This paper proposes a synthetic control (SC) framework for the estimation of conditional distributional treatment effects. Identification rests on a parallel trends condition formulated in the paramet...
The seminal work of Goldreich and Ron (\textit{Combinatorica, 1999}) showed that bipartiteness of bounded-degree graphs can be tested using $O(\sqrt{n\log n})$ random walks of length $O(\log^{6} n)$. ...
We establish new exponential in dimension lower bounds for the Maximum Halfspace Discrepancy problem, which models linear classification. Both are fundamental problems in computational geometry and ma...
Current automated pipelines for audio-visual Question Answering (QA) generally adopt a ``video-caption-QA'' paradigm. However, these methods typically segment videos into short clips and generate sepa...
Passive models for long video understanding typically rely on a "watch-it-all" paradigm, processing frames uniformly regardless of query difficulty, causing computational cost to grow with video durat...
In this paper, we develop a stratification-based semantics for Signal Temporal Logic (STL) in which each atomic predicate is interpreted as a membership test in a stratified space. This perspective re...
To obtain more accurate model parameters and improve prediction accuracy, we proposed a regularized Kriging model that penalizes the hyperparameter theta in the Gaussian stochastic process, termed the...
Human collective participation is rarely steady in time: it is bursty, with short episodes of intense activity separated by long quiet intervals. In crisis response and community mobilization, predict...
We introduce Teleodynamic Learning, a new paradigm for machine learning in which learning is not the minimization of a fixed objective, but the emergence and stabilization of functional organization u...
We propose a method for non-parametric conditional distribution estimation based on partitioning covariate-sorted observations into contiguous bins and using the within-bin empirical CDF as the predic...
Generative artificial intelligence (AI) is increasingly integrated into the online platforms where humans exchange opinions; large language models (LLMs) now polish users' posts on LinkedIn and provid...
We introduce the CLUSTER algorithm (\textbf{c}oordinate-\textbf{l}evel \textbf{u}pdate \textbf{s}trategy for \textbf{t}rust-region step \textbf{e}valuation \textbf{r}efinement) for local derivative-fr...
This paper investigates "free lunch" strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectural redesigns. We first demonstrate that endowing ...
To address the problems of high-power consumption, large weight-on-bit, significant disturbance, and difficulties in sealing and waterproofing in the traditional Deep-sea Seafloor Drill, a novel piezo...
Underwater tactile force sensing is crucial for achieving nondestructive and stable object manipulation in ocean robotics, especially in deep-sea environments where traditional vision-based methods ar...
Earth observation satellites transform our understanding of Earth's biological, atmospheric, and surface systems. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, launched in 2024, repres...
Electrochemical turning is an efficient machining method for machining Ti80 pressure-resistant structures owing to its low tool cost and high machining flexibility. However, research has yet to explor...
Despite the remoteness of their breeding sites, subantarctic seabirds are susceptible to anthropogenic pollutants (e.g. microplastics) and other chemical stressors (e.g. plastic additives) that are re...
This paper proposes a robust navigation method based on a robust square-root cubature Kalman filter (RSRCKF) to address the accuracy divergence of integrated navigation systems caused by drilling-indu...
The order Dendrochirotida (Class Holothuroidea) is a species-rich echinoderm group, yet its internal evolutionary history remains poorly resolved due to limited mitogenomic resources. In this study, w...
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