Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Gaitonde, Jason"'
An important task in high-dimensional statistics is learning the parameters or dependency structure of an undirected graphical model, or Markov random field (MRF). Much of the prior work on this problem assumes access to i.i.d. samples from the MRF d
Externí odkaz:
http://arxiv.org/abs/2409.05284
Autor:
Gaitonde, Jason, Mossel, Elchanan
We consider the problem of linear regression with self-selection bias in the unknown-index setting, as introduced in recent work by Cherapanamjeri, Daskalakis, Ilyas, and Zampetakis [STOC 2023]. In this model, one observes $m$ i.i.d. samples $(\mathb
Externí odkaz:
http://arxiv.org/abs/2402.14229
Autor:
Gaitonde, Jason, Mossel, Elchanan
We revisit the problem of efficiently learning the underlying parameters of Ising models from data. Current algorithmic approaches achieve essentially optimal sample complexity when given i.i.d. samples from the stationary measure and the underlying
Externí odkaz:
http://arxiv.org/abs/2311.09197
Autor:
Alaoui, Ahmed El, Gaitonde, Jason
We consider the Sherrington-Kirkpatrick model with no external field and inverse temperature $\beta<1$ and prove that the expected operator norm of the covariance matrix of the Gibbs measure is bounded by a constant depending only on $\beta$. This an
Externí odkaz:
http://arxiv.org/abs/2212.02445
We study the aggregate welfare and individual regret guarantees of dynamic \emph{pacing algorithms} in the context of repeated auctions with budgets. Such algorithms are commonly used as bidding agents in Internet advertising platforms, adaptively le
Externí odkaz:
http://arxiv.org/abs/2205.08674
We study the relationship between the underlying structure of posets and the spectral and combinatorial properties of their higher-order random walks. While fast mixing of random walks on hypergraphs has led to myriad breakthroughs throughout theoret
Externí odkaz:
http://arxiv.org/abs/2205.00644
Autor:
GAITONDE, JASON1 jsg355@cornell.edu, TARDOS, ÉVA1 eva.tardos@cs.cornell.edu
Publikováno v:
Journal of the ACM. Jun2023, Vol. 70 Issue 3, p1-63. 63p.
In light of increasing recent attention to political polarization, understanding how polarization can arise poses an important theoretical question. While more classical models of opinion dynamics seem poorly equipped to study this phenomenon, a rece
Externí odkaz:
http://arxiv.org/abs/2106.12459
Autor:
Gaitonde, Jason, Tardos, Eva
We consider the problem of selfish agents in discrete-time queuing systems, where competitive queues try to get their packets served. In this model, a queue gets to send a packet each step to one of the servers, which will attempt to serve the oldest
Externí odkaz:
http://arxiv.org/abs/2011.10205
We prove new results on the polarizing random walk framework introduced in recent works of Chattopadhyay {et al.} [CHHL19,CHLT19] that exploit $L_1$ Fourier tail bounds for classes of Boolean functions to construct pseudorandom generators (PRGs). We
Externí odkaz:
http://arxiv.org/abs/2008.01316