A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
New method reduces total cost constraints in CBwK to sqrt(T) with fairness application.
New algorithm reduces regret and constraint violation in constrained bandit problems.
Dynamic tracking error framework shows similar performance but varying volatility across different constraints.
New framework for online influencer selection considering cost constraints.
In this work we consider adversarial contextual bandits with risk constraints. At each round, nature prepares a context, a cost for each arm, and additionally a risk for each arm. The learner leverages the context to pull an arm and then receives the corresponding cost and risk associated with the pulled arm. In additi…
New method optimizes costly functions with unknown costs and budget constraints.
Proposes an angle-based framework for multicategory cost-sensitive classification.
We consider a budget-constrained bandit problem where each arm pull incurs a random cost, and yields a random reward in return. The objective is to maximize the total expected reward under a budget constraint on the total cost. The model is general in the sense that it allows correlated and potentially heavy-tailed cos…
We develop asymptotically optimal policies for the multi armed bandit (MAB), problem, under a cost constraint. This model is applicable in situations where each sample (or activation) from a population (bandit) incurs a known bandit dependent cost. Successive samples from each population are iid random variables with u…
This paper presents a simple method for a posteriori (historical) multi-variate multi-stage optimal trading under transaction costs and a diversification constraint. Starting from a given amount of money in some currency, we analyze the stage-wise optimal allocation over a time horizon with potential investments in mul…
CRPO solves challenging SRL problems with convergence guarantee.
A new stochastic method handles ensemble creation with cost constraints.
Germany's tax admin costs likely exceed 20% of total revenue, requiring system improvement.
Study minimizes Willmore energy with constraints on surface properties.
We discuss the role of integrated chance constraints (ICC) as quantitative risk constraints in asset and liability management (ALM) for pension funds. We define two types of ICC: the one period integrated chance constraint (OICC) and the multiperiod integrated chance constraint (MICC). As their names suggest, the OICC …
A new UCB policy improves reward-cost ratio estimation in budgeted MAB.
We propose to prune a random forest (RF) for resource-constrained prediction. We first construct a RF and then prune it to optimize expected feature cost & accuracy. We pose pruning RFs as a novel 0-1 integer program with linear constraints that encourages feature re-use. We establish total unimodularity of the constra…
Optimal withdrawal strategy for DC pension plans maximizes total withdrawals while managing risk.
Adaptive Bayesian Optimization for resource-constrained experiments with switching costs.
We consider the classical stochastic multi-armed bandit problem with a constraint that limits the total cost incurred by switching between actions to be no larger than a given switching budget. For this problem, we prove matching upper and lower bounds on the optimal (i.e., minimax) regret, and provide efficient rate-o…
Imagine a patient in critical condition. What and when should be measured to forecast detrimental events, especially under the budget constraints? We answer this question by deep reinforcement learning (RL) that jointly minimizes the measurement cost and maximizes predictive gain, by scheduling strategically-timed meas…
Schrödinger bridge solved with Weyl calculus for quadratic state cost.
Study shows maker-taker fees improve market efficiency but increase costs.
Study variational properties of curves in half-plane with area constraints.
Optimizes query routing to LLMs under cost and resource constraints.
Safe reinforcement learning tackles safety constraints with linear approximations.
Because of the prominent position of urban rail in reducing urban transport-related problems, such as congestion and air pollution, insights into the costs of possible new urban rail projects is very relevant for those involved with cost estimations, policy makers, cost-benefit analysts, and other target groups. Knowle…
A novel algorithm reduces communication costs in federated best arm identification.
We investigate the application of two heuristic methods, genetic algorithms and tabu/scatter search, to the optimisation of realistic portfolios. The model is based on the classical mean-variance approach, but enhanced with floor and ceiling constraints, cardinality constraints and nonlinear transaction costs which inc…
The notion of expense in Bayesian optimisation generally refers to the uniformly expensive cost of function evaluations over the whole search space. However, in some scenarios, the cost of evaluation for black-box objective functions is non-uniform since different inputs from search space may incur different costs for …
We study distributed estimation of a Gaussian mean under communication constraints in a decision theoretical framework. Minimax rates of convergence, which characterize the tradeoff between the communication costs and statistical accuracy, are established in both the univariate and multivariate settings. Communication-…
Pareto Testing optimizes model performance under multiple constraints.
The paper tackles sparse graph learning under Laplacian-related constraints, improving upon existing methods.
New system assigns vehicles to routes for cost and energy efficiency.
In some applications, acquiring covariates comes at a cost which is not negligible. For example in the medical domain, in order to classify whether a patient has diabetes or not, measuring glucose tolerance can be expensive. Assuming that the cost of each covariate, and the cost of misclassification can be specified by…
Previous studies into the budget constraint of portfolio optimization problems based on statistical mechanical informatics have not considered that the purchase cost per unit of each asset is distinct. Moreover, the fact that the optimal investment allocation differs depending on the size of investable funds has also b…
Study optimality conditions for interval-valued optimization problems on Riemannian manifolds.
A new method for optimal transport using neural ODEs that preserves marginal constraints.
New methods reduce computational cost for Gaussian Markov Random Fields with sparse constraints.
Solves portfolio optimization with costs using numerical methods.
Optimal wind farm placement using quantile constraints for better power output.
Proves well-posedness for Einstein equations with totally geodesic timelike boundary condition.
In order to scale transaction rates for deployment across the global web, many cryptocurrencies have deployed so-called "Layer-2" networks of private payment channels. An idealized payment network behaves like a Credit Network, a model for transactions across a network of bilateral trust relationships. Credit Networks …
Based on a study of the coupling by reflection of diffusion processes, a new monotonicity in time of a time-dependent transportation cost between heat distribution is shown under Bakry-Emery's curvature-dimension condition on a Riemannian manifold. The cost function comes from the total variation between heat distribut…
A decentralized algorithm minimizes cumulative regret in stochastic linear bandits with safety constraints.
We consider stochastic strongly convex optimization with a complex inequality constraint. This complex inequality constraint may lead to computationally expensive projections in algorithmic iterations of the stochastic gradient descent~(SGD) methods. To reduce the computation costs pertaining to the projections, we pro…
Based on a point of view that solvency and security are first, this paper considers regular-singular stochastic optimal control problem of a large insurance company facing positive transaction cost asked by reinsurer under solvency constraint. The company controls proportional reinsurance and dividend pay-out policy to…
Paper improves COCO problem, reducing constraint violation at the cost of slightly more regret.