Zobrazeno 1 - 10
of 1 244
pro vyhledávání: '"A. Balcan"'
Data-driven algorithm design automatically adapts algorithms to specific application domains, achieving better performance. In the context of parameterized algorithms, this approach involves tuning the algorithm's hyperparameters using problem instan
Externí odkaz:
http://arxiv.org/abs/2409.04367
Overcoming the impact of selfish behavior of rational players in multiagent systems is a fundamental problem in game theory. Without any intervention from a central agent, strategic users take actions in order to maximize their personal utility, whic
Externí odkaz:
http://arxiv.org/abs/2409.03129
Decision trees are a popular tool in machine learning and yield easy-to-understand models. Several techniques have been proposed in the literature for learning a decision tree classifier, with different techniques working well for data from different
Externí odkaz:
http://arxiv.org/abs/2405.15911
Algorithms for playing in Stackelberg games have been deployed in real-world domains including airport security, anti-poaching efforts, and cyber-crime prevention. However, these algorithms often fail to take into consideration the additional informa
Externí odkaz:
http://arxiv.org/abs/2402.08576
Unlabeled data is a key component of modern machine learning. In general, the role of unlabeled data is to impose a form of smoothness, usually from the similarity information encoded in a base kernel, such as the $\epsilon$-neighbor kernel or the ad
Externí odkaz:
http://arxiv.org/abs/2402.00645
Sequence-independent lifting is a procedure for strengthening valid inequalities of an integer program. We generalize the sequence-independent lifting method of Gu, Nemhauser, and Savelsbergh (GNS lifting) for cover inequalities and correct an error
Externí odkaz:
http://arxiv.org/abs/2401.13773
Solving a linear system $Ax=b$ is a fundamental scientific computing primitive for which numerous solvers and preconditioners have been developed. These come with parameters whose optimal values depend on the system being solved and are often impossi
Externí odkaz:
http://arxiv.org/abs/2310.02246
Autor:
Balcan, Maria-Florina1 ninamf@cs.cmu.edu, Dick, Travis2 tdick@google.com, Sandholm, Tuomas3 sandholm@cs.cmu.edu, Vitercik, Ellen4 vitercik@stanford.edu
Publikováno v:
Journal of the ACM. Apr2024, Vol. 71 Issue 2, p1-73. 73p.
Autor:
Khodak, Mikhail, Osadchiy, Ilya, Harris, Keegan, Balcan, Maria-Florina, Levy, Kfir Y., Meir, Ron, Wu, Zhiwei Steven
We study online meta-learning with bandit feedback, with the goal of improving performance across multiple tasks if they are similar according to some natural similarity measure. As the first to target the adversarial online-within-online partial-inf
Externí odkaz:
http://arxiv.org/abs/2307.02295
Publikováno v:
NeurIPS 2023
The problem of designing learners that provide guarantees that their predictions are provably correct is of increasing importance in machine learning. However, learning theoretic guarantees have only been considered in very specific settings. In this
Externí odkaz:
http://arxiv.org/abs/2304.03370