Zobrazeno 1 - 10
of 88 317
pro vyhledávání: '"Computer Science - Information Theory"'
Motivated by real-world applications that necessitate responsible experimentation, we introduce the problem of best arm identification (BAI) with minimal regret. This innovative variant of the multi-armed bandit problem elegantly amalgamates two of i
Externí odkaz:
http://arxiv.org/abs/2409.18909
In this paper, we depart from the widely-used gradient descent-based hierarchical federated learning (FL) algorithms to develop a novel hierarchical FL framework based on the alternating direction method of multipliers (ADMM). Within this framework,
Externí odkaz:
http://arxiv.org/abs/2409.18796
Autor:
Olasunkanmi, Olawumi, Morris, Evan, Kebede, Yaphet, Lee, Harlin, Ahalt, Stanley, Tropsha, Alexander, Bizon, Chris
Knowledge graphs (KGs) represent connections and relationships between real-world entities. We propose a link prediction framework for KGs named Enrichment-Driven GrAph Reasoner (EDGAR), which infers new edges by mining entity-local rules. This appro
Externí odkaz:
http://arxiv.org/abs/2409.18659
Autor:
Balsubramani, Akshay
Artificial intelligence models trained through loss minimization have demonstrated significant success, grounded in principles from fields like information theory and statistical physics. This work explores these established connections through the l
Externí odkaz:
http://arxiv.org/abs/2409.18630
Autor:
Perrault, Pierre, Belomestny, Denis, Ménard, Pierre, Moulines, Éric, Naumov, Alexey, Tiapkin, Daniil, Valko, Michal
In this paper, we introduce a novel approach for bounding the cumulant generating function (CGF) of a Dirichlet process (DP) $X \sim \text{DP}(\alpha \nu_0)$, using superadditivity. In particular, our key technical contribution is the demonstration o
Externí odkaz:
http://arxiv.org/abs/2409.18621
This paper considers the $\varepsilon$-differentially private (DP) release of an approximate cumulative distribution function (CDF) of the samples in a dataset. We assume that the true (approximate) CDF is obtained after lumping the data samples into
Externí odkaz:
http://arxiv.org/abs/2409.18573
In this paper we consider a Metzner-Kapturowski-like decoding algorithm for high-order interleaved sum-rank-metric codes, offering a novel perspective on the decoding process through the concept of an error code. The error code, defined as the linear
Externí odkaz:
http://arxiv.org/abs/2409.18488
Autor:
Lee, Hyeongtaek, Choi, Junil
In realistic cellular communication systems, multiple service providers will operate within different frequency ranges. Each serving cell, which is managed by a distinct service provider, is designed individually due to the orthogonal frequencies. Ho
Externí odkaz:
http://arxiv.org/abs/2409.18465
Hierarchical search in millimeter-wave (mmWave) communications incurs significant beam training overhead and delay, especially in a dynamic environment. Deep learning-enabled beam prediction is promising to significantly mitigate the overhead and del
Externí odkaz:
http://arxiv.org/abs/2409.18429
We study the problem of blind super-resolution, which can be formulated as a low-rank matrix recovery problem via vectorized Hankel lift (VHL). The previous gradient descent method based on VHL named PGD-VHL relies on additional regularization such a
Externí odkaz:
http://arxiv.org/abs/2409.18387