Applied Math · Mathematics & Statistics
Optimization & Control
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754 papers, from 31 August 2026 to 5 November 2026: 698 arXiv preprints and 56 OpenAlex records.
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Newest papers, page 37
Quantum Weighted Moving Average for Predicting Limit Order Book Trends
Can quantum computers be useful for forecasting multivariate financial time series?Efficiently Estimating Optimal Hyperparameter Scaling Laws through Power-Law Entropy Search
Optimal hyperparameter scaling laws describe how the best hyperparameters for large language model (LLM) training change with model and data scale, enabling practitioners to predict optimal…Independent Reinforcement Learning in Discounted Markov Games
In this work, we study radically uncoupled learning in discounted general-sum Markov games.Scalable Inversion of Contests with Correlated Performances, Including Softmax and Multinomial Probit
Multinomial probit choice probabilities over n alternatives are Gaussian orthant integrals, computed by simulation for thirty years, one expensive integral per alternative.Freemium Model for Information Provision
The paper explores a theoretical freemium model for the sale of information, drawing on mathematical tools used in the study of repeated zero-sum games and Bayesian persuasion.Bandits in Prod: Hyperparameter Optimization at Inference Time
Many production systems can assess a configuration only by using it on live requests and observing noisy feedback.Quantum Sparse Autoencoders for Q-Matrix Estimation in Cognitive Diagnosis
Q-matrices play a central role in cognitive diagnosis within educational data mining (EDM), specifying which latent skills each assessment item requires.Exact Risk-Complexity Laws for Projective Boundaries in Scenario Optimization and Distribution-Free Certification
Scenario optimization, conformal prediction, and related distribution-free certification methods use finite samples to construct decisions or prediction sets with violation-risk guarantees for fresh…Mechanism Design for Alignment and Control
We develop a framework for mechanism design with AI agents whose alignment (preferences) and capabilities (feasible actions and information) are unknown.LEAP: Likelihood Elicitation and Aggregation for LLM-based Probabilistic Forecasting
LLM-based forecasting systems have improved on real-world tasks such as financial markets and sports outcomes, largely through stronger search and tool use.Anytime-Valid Distribution Shift Detection via Predictive Rank Martingales
Many sequential distribution shift detectors update a growing reference set with incoming observations.Don't You Know, Pump it Up! Investigating Cryptocurrency Manipulation in Telegram-Driven Activity
Telegram plays a pivotal role in cryptocurrency communication and has been repeatedly associated with coordinated schemes, such as pump-and-dump manipulation.MERGED: Multimodal Entity Resolution via Generated Expert Reasoning Distillation
In product entity resolution, relationship definitions constantly evolve with business needs, yet adapting to each change traditionally requires slow, costly human annotation that is often noisy and…End-to-End Neural Shrinkage of Indefinite Pairwise Correlation Matrices for Small-Cap-Inclusive Portfolios
Small-cap-inclusive equity universes contain recently listed and intermittently traded securities, so enforcing a common look-back discards a substantial fraction of the available information.Computing Equilibria in Simulation-Based Insurance Markets with Discontinuous Demand
We study equilibrium computation in simulation-based games motivated by competition in natural-hazard insurance markets.Agentic Quantitative Trading: A Survey of Workflows, Systems, and Evaluation
Quantitative trading is moving from isolated predictive models toward agentic workflows that combine reasoning, tool use, memory, and feedback.Importance Sampling Enhanced with the COS Method for the Portfolio Risk Allocation
We introduce ISCOS, a cross-entropy importance-sampling calibration method for rare credit-portfolio losses.Projection-Free Bandit Online Optimization for Multi-Agent Systems with Dynamic Regret
This paper investigates distributed online optimization for multi-agent dynamical systems with constrained inputs and time-varying cost functions.From Metaheuristics to Exact Methods: A CP-SAT Approach for Multi-Objective Healthcare Workforce Scheduling
Healthcare workforce scheduling is an NP-hard optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, employee preferences and cost objectives.FaVOR: LLM-Based Agentic Framework for Factor Mining via Empirical Validation
Traditional finance relies on experts to hand-craft factors through a principled process grounded in economic rationale.