We study agents communicating over an underlying network by exchanging messages, in order to optimize their individual regret in a common nonstochastic multi-armed bandit problem. We derive regret minimization algorithms that guarantee for each agent an individual expected regret of $\widetilde{O}\left(\sqrt{\left(…
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48 results for “individual rights”
Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc for matching restaurants to customers. In these online to offline service problems, individuals who are respo…
New framework for contesting algorithmic decisions, not just explaining them.
problem Helping individuals review and correct erroneous algorithmic decisions.
method Operationalized contestability as a natural complement to explainable AI (XAI), identifying three types of evidence for reversal.
result Existing EU legislation already grants individuals legal rights to contest algorithmic decisions.
Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibrationstat.ML
Proposes a compensation mechanism for improving individual forecast confidence.
problem Difficult to assess the quality of individual probabilistic forecasts and their utilities.
method Compensation mechanism based on fair bets and online learning.
result The proposed mechanism cannot be exploited and ensures forecasted utility matches actual utility.
Linear filtration helps delete training data from models.
problem Deleting training data from models when individuals request it.
method Linear filtration as a computationally efficient sanitization method.
result Demonstrates benefits in an adversarial setting over naive deletion schemes.
The paper develops deep learning models for personalized treatment rules in survival analysis.
problem Deriving optimal treatment rules for bivariate survival outcomes in randomized trials.
method Adaptive prediction-powered learning using deep neural networks and stochastic policies.
result Maximizes joint survival probability beyond fixed time points .
This article reviews entity resolution methods and their applications.
problem Integrating information from multiple sources to clean and accurately link records.
method Clustering, semi- and fully supervised methods, canonicalization.
result Modern probabilistic record linkage has been foundational.
A pair of simple closed geodesics on a closed and oriented hyperbolic surface of genus is called a filling pair if the complementary components of in are simply connected. The length of a filling pair is defined to be the sum of their individual lengths. In \cite{Aou}, Aougab-Huang con…
We summarize the potential impact that the European Union's new General Data Protection Regulation will have on the routine use of machine learning algorithms. Slated to take effect as law across the EU in 2018, it will restrict automated individual decision-making (that is, algorithms that make decisions based on user…
Intense recent discussions have focused on how to provide individuals with control over when their data can and cannot be used --- the EU's Right To Be Forgotten regulation is an example of this effort. In this paper we initiate a framework studying what to do when it is no longer permissible to deploy models derivativ…
New method estimates optimal personalized treatment rules from mixed data sources.
problem Combining RCT and observational data for personalized treatment rules.
method Doubly robust estimator for value function, maximizing within pre-specified ITR class.
result Consistent and asymptotically normal optimal value estimator with rate of convergence.
It seems that what has been said by now about market and competitiveness do not fit perfectly with competences of getting the best of profit. Sometimes, the classical methods of fundamentals of management do not apply to individual companies that face irregular accommodation on the market. It is high time to replace th…
Paper proposes a new metric to evaluate survival models, especially for censored data.
problem Challenges in evaluating survival prediction models due to censored data.
method Developed a novel approach to estimate Mean Absolute Error (MAE) for survival datasets with censored data.
result The proposed MAE metric using pseudo-observations accurately ranks model performance and closely matches true MAE.
In the context of fake news, bias, and propaganda, we study two important but relatively under-explored problems: (i) trustworthiness estimation (on a 3-point scale) and (ii) political ideology detection (left/right bias on a 7-point scale) of entire news outlets, as opposed to evaluating individual articles. In partic…
Analyzes national real estate investment risks and returns.
problem Investors and home buyers face increasing costs and risks.
method Examines economic vulnerabilities and traditional market analysis.
result Ensures positive returns and fair prices for real estate investments.
We consider settings in which the right notion of fairness is not captured by simple mathematical definitions (such as equality of error rates across groups), but might be more complex and nuanced and thus require elicitation from individual or collective stakeholders. We introduce a framework in which pairs of individ…
New method achieves nearly horizon-free offline reinforcement learning for tabular and linear MDPs.
problem Achieving efficient reinforcement learning without knowing the horizon.
method Simple recursion-based method to bound total variance in offline scenarios.
result Nearly horizon-free sample complexity bounds for offline policy evaluation and optimization.
