NishiSearch

Web This site Trusted

30 result(s) for “if cram target site effort com site lemma would site:arxiv.org” of 100 matched · page 2 · 640 ms

Scope: Nishi’s own index (our crawl + Common Crawl) — not the whole live web. Some sites block all automated crawlers (anti-bot walls), so their pages may be absent here even though we never filter lawful content.

Did you mean if cam target site effort com site lemmy would site:arxiv.org?

Freshness: no result on this page carries a fetch time yet (indexed before the fetch epoch was stored beside the doc)

Report GitHub Issue

https://arxiv.org/html/2608.02609v1
× Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to Abstract Download PDF

Asymptotic Equivalence of Immediate and Deferred Acceptance

https://arxiv.org/html/2607.24970v2
That total number of applications mirrors the classical coupon-collector problem: if each breakfast cereal box contains one of nn equally likely coupons, how many cereal boxes do I need to buy to collect all nn coupons

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially

https://arxiv.org/html/2407.04974v1
The primary reason for focusing on this MARL setting is that off-policy learning [6, 7, 8, 9] provides a more general setting compared to its on-policy counterpart, as it allows the behavioral policy to differ from the estimated target policy

Mitigating Distribution Shift in Stock Price Data via Return-Volatility

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

I INTRODUCTION

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

Multi-Currency AMMs for Decentralized FOREX Markets: Feasibility

https://arxiv.org/html/2607.26405v1
& Optimal Design Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report

United We Stand: Decentralized Multi-Agent Planning With Attrition

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

Learning Equilibrium with Estimated Payoffs in Population Games

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

Finance-Informed Neural Network: Learning the Geometry of Option Pricing

https://arxiv.org/html/2412.12213v2
Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to

Eliminating Majority Illusion is Easy

https://arxiv.org/html/2407.20187v1
If there are more blue nodes than red nodes then we say blue is the majority

Forthcoming in SIAM Journal on Financial Mathematics Decentralised

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

1 Introduction

https://arxiv.org/html/2511.06451v1
1 Data Protocol (arXiv Release) Synthetic risk–neutral generator

Economics

https://arxiv.org/list/econ/new
up to 2000 entries per page: fewer | more | all New submissions (showing 21 of 21 entries) [1] arXiv:2608

Homogeneous Distributed Observers for Quasilinear Systems

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)

Mathematics

https://arxiv.org/list/math/new
up to 2000 entries per page: fewer | more | all New submissions (showing 219 of 219 entries) [1] arXiv:2608

arXiv is now an independent nonprofit! Learn more ×

https://arxiv.org/html/2401.02063v2
Description: arXiv is now an independent nonprofit

Hardware Architecture

https://arxiv.org/list/cs.AR/new
more | all New submissions (showing 4 of 4 entries) [1] arXiv:2608

Mathematical Finance Apr 2021

https://arxiv.org/list/q-fin.MF/2021-04
A lacuna in the proof of the old Lemma 3

Systems and Control

https://arxiv.org/list/cs.SY/new
more | all New submissions (showing 8 of 8 entries) [1] arXiv:2608

Information Theory

https://arxiv.org/list/cs.IT/new
all New submissions (showing 11 of 11 entries) [1] arXiv:2608

Microstructural Foundations of Rough Noise1footnote

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

A Heterogeneous Spatiotemporal GARCH Model: A Predictive Framework for

https://arxiv.org/html/2508.20101v1
Volatility in Financial Networks 1 Introduction 2 Heterogeneous Spatiotemporal GARCH model 2.1 Model Assumptions 2.2 Prediction at Unobserved Locations 2.3 Estimation of Parameter Surface 2.4 Properties of the Estimator 3 Monte Carlo

Untitled Document

https://arxiv.org/html/2607.28294v1
Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv Why HTML? Report Issue Back to

Rainfall is rough

https://arxiv.org/html/2607.27099v1
org perpetual non-exclusive license arXiv:2607

Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Transmission Parameter Allocation in Multi-Gateway LoRa Networks I INTRODUCTION II RELATED WORK III SYSTEM MODEL III-A The Traffic Pattern of LoRa Networks III-B Capture Effect and Quasi-Orthogonality between SFs III-C Packet Delivery

1 Introduction

https://arxiv.org/html/2407.15077v2
2 Problem Definition 3 Method 3.1 Monotonic Improvement of B2MAPO scheme 3.2 B2MAPO Framework 3.2.1 Batch Sequence Generation Layer 3.2.2 Batch by Batch Policy Optimization Layer 4 DAG-based B2MAPO Algorithm 4.1 Hierarchical DAG

[2607.28847v1] Effort-Centric Fairness in Lending Decisions

https://arxiv.org/abs/2607.28847v1
We develop an effort-centric framework that measures an applicant's effort as the minimum weighted cost of feasible changes required to cross the approval boundary

%PDF-1.5 %� 207 0 obj > stream xÚ¥V*4ý»®Çý²…?0(Â�ùS�ê±üxGé7öe;”;Ä

https://arxiv.org/pdf/1811.12628
ioªAJÃyØU§±Æ# LFg”À¡ë‡C}Âz¾¹OÒ7ÜtŸXW,Û½¸×·Ý­ÔDZ¤¥bùé�¹n‡‘;• æ] ,¡=h粂7'�6m·¯.>×tÐØv Á}u/ÔÇ|8à ÏÈp­qMùP7õøš™f3îE()Ö½”‡—a¬Ž\¾×ÉÅdYD3²,V:…A3•™„ýñ K+r ‰Ó è:ßtåî 4�!÷ð4}w¨áƒóLožñd»þ#×äà±­È6?úq2UdQL %Ê”‰c7Ð_®·Vo¾§ßïÓÿ1‘q½o

Looking under the Wrong Lamppost: On the Limitations of Automated

https://arxiv.org/html/2608.03577v1
This is precisely why relying solely on mechanical markers of quality, such as post-editing effort, fails to capture the full nuance of what translators do

Software Engineering

https://arxiv.org/list/cs.SE/new
Skip to main content System maintenance August 4th and 5th Learn more × Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Software Engineering New submissions Cross-lists Replacements See recent