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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/2407.10811v1
II RELATED WORK
II-A Traditional methods
II-B RL methods.
III PRELIMINARIES
IV METHOD
IV-A RL Setup
IV-B Network design
IV-C Training
IV-D Theoretical Analysis
V EXPERIMENT
V-A Towards Real-world Dataset and Simulation
V-B Benchmark
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/list/cs.CR/new
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New submissions (showing 32 of 32 entries)
[1] arXiv:2608
https://arxiv.org/html/2608.02800v1
com in China, Walmart Marketplace and Target Plus in the United States, Otto in Germany, Flipkart in India, and Rakuten in Japan
https://arxiv.org/html/2607.26405v1
& Optimal Design
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https://arxiv.org/html/2407.08254v2
We prove that our approach guarantees that the average joint action of all agents converges to a Nash equilibrium (NE) if every agent applies the same RM procedure in any cooperative game with a submodular utility function
https://arxiv.org/html/2407.06328v2
In such dynamic game settings, if agents have limited capabilities for observing the game’s state, they must estimate it and use this estimate to infer expected payoffs and select one of available strategies
https://arxiv.org/html/2608.03573v1
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arXiv:2608
https://arxiv.org/html/2412.12213v2
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https://arxiv.org/html/2407.20187v1
If there are more blue nodes than red nodes then we say blue is the majority
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/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/math/new
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New submissions (showing 219 of 219 entries)
[1] arXiv:2608
https://arxiv.org/src/2006.02735
Sãý°ËŒ‡d \Üǹç^´^”o~™fer“,´-ÆÞ¼ÿ䣿Nðzúô±¼ã5|?}öèäÉÓON=}úôôÑé)¯ãýÑÓOÔÉÇe÷Õ8¯k¥>©ËÒß7î·~ÿ?ú:R“´LšÜ>É´sW§g•©¿•M]èl¤ÊÂ$eÖäÅõêÍ«W¯|‹õááÎ]igøèŠr=õn)NØ¿yëNWv#O†#¹LãL¥“=7+�;·Ì§#¼çÚ/F ü"©Äzƒy{CËÊÔµ™Õ‘Jj£½Qr)³Å�Œœ×ºZØäýðþ¸ÔÎE®;¼È+¾
https://arxiv.org/pdf/2006.00812
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https://arxiv.org/src/2405.20232
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https://arxiv.org/pdf/2407.00768
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https://arxiv.org/pdf/2006.02055
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https://arxiv.org/pdf/2010.15980v1
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https://arxiv.org/pdf/2010.15980
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https://arxiv.org/pdf/2608.03494
ºuàÇüŒŸók~ÃãùjóQéJ|Ì“Õ&…3>áÓu#Vò”ßñy¼¸Ç|Á[¾ÔŽÆ7¥§ñœçñ–ßóü'ÿý0ãp¥6uLÃ8ªƒÛ½˜¬£¥º˜ä¥ ‚ÃæñHA؃ ¡úÖÆ®Diã17pBï©áÜ=L;´�qm0fMØF> endobj 92 0 obj > stream xœÍ[Ýo¹ï_ÁÇöÁk’ÃOààÒCzZôpw@Ó÷ Kk[±¬5ô‘äî¯ïo¸³«µe9ŽÖBüsµKœÎ™LJ«ìá¯W1¨”
https://arxiv.org/pdf/2608.03095
™æ×ÏéÖÖ’W“[G³÷éïtËaÄ!q$|� I¤ Pˆ`$ž¥Éè :�ïš¾^�á, k*̾Æè(JÎÑß[Eô“N‡ß_ëaô]õ߯€÷àl€¶ÆE1Í_Á0�wÒl¼Ãµ8p v¨Äz3lœÄwQ’G¥ÈÜYcñCt—Þß§Iîä'%O|{ ø@ìDYšo肋áö`%E\ “ å¶z\A@ݼOîÒ¡u;ð>Ͼ®VlÅ`¸¤WI|gË‹ÖuWÖ’sbc§ Ÿó"º$ßSd¥Î²a”Y
https://arxiv.org/pdf/2609.18842
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https://arxiv.org/pdf/2608.02872
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https://arxiv.org/pdf/2608.03138
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https://arxiv.org/pdf/2608.02244
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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2608.02625
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