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https://arxiv.org/list/cs.NA/new
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New submissions (showing 18 of 18 entries)
[1] arXiv:2608
https://arxiv.org/html/2508.20101v1
In an empirical application, we demonstrate how the model can be applied to financial stock networks
https://arxiv.org/list/cs.CR/new
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New submissions (showing 32 of 32 entries)
[1] arXiv:2608
https://arxiv.org/list/cs.SE/new
Yet it remains unclear when further evolution helps, how successful and failed trajectories shape revision, and whether extra test-time computation can recover the same gains
https://arxiv.org/html/2407.20441v1
I Introduction
Training reinforcement learning (RL) algorithms is well-known to be a critically time consuming task that can require several data samples to achieve a desired level of accuracy
https://arxiv.org/html/2608.02817v1
expressed here are those of the authors and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve System. The authors are grateful for the invaluable feedback they received on an earlier draft from Jón
https://arxiv.org/html/2508.02739v1
2 Preliminary
3 Methodology
K-line Tokenization
Hierarchical Autoregressive Modeling
Model Pre-training
Dataset
Model Training
Inference
4 Experiments
Experimental Setup
Main Results
Prediction Tasks
Generative Tasks
Investment
https://arxiv.org/list/quant-ph/new
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https://arxiv.org/html/2407.18010v2
We prove the game respects a dynamic programming principle and that the Markov perfect equilibrium can be computed as a limit point of a sequence of Bellman operations
https://arxiv.org/list/cs.CV/new
Project Page: this https URL
[2] arXiv:2608
https://arxiv.org/html/2407.05763v1
(2023) present the sole result on the fixed-time distributed observer, utilizing a kernel-based design approach
https://arxiv.org/list/math/new
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New submissions (showing 219 of 219 entries)
[1] arXiv:2608
https://arxiv.org/list/math.ST/2024-03
00186 [pdf, html, other]
Title: Warped Kernel Estimator for I
https://arxiv.org/list/eess/new
The design relies on two affine Volterra transformations involving both Fredholm- and Volterra-type integral terms, which results in a four-PIDE kernel equations
https://arxiv.org/abs/2504.02246
C* extends C with verification capabilities, powered by a symbolic execution engine and an LCF-style proof kernel
https://arxiv.org/list/cs.LG/2022-12
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[1] arXiv:2212
https://arxiv.org/list/astro-ph.SR/new
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New submissions (showing 19 of 19 entries)
[1] arXiv:2608
https://arxiv.org/html/2608.03411v1
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https://arxiv.org/pdf/2608.01651v1
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https://arxiv.org/pdf/2608.03883
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/abs/2608.03860
The pipeline combines sentence-window chunking, BM25, BGE-M3 dense retrieval, reciprocal rank fusion, optional cross-encoder reranking, and grounded answer generation
https://arxiv.org/pdf/2608.04341
) /Title (Continuous Improvement and Parallel Autonomous Exploration: An LLM-Agent Framework for Searching Large Solution Spaces) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.02764
~ €'Ñ£ö—³ê° `Á‰çÄ"± m�Óšc3á8{�ck'NÕ: µ‡œãLº¤q]œ\—�s@Î1uœñÑfìq®œ#ô ´™òØ£1²¯Ø> c¥%câðxA{5fv®MKDoußtßõÉP}¿²›tΣ)÷•8sjtíÙ1ñŸ7´µôæ›×&—-âü·âùòlõ×eë±¾}óÏö�í¶�’_±'ºæK¶W×(&H‹—›¤|�üÐŒ§„2šË¿P"§±”ÍFAHŠ3Qˆ„cy
https://arxiv.org/pdf/2607.28577v1
) /Title (Train Often, Deploy Selectively: Forward-Gated Model Replacement in Crypto Markets) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2607.28410v1
©’ðÐÿ~N·68^Õ°œûõ¹ï�„ÀpÁ@€` bH0„$"HP’~€ ¯Èb¤`Ft¡3¦“rƾ\^BÐÓ•û‚Áíâa¹ºHÍzôRšÔ”¿MµþÚ+vÙö›"Ë÷[H$!ÜA0Ì˪î?阤%øfªM™?×EIõ¸õšêÆ ƒàþð«~y6¤ô�tË}Ny֤͑'»åYåYýT�ŠN¦««îíb> endobj 15 0 obj > stream xœí\Ys9’~Ÿ_�Çݘ°Q(œ11±’
https://arxiv.org/pdf/2607.27188v1
) /Title (Inverse Learning of Latent Risk-Neutral Densities from Irregular Option Quotes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.03063
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https://arxiv.org/pdf/2608.02122
) /Title (DEFT: Joint Task Placement and DVFS for Energy-Efficient Multi-GPU Runtimes) /Trapped /False /arXivID (https://arxiv
https://arxiv.org/pdf/2608.01785
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