Enhances survival analysis by separating population behavior from individual dynamics.
problem Improving the training and inference of survival analysis models for sparsely occurring events.
method Decouples survival analysis into an aggregated baseline hazard and independent survival scores.
result Achieves competitive performance and robust results without fine-tuning.
Bayesian inference forgetting framework removes influence of single data points.
problem Enforcement of the right to be forgotten in machine learning causes high costs for companies.
method Develops forgetting algorithms for variational and Markov chain Monte Carlo in Bayesian inference.
result Proves removal of influence of single datums on learned models with guaranteed generalizability.
Some remarks on twin groupsmath.GR
Study on twin groups with algorithm and properties.
problem Properties and algorithm of twin groups.
method Algorithm for equivalence under Markov moves, properties of R-infinity and co-Hopfian.
result Twin groups have -property and are not co-Hopfian for .
Designing AI market for content creation
problem Balancing technological progress and individual incentives for content creation
method Dynamic Stackelberg game model
result Inducing greater reliance on AI-assisted creation
Models for predicting the risk of cardiovascular events based on individual patient characteristics are important tools for managing patient care. Most current and commonly used risk prediction models have been built from carefully selected epidemiological cohorts. However, the homogeneity and limited size of such coho…
We proposed a probabilistic approach to joint modeling of participants' reliability and humans' regularity in crowdsourced affective studies. Reliability measures how likely a subject will respond to a question seriously; and regularity measures how often a human will agree with other seriously-entered responses coming…
Causal forests use honesty to reduce overfitting, but it can also reduce accuracy, especially with large datasets.
problem Causal forests' honesty can reduce accuracy of individual treatment effects.
method Using honest estimation to divide data into two samples, one for subgroup definition and another for effect estimation.
result Honest estimation can reduce accuracy by requiring 27% more data to match performance of non-honest models.
Linear ODEs are solved by geodesics in hyperbolic geometry.
problem Solving real linear second order ODEs.
method Defined a Riemannian hyperbolic geometry and showed that solutions to ODEs correspond to geodesics in this geometry.
result Local solutions to ODEs correspond to geodesics in a specific hyperbolic geometry.
Local surrogate models, to approximate the local decision boundary of a black-box classifier, constitute one approach to generate explanations for the rationale behind an individual prediction made by the back-box. This paper highlights the importance of defining the right locality, the neighborhood on which a local su…
Efficient oblique RSF method improves prediction and interpretability.
problem Limited computational efficiency and difficulty in interpreting oblique RSF ensembles.
method Newton-Raphson scoring for computational efficiency and negation importance for variable importance estimation.
result The method reduces computational overhead by 450 times and improves prediction accuracy.
The Internet is known to have had a powerful impact on on-line retailer strategies in markets characterised by long-tail distribution of sales. Such retailers can exploit the long tail of the market, since they are effectively without physical limit on the number of choices on offer. Here we examine two extensions of t…
We study the performance of stochastic gradient descent (SGD) on smooth and strongly-convex finite-sum optimization problems. In contrast to the majority of existing theoretical works, which assume that individual functions are sampled with replacement, we focus here on popular but poorly-understood heuristics, which i…
The paper revisits the -Yamabe problem and proves the existence of a conformal metric with constant -scalar curvature.
problem Finding a conformal metric with constant -scalar curvature on closed manifolds.
method Analyzing the -Yamabe constant and proving its achievability under certain conditions.
result The -Yamabe constant is achieved by a conformal metric, solving the -Yamabe problem on manifolds with positive Yamabe constant.
The paper proves foliations of solutions to the minimal surface equation in exterior domains.
problem Existence and properties of foliations by solutions to the exterior Dirichlet problem for minimal surfaces.
method Analyzes a 1-parameter family of solutions to the minimal surface equation in exterior domains with specific boundary conditions.
result Foliation of the open subset in R^(n+1) by graphs of solutions, with bounds and asymptotic behavior.
The paper examines differentiability of horizons along their generators in Lorentz manifolds.
problem Analyzing the differentiability of horizons along their generators in Lorentz manifolds.
method Using a result that every mathematical horizon locally coincides with a Cauchy horizon, the paper proves conditions for differentiability of horizons.
result Horizons are either continuously differentiable or have differentiability jumping points.
New study finds targeting based on treatment effects outperforms risk-based targeting in social interventions.
problem Lack of accurate treatment effect estimates for machine learning-based targeting in social domains.
method Empirical assessment of targeting strategies using data from 5 real-world RCTs in various domains.
result Treatment effect-based targeting outperforms risk-based targeting, even with biased estimates.
