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Zhe Feng

Ph.D student in Computer Science

Maxwell Dworkin 242, 33 Oxford Street, Cambridge, MA 01238
zhe_feng@g.harvard.edu
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Zhe Feng
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News

[6/2020] One paper "The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation" is accepted to ICML 2020.

June 2, 2020

[5/2020] Our paper “Optimal Auctions through Deep Learning” was invited to appear as a Research Highlight in the Communications of the ACM!

June 2, 2020

[4/2019] Our paper "Optimal Auctions through Deep Learning" is accepted in ICML'19.

May 29, 2019

[3/2019] I was named one of the 2019 Google PhD Fellows.

April 2, 2019

[1/2019] One paper "Online Learning for Measuring Incentive Compatibility in Ad Auctions" is accepted in WWW'19

January 22, 2019

[4/2018] One paper "Learning to Bid Without Knowing your Value" accepted in EC.

April 20, 2018

[1/2018] New paper "Deep Learning for Revenue-Optimal Auctions with Budgets" accepted in AAMAS 2018

January 24, 2018

[11/2017] New paper "Learning to Bid Without Knowing your Value", available on ArXiv

November 10, 2017

[7/2017] New paper on "Octahedral Tucker is PPA-Complete", now available on ECCC.

July 30, 2017
Our paper "Octahedral Tucker is PPA-Complete" is now available on ECCC. Read more about [7/2017] New paper on "Octahedral Tucker is PPA-Complete", now available on ECCC.

[6/2017] New paper on "Optimal Auction through Deep Learning ", now available on ArXiv.

June 12, 2017
Our paper "Optimal Auction through Deep Learning" is now available on ArXiv. Read more about [6/2017] New paper on "Optimal Auction through Deep Learning ", now available on ArXiv.
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Latest News

  • [6/2020] One paper "The Intrinsic Robustness of Stochastic Bandits to Strategic Manipulation" is accepted to ICML 2020.
  • [5/2020] Our paper “Optimal Auctions through Deep Learning” was invited to appear as a Research Highlight in the Communications of the ACM!
  • [4/2019] Our paper "Optimal Auctions through Deep Learning" is accepted in ICML'19.
  • [3/2019] I was named one of the 2019 Google PhD Fellows.
  • [1/2019] One paper "Online Learning for Measuring Incentive Compatibility in Ad Auctions" is accepted in WWW'19
More
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