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30 result(s) for “if com receive site lemma would site have apache org site:arxiv.org” of 93 matched · page 2 · 492 ms
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Freshness: newest result fetched 27 d ago · median age of these results 27 d · 1 of 30 carry a fetch time
https://arxiv.org/html/2407.20187v1
If a personal decision to vaccinate oneself is influenced by the actions of people in your local social network then misinformation here may have significant consequences
https://arxiv.org/html/2309.08431v3
Concentration risk refers to the decrease in fee revenue if the marginal exchange rate (akin to the midprice in a limit order book) in the pool exits the LP’s range of liquidity
https://arxiv.org/html/2511.06451v1
1 Data Protocol (arXiv Release)
Synthetic risk–neutral generator
https://arxiv.org/list/math/new
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https://arxiv.org/list/cs.LG/2022-12
2001-2004
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https://arxiv.org/html/2608.02942v1
org perpetual non-exclusive license
arXiv:2608
https://arxiv.org/html/2508.20108v2
Normalization for Accurate Prediction
1 Introduction
2 Related Works
2.1 Geometric Brownian Motion
2.2 Deep Learning-Based Stock Price Prediction
2.3 Methods for Addressing Distribution Shift
3 Proposed Method
3.1 Overview
3.2 Return
https://arxiv.org/html/2608.03067v1
, 2025), while more recent studies have learned AD-related patterns directly from patient language through fine-tuning, representation learning, and prompting (Balagopalan et al
https://arxiv.org/html/2508.20101v1
Most of the spatiotemporal GARCH models have been developed for areal data or fixed sets of spatial locations (a notable exception is the stochastic volatility model of Huang et al
https://arxiv.org/html/2608.02909v1
In practice, most researchers use the generated variables “as is” on the right-hand side of the regression, as if they captured the true, latent variable of interest
https://arxiv.org/html/2607.28294v1
This feature fundamentally shapes the asymptotic framework, particularly so when the durations do not have finite expectation
https://arxiv.org/html/2407.20441v1
Abstract
Recent research endeavours have theoretically shown the beneficial effect of cooperation in multi-agent reinforcement learning (MARL)
https://arxiv.org/html/2412.12213v2
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https://arxiv.org/html/2407.15077v2
However, the non-stationarity problem still persists, especially when agents only have partial observations, making policy optimization more challenging
https://arxiv.org/html/2407.04974v1
When multiple agents are deployed across an environment, they may only have access to limited information, observing only specific portions of the overall environment
https://arxiv.org/html/2407.05763v1
A system is said to be finite-time stable if it is Lyapunov stable and its states reach zeros at a finite instant of time (which may depend on the initial state of the system)
https://arxiv.org/list/cs.CG/new
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[1] arXiv:2608
https://arxiv.org/list/q-fin.MF/2021-04
A lacuna in the proof of the old Lemma 3
https://arxiv.org/html/2607.29442v2
1footnoteFootnotefootnotesFootnotes1footnote 1We are grateful to Carsten Chong for fruitful discussions on rough noise. We benefitted from comments by and discussions with Kim Christensen, Mikko Pakkanen, Bent Jesper Christensen, and Mikkel
https://arxiv.org/pdf/1811.12628
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https://arxiv.org/pdf/2508.11152
com three Proceedings of ACM Conference (Conference'17) book 1 1 9 9 Tianjiao ZhaoJingrao LyuStokes JonesHarrison GarberStefano PasqualiDhagash Mehtahttp://arxiv
https://arxiv.org/pdf/2609.18842
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https://arxiv.org/pdf/2608.02694
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https://arxiv.org/pdf/2607.26327v3
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https://arxiv.org/pdf/2506.01844
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient RoboticsMustafa ShukorDana AubakirovaFrancesco CapuanoPepijn KooijmansSteven PalmaAdil ZouitineMichel AractingiCaroline PascalMartino RussiAndres MarafiotiSimon
https://arxiv.org/src/1910.03771
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https://arxiv.org/pdf/2608.02609
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