arXiv:2412.19634v2 Announce Type: replace-cross Abstract: Marked temporal point processes (MTPPs) model sequences of events occurring at irregular time intervals, with wide-ranging applications in fields such as healthcare, finance and social networks. We propose the state-space point process (S2P2) model, a…
arXiv:2510.20055v1 Announce Type: new Abstract: Online advertising platforms use automated auctions to connect advertisers with potential customers, requiring effective bidding strategies to maximize profits. Accurate ad impact estimation requires considering three key factors: delayed and long-term effects, cumulative ad impacts…
arXiv:2505.17203v2 Announce Type: replace-cross Abstract: We study contextual dynamic pricing when a target market can leverage K auxiliary markets — offline logs or concurrent streams — whose mean utilities differ by a structured preference shift. We propose Cross-Market Transfer Dynamic…
arXiv:2510.20064v1 Announce Type: new Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection problem in speculative decoding. We design an algorithm that provably competes with…
arXiv:2507.16068v3 Announce Type: replace-cross Abstract: Multi-robot coordination has traditionally relied on a mission-specific and expert-driven pipeline, where natural language mission descriptions are manually translated by domain experts into mathematical formulation, algorithm design, and executable code. This conventional process is labor-intensive,…
arXiv:2510.20066v1 Announce Type: new Abstract: We study whether liquidity and volatility proxies of a core set of cryptoassets generate spillovers that forecast market-wide risk. Our empirical framework integrates three statistical layers: (A) interactions between core liquidity and returns, (B) principal-component…
arXiv:2510.12988v2 Announce Type: replace-cross Abstract: As virtual reality (VR) devices become increasingly integrated into everyday settings, a growing number of users without prior experience will engage with VR systems. Automatically detecting a user’s familiarity with VR as an interaction medium…
arXiv:2510.20068v1 Announce Type: new Abstract: Simultaneous recordings from thousands of neurons across multiple brain areas reveal rich mixtures of activity that are shared between regions and dynamics that are unique to each region. Existing alignment or multi-view methods neglect temporal…
arXiv:2405.12412v3 Announce Type: replace Abstract: While significant progress has been made in specifying neural networks capable of representing uncertainty, deep networks still often suffer from overconfidence and misaligned predictive distributions. Existing approaches for measuring this misalignment are primarily developed under…
arXiv:2510.20084v1 Announce Type: new Abstract: Explaining time series classification models is crucial, particularly in high-stakes applications such as healthcare and finance, where transparency and trust play a critical role. Although numerous time series classification methods have identified key subsequences, known…
