Blog
Asymptotics of Yule’s nonsense correlation for Ornstein-Uhlenbeck paths: The correlated case
We study the continuous-time version of the empirical correlation coefficient between the paths of two possibly correlated Ornstein-Uhlenbeck processes, known as Yule’s nonsense correlation for these paths. Using sharp tools from the analysis on Wiener chaos, we establish the asymptotic normality of...
Approximating fluid queues with quasi birth-and-death processes with rational arrival process components
A fluid queue is a stochastic process which moves linearly with a rate that is determined by the state of a continuous-time Markov chain (CTMC). In this paper we construct an approximation to a fluid queue using a quasi birth-and-death process with...
How to Grow an LSM-tree? Towards Bridging the Gap Between Theory and Practice
LSM-tree based key-value stores are widely adopted as the data storage backend in modern big data applications. The LSM-tree grows with data ingestion, by either adding levels with fixed level capacities (dubbed as vertical scheme) or increasing level capacities with fixed number...
Evaluating Learned Query Performance Prediction Models at LinkedIn: Challenges, Opportunities, and Findings
Recent advancements in learning-based query performance prediction models have demonstrated remarkable efficacy. Tuttavia, these models are predominantly validated using synthetic datasets focused on cardinality or latency estimations. This paper explores the application of these models to LinkedIn’s complex real-world OLAP queries executed...
DualAttWaveNet: Multiscale Attention Networks for Satellite Interference Detection
The escalating overlap between non-geostationary orbit (NGSO) and geostationary orbit (GSO) satellite frequency allocations necessitates accurate interference detection methods that address two pivotal technical gaps: computationally efficient signal analysis for real-time operation, and robust anomaly discrimination under varying interference patterns. Existing deep...
A general approach to modeling environmental mixtures with multivariate outcomes
An important goal of environmental health research is to assess the health risks posed by mixtures of multiple environmental exposures. In these mixtures analyses, flexible models like Bayesian kernel machine regression and multiple index models are appealing because they allow for arbitrary...
A Double-Norm Aggregated Tensor Latent Factorization Model for Temporal-Aware Traffic Speed Imputation
In intelligent transportation systems (ITS), traffic management departments rely on sensors, cameras, and GPS devices to collect real-time traffic data. Traffic speed data is often incomplete due to sensor failures, data transmission delays, or occlusions, resulting in missing speed data in certain...
Horizontally periodic generalized surface quasigeostrophic patches and layers
We study solutions to the $\alpha$-SQG equations, which interpolate between the incompressible Euler and surface quasi-geostrophic equations. We extend prior results on existence of bounded patches, proving propagation of $H^k$-regularity of the patch boundary, $k \ge 3$, for finite time for patches...
Factually: Exploring Wearable Fact-Checking for Augmented Truth Discernment
Wearable devices are transforming human capabilities by seamlessly augmenting cognitive functions. In this position paper, we propose a voice-based, interactive learning companion designed to amplify and extend cognitive abilities through informal learning. Our vision is threefold: (1) to enable users to discover...
Characterisation of Hamamatsu R11065-20 PMTs for use in the SABRE South NaI(Tl) Crystal Detectors
The SABRE Experiment is a direct detection dark matter experiment using a target composed of multiple NaI(Tl) crystals. The experiment aims to be an independent check of the DAMA/LIBRA results with a detector in the Northern (Laboratori Nazionali Del Gran Sasso, LNGS)...