Zobrazeno 1 - 10
of 32 817
pro vyhledávání: '"AZEEM, A."'
The primary challenge in Video Object Detection (VOD) is effectively exploiting temporal information to enhance object representations. Traditional strategies, such as aggregating region proposals, often suffer from feature variance due to the inclus
Externí odkaz:
http://arxiv.org/abs/2412.04915
As sample sizes grow, scalability has become a central concern in the development of Markov chain Monte Carlo (MCMC) methods. One general approach to this problem, exemplified by the popular stochastic gradient Langevin dynamics (SGLD) algorithm, is
Externí odkaz:
http://arxiv.org/abs/2412.01952
Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework for decision-making under uncertainty and partial observability. Since in general optimal policies may require infinite memory, they are hard to implement and often r
Externí odkaz:
http://arxiv.org/abs/2411.13365
Algorithmic analysis of Markov decision processes (MDP) and stochastic games (SG) in practice relies on value-iteration (VI) algorithms. Since the basic version of VI does not provide guarantees on the precision of the result, variants of VI have bee
Externí odkaz:
http://arxiv.org/abs/2411.11549
Enterprises are increasingly adopting serverless computing to enhance scalability, reduce costs, and improve efficiency. However, this shift introduces new responsibilities and necessitates a distinct set of skills for practitioners. This study aims
Externí odkaz:
http://arxiv.org/abs/2411.10344
Autor:
Winnik, Julianna, Zdankowski, Piotr, Stefaniuk, Marzena, Ahmad, Azeem, Zuo, Chao, Ahluwalia, Balpreet S., Trusiak, Maciej
Optical diffraction tomography (ODT) enables non-invasive information-rich 3D refractive index (RI) reconstruction of unimpaired transparent biological and technical samples, crucial in biomedical research, optical metrology, materials sciences, and
Externí odkaz:
http://arxiv.org/abs/2411.08423
Graph convolutional networks (GCNs) are an effective skeleton-based human action recognition (HAR) technique. GCNs enable the specification of CNNs to a non-Euclidean frame that is more flexible. The previous GCN-based models still have a lot of issu
Externí odkaz:
http://arxiv.org/abs/2411.06553
Autor:
Bai, Yuehao, Huang, Shunzhuang, Moon, Sarah, Santos, Andres, Shaikh, Azeem M., Vytlacil, Edward J.
In a setting with a multi-valued outcome, treatment and instrument, this paper considers the problem of inference for a general class of treatment effect parameters. The class of parameters considered are those that can be expressed as the expectatio
Externí odkaz:
http://arxiv.org/abs/2411.05220
While policymakers and researchers are often concerned with conducting inference based on a data-dependent selection, a strictly larger class of inference problems arises when considering multiple data-dependent selections, such as when selecting on
Externí odkaz:
http://arxiv.org/abs/2410.19212
Autor:
Azeem, Muqsit, Chakraborty, Debraj, Kanav, Sudeep, Kretinsky, Jan, Mohagheghi, Mohammadsadegh, Mohr, Stefanie, Weininger, Maximilian
Despite the advances in probabilistic model checking, the scalability of the verification methods remains limited. In particular, the state space often becomes extremely large when instantiating parameterized Markov decision processes (MDPs) even wit
Externí odkaz:
http://arxiv.org/abs/2410.18293