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arXiv:2210.01410v2 Announce Type: replace Abstract: The rapid growth of data generated from Internet of Things (IoTs) such as smart phones and smart home devices presents...
arXiv:2210.17174v5 Announce Type: replace Abstract: We propose uBFT, the first State-Machine Replication (SMR) system to achieve microsecond-scale latency in data centers, while using only $2f{+}1$...
arXiv:2211.15549v2 Announce Type: replace Abstract: Portrait Stylization aims to imbue portrait photos with vivid artistic effects drawn from style examples. Despite the availability of enormous...
arXiv:2212.01211v5 Announce Type: replace Abstract: In the art gallery problem, we are given a closed polygon $P$, with rational coordinates and an integer $k$. We...
arXiv:2301.02102v3 Announce Type: replace Abstract: A decentralized identity system that can provide users with self-sovereign digital identities to facilitate complete control over their own data...
arXiv:2302.07033v3 Announce Type: replace Abstract: Disjoint-paths logic, denoted $\mathsf{FO}$+$\mathsf{dp}$, extends first-order logic ($\mathsf{FO}$) with atomic predicates $\mathsf{dp}_r[(x_1,y_1),\ldots,(x_r,y_r)]$, expressing the existence of vertex-disjoint paths between $x_i$...
arXiv:2302.12093v5 Announce Type: replace Abstract: We study randomized experiments in a service system when stochastic congestion can arise from temporarily limited supply or excess demand....
arXiv:2303.09807v3 Announce Type: replace Abstract: Video prediction is a complex time-series forecasting task with great potential in many use cases. However, traditional methods prioritize accuracy...
arXiv:2307.14397v3 Announce Type: replace Abstract: Generative modeling in machine learning aims to synthesize new data samples that are statistically similar to those observed during training....
arXiv:2308.06403v2 Announce Type: replace Abstract: By definition, people are reticent or even unwilling to talk about taboo subjects. Because subjects like sexuality, health, and violence...
arXiv:2312.02355v2 Announce Type: replace Abstract: Offline reinforcement learning algorithms often require careful hyperparameter tuning. Before deployment, we need to select amongst a set of candidate...
arXiv:2401.05057v2 Announce Type: replace Abstract: This work introduces the BoundMPC strategy, an innovative online model-predictive path-following approach for robot manipulators. This joint-space trajectory planner allows...
arXiv:2402.02644v4 Announce Type: replace Abstract: Estimating the structure of Bayesian networks as directed acyclic graphs (DAGs) from observational data is a fundamental challenge, particularly in...
arXiv:2402.15751v2 Announce Type: replace Abstract: While fine-tuning large language models (LLMs) for specific tasks often yields impressive results, it comes at the cost of memory...
arXiv:2402.16803v4 Announce Type: replace Abstract: Incorporating probabilistic terms in mathematical models is crucial for capturing and quantifying uncertainties in real-world systems, especially when the solution...
arXiv:2403.10723v4 Announce Type: replace Abstract: Quadrupedal robots exhibit a wide range of viable gaits, but generating specific footfall sequences often requires laborious expert tuning of...
arXiv:2403.15605v2 Announce Type: replace Abstract: Domain shift is a formidable issue in Machine Learning that causes a model to suffer from performance degradation when tested...
arXiv:2404.08634v4 Announce Type: replace Abstract: Large Language Models (LLMs) are known for their performance, but we uncover a significant structural inefficiency: a phenomenon we term...
arXiv:2404.10652v4 Announce Type: replace Abstract: Visual Question Answerinng (VQA) is a complicated task that requires the capability of simultaneously processing natural language and images. This...
arXiv:2404.12568v3 Announce Type: replace Abstract: In a Jacobi--Davidson (JD) type method for singular value decomposition (SVD) problems, called JDSVD, a large symmetric and generally indefinite...
arXiv:2404.13895v4 Announce Type: replace Abstract: Learning of preference models from human feedback has been central to recent advances in artificial intelligence. Motivated by the cost...
arXiv:2405.14273v5 Announce Type: replace Abstract: A data-driven inverse optimization problem (DDIOP) seeks to estimate an objective function (i.e., weights) that is consistent with observed optimal-solution...
arXiv:2406.04955v2 Announce Type: replace Abstract: Deploying robots in human-shared environments requires a deep understanding of how nearby agents and objects interact. Employing causal inference to...
arXiv:2406.05808v3 Announce Type: replace Abstract: The Landau--Lifshitz--Bloch equation (LLBE) describes the evolution of the magnetic spin field in ferromagnets at high temperatures. In this paper,...