Zobrazeno 1 - 10
of 76
pro vyhledávání: '"Maria Florina Balcan"'
Publikováno v:
AAAI
Algorithms typically come with tunable parameters that have a considerable impact on the computational resources they consume. Too often, practitioners must hand-tune the parameters, a tedious and error-prone task. A recent line of research provides
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fca962747e5d7d8e0d64962a17f2b4c6
https://doi.org/10.1609/aaai.v34i04.5721
https://doi.org/10.1609/aaai.v34i04.5721
Publikováno v:
Theoretical Computer Science. 808:14-37
An important long-term goal in machine learning systems is to build learning agents that, like humans, can learn many tasks over their lifetime, and moreover use information from these tasks to improve their ability to do so efficiently. In this work
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::034b68e790454effee0ac1aa6ea623cd
https://doi.org/10.1016/j.tcs.2019.11.010
https://doi.org/10.1016/j.tcs.2019.11.010
Publikováno v:
IJCAI
We develop a new framework for designing truthful, high-revenue (combinatorial) auctions for limited supply. Our mechanism learns within an instance. It generalizes and improves over previously-studied random-sampling mechanisms. It first samples a p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d0b15ea145298f20a3275c86fdff6b7
https://doi.org/10.24963/ijcai.2021/5
https://doi.org/10.24963/ijcai.2021/5
Autor:
Maria-Florina Balcan
Publikováno v:
Beyond the Worst-Case Analysis of Algorithms
Data driven algorithm design is an important aspect of modern data science and algorithm design. Rather than using off the shelf algorithms that only have worst case performance guarantees, practitioners often optimize over large families of parametr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f52ec860abb1ead24eb094480ba74ba9
https://doi.org/10.1017/9781108637435.036
https://doi.org/10.1017/9781108637435.036
Autor:
Nika Haghtalab, Maria-Florina Balcan
Publikováno v:
Beyond the Worst-Case Analysis of Algorithms
This chapter considers the computational and statistical aspects of learning linear thresholds in presence of noise. When there is no noise, several algorithms exist that efficiently learn near-optimal linear thresholds using a small amount of data.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b493ecf674238988a03a0212b3f38146
https://doi.org/10.1017/9781108637435.022
https://doi.org/10.1017/9781108637435.022
Publikováno v:
IJCAI
A two-part tariff is a pricing scheme that consists of an up-front lump sum fee and a per unit fee. Various products in the real world are sold via a menu, or list, of two-part tariffs---for example gym memberships, cell phone data plans, etc. We stu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::56dc483f624f51b5608df44fc71174bb
https://doi.org/10.24963/ijcai.2020/47
https://doi.org/10.24963/ijcai.2020/47
Publikováno v:
SIAM Journal on Computing. 47:703-754
Submodular functions are discrete functions that model laws of diminishing returns and enjoy numerous algorithmic applications. They have been used in many areas, including combinatorial optimization, machine learning, and economics. In this work we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3f6b2304603b2daaef6b9f9dee29c7f
https://doi.org/10.1137/120888909
https://doi.org/10.1137/120888909
Portfolio-based algorithm selection has seen tremendous practical success over the past two decades. This algorithm configuration procedure works by first selecting a portfolio of diverse algorithm parameter settings, and then, on a given problem ins
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10500cdb0980d096e93b4989dc8743a9
Autor:
Dan DeBlasio, Carl Kingsford, Tuomas Sandholm, Maria-Florina Balcan, Travis Dick, Ellen Vitercik
Publikováno v:
STOC
Algorithms often have tunable parameters that impact performance metrics such as runtime and solution quality. For many algorithms used in practice, no parameter settings admit meaningful worst-case bounds, so the parameters are made available for th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5fbf8d5aa6ac8d260730b0a47d8c32dd
http://arxiv.org/abs/1908.02894
http://arxiv.org/abs/1908.02894
Publikováno v:
EC
In practice, most mechanisms for selling, buying, matching, voting, and so on are not incentive compatible. We present techniques for estimating how far a mechanism is from incentive compatible. Given samples from the agents' type distribution, we sh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b1fab76b18b31fddbe673c7d96e80f8
http://arxiv.org/abs/1902.09413
http://arxiv.org/abs/1902.09413