uses large-scale demographic, behavioral and network data to address longstanding questions in sociology, economics, politics, and beyond. We seek postdoc applicants with a diverse set of skills, including experience with large-scale data, scalable statistical and machine learning methods, and knowledge of a substantive social science field, such as sociology, economics, psychology, political science, or marketing.

ONLINE EXPERIMENTAL SOCIAL SCIENCE

Online experimental social science involves using the web, including crowdsourcing platforms such as Amazon’s Mechanical Turk, to study human behavior in “virtual lab” environments. Among other topics, virtual labs have been used to study the relationship between financial incentives and performance, the honesty of online workers, advertising impact as a function of exposure time, the implicit cost of “bad ads,” the testing of graphical user interfaces eliciting probabilistic information and also the relationship between network structure and social dynamics, related to social phenomena such as cooperation, learning, and collective problem solving. We seek postdoc applicants with a diverse mix of skills, including awareness of the theoretical and experimental social science literature, and experience with experimental design, as well as demonstrated statistical modeling and programming expertise. Specific experience running experiments on Amazon’s Mechanical Turk or related crowdsourcing websites, as well as managing virtual participant pools is also desirable, as is evidence of UI design ability.

ALGORITHMIC ECONOMICS AND MARKET DESIGN

Market design, the engineering arm of economics, benefits from an understanding of computation: complexity, algorithms, engineering practice, and data. Conversely, computer science in a networked world benefits from a solid foundation in economics: incentives and game theory. Scientists with hybrid expertise are crucial as social systems of all types move to electronic platforms, as people increasingly rely on programmatic trading aids, as market designers rely more on equilibrium simulations, and as optimization and machine learning algorithms become part of the inner loop of social and economic mechanisms. We seek applicants who embody a diverse mix of skills, including a background in computer science (e.g., artificial intelligence or theory) or related field, and knowledge of the theoretical and experimental economics literature. Experience building prototype systems, and a comfort level with modern programming paradigms (e.g., web programming and map-reduce) are also desirable.

MACHINE LEARNING

Machine learning is the discipline of designing efficient algorithms for making accurate predictions and optimal decisions in the face of uncertainty. It combines tools and techniques from computer science, signal processing, statistics and optimization. Microsoft offers a unique opportunity to work with extremely diverse data sources, both big and small, while also offering a very stimulating environment for cutting-edge theoretical research. We seek postdoc applicants who have demonstrated ability to do independent research, have a strong publication record at top research venues and thrive in a multidisciplinary environment.

Microsoft Research New York City, First Days

Microsoft Research NYC logoNow that I’ve said my goodbyes, I’m thrilled to announce that I’ve joined Microsoft Research, an organization with going-on twenty-one years of commitment to basic and applied research, employing 850 Ph.D. scientists around the globe including Turing Award winners, Fields Medalists, and many long-time colleagues that I hugely respect. If that were all, I would be over-the-top happy right now.

But that’s not all. Together with fourteen other founding members (seven of whom I can name: Duncan Watts, John Langford, David Rothschild, Sharad Goel, Dan Goldstein, Jake Hofman, and Sid Suri), we are cutting the ribbon on a new outpost for Microsoft Research in New York City. We will report to Jennifer Chayes, the founder and director of Microsoft Research New England in Cambridge, MA. It’s been amazing to watch her up close pursue a goal relentlessly with boundless positive energy. I get the feeling it’s how she approaches everything she does, a realization that played no small part in my decision. The New England Lab, like us, is an interdisciplinary research group that blends computer science, social science, and machine learning, yet from different enough perspectives to make this an almost perfect marriage. It’s no exaggeration to say that helping to found and lead a new research group amid the bursting tech scene in New York City, with the resources of Microsoft behind us, is — as Duncan says — a once-in-a-career opportunity.

The press coverage Thursday was gratifying, including nice pieces in PCMag (source of the sweet logo above), NYTimes.com, AllThingsD, and dozens more. Here is the official press release. For science perspectives, see John Langford’s, Lance Fortnow’s, Dan Goldstein’s, and Jennifer Chayes’s blog posts. One of the coolest moments came when New York Mayor Michael Bloomberg tweeted about us.

Note that, despite the attrition, Yahoo! Labs lives on, probably more applied but not solely so. Ron Brachman, the new head of Yahoo! Labs, is terrific and may be able to do something special there. The Barcelona group remains largely intact and just got 7 (!) papers into SIGIR. Other groups remain intact as well.

The reception within Microsoft research and product orgs has been swift and very warm. The breadth and scope of the place can be daunting at first but invigorating. The ability to impact products that touch hundreds of millions of people’s lives is, as always, a rewarding draw of corporate research. Yet one of the deciding factors for many of us in joining Microsoft is the freedom to interact with universities in research, service, teaching, hosting visitors, hiring interns and postdocs, etc. In addition, we’d like to play our part in the New York City tech scene, including the startup, venture-capitalist, and hack/make communities, plus the new Cornell-Technion campus, contributing to Mayor Bloomberg’s vision of New York City as a tech hub.

An interesting side note that bodes well for my two daughters ages 7 and 4 is that my primary decision boiled down to working for one of two brilliant and accomplished women: Jennifer Chayes at Microsoft, or Corinna Cortes at Google, who is absolutely terrific. Google is a incredible place, a model of efficiency, innovation, and ambition, with an impressive roster of people, and the company is in a very strong position. But this opportunity at Microsoft simply proved to be too good to pass up. I can’t believe how perfectly everything fell into place. I’m beyond thrilled at the outcome and excited to begin this next chapter of my career.