Uniqueness of quasi-roots explored in right-angled Artin groups.
problem Uniqueness of quasi-roots in right-angled Artin groups.
method Introducing quasi-roots and studying their uniqueness.
result Uniqueness of quasi-roots established in right-angled Artin groups.
Study bounds financial path expectations using martingale distributions.
problem Bounding path-dependent financial expectations over martingale distributions.
method Relaxed martingale optimal transport problem, approximated via linear programming.
result Empirical relaxation can be approximated within O(n^(-1/2)) error.
Study benchmarks 19 survival models on 34 datasets, finding Cox model still best.
problem Quantitative comparison of survival models on low-dimensional data.
method Comprehensive benchmarking of 19 models on 34 datasets, tuning and evaluating using 6 metrics.
result Cox Proportional Hazards model remains best overall for low-dimensional, right-censored data.
A new matrix concentration inequality for random products of matrices.
problem Understanding the behavior of random matrix products under bounded independent positive semidefinite matrices.
method Developed a non-asymptotic concentration inequality for the product of matrices.
result The inequality provides a bound on the deviation of the matrix product from its expected value.
Our paper improves uplift model evaluation on randomized controlled trials (RCT) data.
problem Variance in uplift evaluation metrics makes their signals arbitrary and unreliable.
method Theoretical analysis and statistical adjustment of the outcome to reduce variance.
result Variance reduction methods improve uplift evaluation metrics on RCT data.
Extracts causal brain dynamics across multiple scales.
problem Statistical associations do not reflect causal mechanisms in brain dynamics.
method Multiscale causal backbone (MCB) extraction using advanced causal structure learning.
result Sparse MCBs reveal distinct causal roles at different brain frequency bands.
K-theory of affine actionsmath.DG
For a Lie group and a vector bundle we study those actions of the Lie group on for which the action map is a morphism of vector bundles, and call those \emph{affine actions}. We prove that the category of such actions over a fixed …
Deep neural networks classify T2D from retinal images with high accuracy.
problem Detecting early-stage Type 2 Diabetes from retinal images.
method Employed deep neural networks and multi-target learning to differentiate T2D from healthy individuals.
result Classification performance improved to AUC = 0.758 [0.003] using images from both eyes.
Who Increases Emergency Department Use? New Insights from the Oregon Health Insurance Experimentecon.EM
New insights show Medicaid impacts on ED use vary widely, with some groups seeing significant increases.
problem Understanding the varied impacts of Medicaid on emergency department use.
method Causal machine learning methods to identify heterogeneous impacts.
result Meaningful heterogeneity in the effect of Medicaid on ED use, with a small group driving the overall effect.
Detects right-veering properties in open books using combinatorial methods.
problem Determining the right-veering property of contact structures.
method Combinatorial approach to detect left-veering arcs in open books.
result Existence of an algorithm to detect right-veering for compact surfaces.
Surveying connections between graph combinatorics and algebraic right-angled Artin groups.
problem Understanding the relationship between graph structures and algebraic properties of right-angled Artin groups.
method Analyzing the defining and extension graphs of right-angled Artin groups.
result Discovers connections to geometric group theory and complexity theory.
We introduce a notion of "quasi-right-veering" for closed braids, which plays an analogous role to "right-veering" for open books. We show that a transverse link in a contact 3-manifold is non-loose if and only if every braid representative of with respect to every open book decomposition that supports …
The study characterizes spacetime and modified gravity models using projective curvature tensor.
problem Characterizing spacetime and modified gravity models with projective curvature tensor.
method Analyzing $f\left(R,G
ight)$, $f\left(R,T
ight)$, and $f\left(R,L_{m}
ight)$-gravity models.
result Projectively flat perfect fluid spacetimes represent dark energy era and are locally isometric to Minkowski or de-Sitter spacetimes.
The social media revolution has changed the way that brands interact with consumers. Instead of spending their advertising budget on interstate billboards, more and more companies are choosing to partner with so-called Internet "influencers" --- individuals who have gained a loyal following on online platforms for the …
In this paper we study the right-angled Coxeter groups that acts geometrically on the Salvetti complex of a certain right-angled Artin group, which we refer to as Croke-Kleiner spaces. We prove that any right-angled Coxeter group that acts geometrically on the Croke-Kleiner spaces acts with angles between reflect…