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.
Study stability of trading strategy under market perturbations.
Paper tackles RUL prediction with scarce data using indirect supervision.
Machine learning models trained on indirect data labels can fail on real-world examples.
Unified framework for learning with indirect supervision signals.
PLRM synthesizes labels from mismatched sources for better training sets.
We address the problem of gauging the influence exerted by a given country on the global trade market from the viewpoint of complex networks. In particular, we apply the PWP method for computing indirect influences on the world trade network.
Reinforcement learning (RL) algorithms have been successfully applied to a range of challenging sequential decision making and control tasks. In this paper, we classify RL into direct and indirect RL according to how they seek the optimal policy of the Markov decision process problem. The former solves the optimal poli…
Study shows cooperation can improve everyone's market efficiency.
Unified framework for estimating indirect effects in observational studies with unmeasured confounding.
New methods resolve conflicting treatment effect estimates in health tech assessments.
This study compares direct and indirect methods for estimating own funds in life insurance, finding indirect methods more effective under realistic asset-liability coupling.
Estimates causal effects using machine learning for binary treatment and mediator.
The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalization. In this paper we investigate the effects of FDI on trade from a network perspective, since FDI takes not only direct but also indirect channels from origin to destination countries because of f…
Weakly-supervised learning is a paradigm for alleviating the scarcity of labeled data by leveraging lower-quality but larger-scale supervision signals. While existing work mainly focuses on utilizing a certain type of weak supervision, we present a probabilistic framework, learning from indirect observations, for learn…
New method for learning indirectly through control variables.
Indirect attacks can fool graph classifiers even with poisoned neighbors.
Develops exact and invariant study-based decompositions for network meta-analysis.
Financial markets are exposed to systemic risk, the risk that a substantial fraction of the system ceases to function and collapses. Systemic risk can propagate through different mechanisms and channels of contagion. One important form of financial contagion arises from indirect interconnections between financial insti…
This paper learns prior models from indirect data efficiently.
AI detects 38% NFT trades likely manipulated, improving on indirect methods.
The study tackles indirect discrimination in insurance pricing models.
We study the ever more integrated and ever more unbalanced trade relationships between European countries. To better capture the complexity of economic networks, we propose two global measures that assess the trade integration and the trade imbalances of the European countries. These measures are the network (or indire…
Driven by the goal to enable sleep apnea monitoring and machine learning-based detection at home with small mobile devices, we investigate whether interpretation-based indirect knowledge transfer can be used to create classifiers with acceptable performance. Interpretation-based indirect knowledge transfer means that a…
This paper tackles structure learning in indirect observations of Gaussian and non-Gaussian random vectors.
Paper proposes an algorithm to learn DAGs with indirect dependencies.
New benchmark PVR tests neural network reasoning about indirection.
This paper studies communication efficiency in federated learning by optimizing the sum-rate-distortion function for indirect multiterminal source coding.
New method estimates corporate default probabilities using indirect data.
Study relaxes identification assumptions for natural direct effects in non-randomized settings.
In structured prediction problems where we have indirect supervision of the output, maximum marginal likelihood faces two computational obstacles: non-convexity of the objective and intractability of even a single gradient computation. In this paper, we bypass both obstacles for a class of what we call linear indirectl…
Researchers show how to secretly train models with hidden data, detect usage with high confidence.
Optimal reinsurance contracts designed for a continuum of risk types.
The objective optimization of medical imaging systems requires full characterization of all sources of randomness in the measured data, which includes the variability within the ensemble of objects to-be-imaged. This can be accomplished by establishing a stochastic object model (SOM) that describes the variability in t…
End-to-end algorithm for controlling bilinear systems with probabilistic noise.
This study measures price risk aversion using indirect utility functions in a lab experiment.
A fundamental problem in geostatistical modeling is to infer the heterogeneous geological field based on limited measurements and some prior spatial statistics. Semantic inpainting, a technique for image processing using deep generative models, has been recently applied for this purpose, demonstrating its effectiveness…
A simple banking network model is proposed which features multiple waves of bank defaults and is analytically solvable in the limiting case of an infinitely large homogeneous network. The model is a collection of nodes representing individual banks; associated with each node is a balance sheet consisting of assets and …
Paper develops models to forecast private equity fund cash flows.
We introduce the anti-profile Support Vector Machine (apSVM) as a novel algorithm to address the anomaly classification problem, an extension of anomaly detection where the goal is to distinguish data samples from a number of anomalous and heterogeneous classes based on their pattern of deviation from a normal stable c…
Extends causal inference to hidden mediators with proxies.
We propose a new method for assessing agents' influence in financial network structures, which takes into consideration the intensity of interactions. A distinctive feature of this approach is that it considers not only direct interactions of agents of the first level and indirect interactions of the second level, but …
Modeling supply chain disruptions from climate hazards with adaptive firms.
The main result of this paper is a negative answer to the question: are all transversal knot types transversally simple? An explicit infinite family of examples is given of closed 3-braids that define transversal knot types that are not transversally simple. The method of proof is topological and indirect.
We present Vision-based Navigation with Language-based Assistance (VNLA), a grounded vision-language task where an agent with visual perception is guided via language to find objects in photorealistic indoor environments. The task emulates a real-world scenario in that (a) the requester may not know how to navigate to …
Three configurations of two perpendicular disks in R^3 are examined, the first in which the disks share centers and the other two in which the disks touch at precisely one point. Volume, surface area and mean width calculations dominate the discussion. Integrated mean curvature also appears as an indirect way to comput…
Using techniques from the theories of convex polytopes, lattice paths, and indirect influences on directed manifolds, we construct continuous analogues for the binomial coefficients and the Catalan numbers. Our approach for constructing these analogues can be applied to a wide variety of combinatorial sequences. As an …
New method simplifies checking consistency of differentiable loss functions.
This paper studies the problem of {\em learning} the probability distribution of a discrete random variable using indirect and sequential samples. At each time step, we choose one of the possible functions, and observe the corresponding sample . The goal is to estimate the proba…