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.
Develops a new approach for algorithmic recourse in AI systems.
AReS framework provides interpretable recourses for entire populations.
New approach to meaningful and robust algorithmic recourse.
Recourse explanations can become invalid if collective actions change statistical data.
New framework shows algorithmic recourse can be harmful.
New probabilistic approaches offer recourse recommendations even when causal models are imperfect.
Study on maximizing submodular functions with limited updates, achieving tight bounds and poly-time algorithms.
Proposes a new method for algorithmic recourse in confounded settings.
COMRECGC finds common recourse for global counterfactual explanations in GNNs.
Improves algorithmic recourse to guide towards both acceptance and improvement.
Improves global counterfactual explanations for model recourse.
New fairness criteria for algorithmic recourse actions that consider causal relationships.
Proposes a new algorithm for accurate tree-based models with guaranteed recourse actions.
Proposes a new method to explain model predictions for consumer recourse.
The paper proposes a method to measure fairness through equality of effort using algorithmic recourse.
Paper proposes using pairwise feature comparisons to infer modification costs for user recourse.
Proposes sparse local and regional counterfactual rules for robust recourses.
The rise in machine learning-assisted decision-making has led to concerns about the fairness of the decisions and techniques to mitigate problems of discrimination. If a negative decision is made about an individual (denying a loan, rejecting an application for housing, and so on) justice dictates that we be able to as…
This work surveys algorithmic recourse, aiming to clarify definitions and solutions.
Machine learning models are increasingly used to automate decisions that affect humans - deciding who should receive a loan, a job interview, or a social service. In such applications, a person should have the ability to change the decision of a model. When a person is denied a loan by a credit score, for example, they…
As machine learning is increasingly used to inform consequential decision-making (e.g., pre-trial bail and loan approval), it becomes important to explain how the system arrived at its decision, and also suggest actions to achieve a favorable decision. Counterfactual explanations -- "how the world would have (had) to b…
Procedure verifies if machine learning models assign fixed predictions that preclude access.
New AR framework handles missing values for better recourse actions.
New findings show local attributions can't be both robust and provide recourse.
Machine learning based decision making systems are increasingly affecting humans. An individual can suffer an undesirable outcome under such decision making systems (e.g. denied credit) irrespective of whether the decision is fair or accurate. Individual recourse pertains to the problem of providing an actionable set o…
CounteRGAN generates realistic, actionable counterfactuals for machine learning models.
This work improves surrogate models for balancing accuracy and cost in multi-fidelity methods.
We give an entirely geometric proof, without recourse to cellular homology, of the fact that in the chain complex defined by a handle decomposition of a given manifold. Topological invariance of the resulting `handle homology' is a consequence of Cerf theory.
New framework for contesting algorithmic decisions, not just explaining them.
In a simplified setting, we show how to price invoice non-recourse factoring taking into account not only the credit worthiness of the debtor but also the assignor's one, together with the default correlation between the two. Indeed, the possible default of the assignor might impact the payoff by means of the bankruptc…
We develop and analyze stochastic optimization algorithms for problems in which the expected loss is strongly convex, and the optimum is (approximately) sparse. Previous approaches are able to exploit only one of these two structures, yielding an $\order(\pdim/T)$ convergence rate for strongly convex objectives in $\pd…
New approach to counterfactual reasoning avoids demographic interventions.
The usual development of the continuous-time random walk (CTRW) proceeds by assuming that the present is one of the jumping times. Under this restrictive assumption integral equations for the propagator and mean escape times have been derived. We generalize these results to the case when the present is an arbitrary tim…
We present the Integrated Size and Price Optimization Problem (ISPO) for a fashion discounter with many branches. Based on a two-stage stochastic programming model with recourse, we develop an exact algorithm and a production-compliant heuristic that produces small optimality gaps. In a field study we show that a distr…
Proposes an efficient method for ordered counterfactual explanations.
Define an arithmetic variety to be the quotient of a bounded symmetric domain by an arithmetic group. An arithmetic variety is algebraic, and the theorem in question states that when one applies an automorphism of the field of complex numbers to the coefficients of an arithmetic variety the resulting variety is again a…
We improve optimization for data with varying variance.
Stablecoins offer efficient settlement but externalize costs and risks.
Models for recommender systems show similar results in item availability.
This paper presents hyperbolic rank rigidity results for rank 1, nonpositively curved spaces. Let be a compact, rank 1 manifold with nonpositive sectional curvature and suppose that along every geodesic in there is a parallel vector field making curvature with the geodesic direction. We prove that ha…
We recently showed that the S&P500 stock market index is well described by Tsallis non-extensive statistics and nonlinear Fokker-Planck time evolution. We argued that these results should be applicable to a broad range of markets and exchanges where anomalous diffusion and `heavy' tails of the distribution are present.…
There are no known exact formulas for the valuation of a number of exotic options, and this is particularly true for options under discrete monitoring and for American style options. Therefore, one usually recourses to a Monte Carlo Simulation approach, amongst other numerical methods, to estimate the value of these op…
By mid 2004, the Basel Committee on Banking Supervision (BCBS) is epected to launch its final recommendations on minimum capital requirements in the banking industry. Although there is the intention to arrive at capital charges which concur with economic intuition, the risk weight formulas proposed by the committee wil…
We revisit the optimal investment and consumption model of Davis and Norman (1990) and Shreve and Soner (1994), following a shadow-price approach similar to that of Kallsen and Muhle-Karbe (2010). Making use of the completeness of the model without transaction costs, we reformulate and reduce the Hamilton-Jacobi-Bellma…
When training large machine learning models with many variables or parameters, a single machine is often inadequate since the model may be too large to fit in memory, while training can take a long time even with stochastic updates. A natural recourse is to turn to distributed cluster computing, in order to harness add…
Recommender systems often rely on models which are trained to maximize accuracy in predicting user preferences. When the systems are deployed, these models determine the availability of content and information to different users. The gap between these objectives gives rise to a potential for unintended consequences, co…
We study solutions of the Bogomolny equation on R^2\times S^1$ with prescribed singularities. We show that Nahm transform establishes a one-to-one correspondence between such solutions and solutions of the Hitchin equations on a punctured cylinder with the eigenvalues of the Higgs field growing at infinity in a particu…
On conformally compact manifolds of arbitrary signature, we use conformal geometry to identify a natural (and very general) class of canonical boundary problems. It turns out that these encompass and extend aspects of already known holographic bulk-boundary problems, the conformal scattering description of boundary con…