Paper tackles inconsistent CATE estimation across group assignments.
problem Inconsistent learning behavior for the same instance across different group assignments.
method CLAGA method to eliminate inconsistency.
result Significant performance improvements with CLAGA method.
Solves inconsistent estimation for Neyman-Scott problems.
problem Inconsistent estimation for Neyman-Scott problems.
method RKL estimator, invariant to representation, consistent over any non-degenerate prior.
result General-purpose Bayes estimator for Neyman-Scott that is consistent and invariant.
V-matrix method fails to consistently estimate conditional probabilities.
problem Inconsistent solutions in V-matrix method for conditional probability estimation.
method Construct constrained quadratic programming problems with inconsistent inequality constraints.
result V-matrix method may not always have a consistent solution for conditional probability estimation.
We formalize nesting in probabilistic queries and correct inconsistent estimates.
problem Inconsistent estimates in probabilistic query nesting.
method Formalized nesting, introduced online nested Monte Carlo estimator, proved correctness and asymptotic variance.
result Corrected inconsistent estimates through new estimator and conditions.
In this paper we propose a method for a quantitative estimation of the decision maker's knowledge in the context of the Analytic Hierarchy Process (AHP) in cases, where the judgment matrix is inconsistent. We show that the matrix of deviation from the transitivity condition corresponds to the rate matrix for transactio…
TWINs tackles PDA by weighting inconsistency between two networks.
problem PDA where target classes are a subset of source classes.
method Two Weighted Inconsistency-reduced Networks (TWINs) with two classification networks and weighted classification loss.
result TWINs outperforms other methods in PDA datasets.
Paper analyzes venture capital exit decisions under inconsistent preferences.
problem Time-inconsistent preferences in venture capital exit timing.
method Modeling four types of venture capitalists with varying levels of inconsistency.
result Time-inconsistent venture capitalists exit earlier than consistent ones.
The paper shows cross-validation fails in learning Gaussian graphical model structures.
problem Cross-validation's failure in learning Gaussian graphical model structures.
method Finite-sample bounds on misidentification probability of Lasso estimator.
result Cross-validation is inconsistent for learning Gaussian graphical model structures.
Paper solves time-inconsistent control problems with BSDEs.
problem Time-inconsistent stochastic control in continuous time.
method Probabilistic representation via BSDEs.
result Equilibrium value function resolved for inconsistent cases.
New framework quantifies learning guarantees for inconsistent convex surrogates.
problem Analyzing consistency properties of machine learning methods with inconsistent convex surrogates.
method Extending the framework of Osokin et al. (2017) to inconsistent surrogates, introducing a new lower bound on the calibration function.
result Shows how learning with inconsistent surrogates can have guarantees on sample complexity and optimization difficulty.
The paper shows failure of smooth pasting principle in time-inconsistent stopping problems.
problem Time-inconsistent stopping problems with non-constant time preference rates.
method Analysis of the smooth pasting principle within the intra-personal game theoretic framework.
result The smooth pasting principle fails under time-inconsistency and does not guarantee equilibrium solutions.
New theory extends LQ control to non-exponential discount scenarios.
problem Time-inconsistent deterministic LQ control problems.
method Extended equivalent relationship to non-exponential discount functions, studied Riccati equation solvability.
result Existence and uniqueness of linear equilibrium for time-inconsistent LQ problem.
DAGnosis uses DAGs to identify and localize data inconsistencies.
problem Handling data inconsistencies in machine learning models at deployment time.
method Directed acyclic graphs (DAGs) to encode feature probability distribution and independencies.
result Localization of inconsistencies and insights into their causes.
The paper proves well-posedness of nonlocal PDEs related to stochastic control problems.
problem Characterizing equilibrium strategies and value functions for time-inconsistent stochastic control problems.
method Method of continuity and Banach's fixed point arguments, with Schauder prior estimates.
result Global well-posedness of nonlocal fully nonlinear PDEs with sharp a-priori estimates.
TD learning reduces prediction error in Markov chain problems.
problem Estimating value functions in Markov chains with temporal inconsistency.
method Temporal difference learning minimizes temporal inconsistency between successive estimates.
result TD learning can significantly reduce mean-squared error in value estimates.
Study solves HJB equations for time-inconsistent control problems.
problem Time-inconsistent deterministic linear quadratic control problems.
method Characterized solutions using Riccati equations with integral terms, proving uniqueness.
result Uniqueness of solutions to equilibrium HJB equations proved.
Study time-inconsistent consumption-investment in incomplete markets with general discount functions.
problem Time-inconsistent consumption-investment problems in incomplete markets.
method Coupled forward-backward stochastic differential equation approach.
result Uniqueness of open-loop equilibrium pair proved.
This paper tackles objective inconsistency in federated optimization with heterogeneous clients.
problem Objective inconsistency due to heterogeneity in clients' datasets and computation speeds.
method General framework for analyzing federated heterogeneous optimization algorithms, including FedAvg and FedProx, and proposing FedNova.
result FedNova eliminates objective inconsistency while preserving fast error convergence.
Study time-inconsistent portfolio optimization for competitive agents with relative performance criteria.
problem Time-inconsistent mean field and n-agent games under relative performance criteria.
method Construct open-loop equilibrium strategies for n-agent games and mean field games.
result Explicit solutions for n-agent games and mean field games, unique in a special class of equilibria.
Develops a reinforcement learning algorithm for learning deterministic equilibrium policies in time-inconsistent control problems.
problem Learning equilibrium policies in time-inconsistent control problems.
method Continuous-time model-free reinforcement learning algorithm using deterministic policy gradient approach.
result Learned equilibrium policies in general time-inconsistent control problems.
Natural experiment dataset reveals inconsistent treatment effect estimators.
problem Inconsistent results from over 20 estimators on a new dataset.
method Created a benchmark to evaluate estimator accuracy, derived variance formula, introduced new estimator.
result Doubly robust estimators outperform others by orders of magnitude.
Recurrent models can produce infinite sequences, causing bias; new methods prevent this.
problem Inconsistency in decoding infinite-length sequences from recurrent language models.
method Defined and proved inconsistency of common decoding algorithms; proposed remedies.
result Proposed methods prevent inconsistency in practice.
New method resolves inconsistency in learning directed acyclic graphs using penalized likelihood.
problem Inconsistency of ℓ1-penalized likelihood in learning directed acyclic graphs. method Developed a hybrid differentiable structure learning method based on ℓ0-penalized likelihood with hard acyclicity constraint. result Demonstrated and explained why ℓ1-penalized likelihood is fundamentally inconsistent in identifying true structure up to Markov equivalence classes. Corrects GCV for inconsistent risk estimation in finite ensembles of penalized estimators.
problem Inconsistent risk estimation of GCV for finite ensembles of penalized estimators.
method Identifies a correction involving an additional scalar correction based on degrees of freedom adjusted training errors from each ensemble component.
result CGCV maintains computational advantages of GCV and is model-free uniformly consistent for ridge regression.
Paper solves a complex portfolio selection problem with time-inconsistent preferences.
problem Time-inconsistent preferences in portfolio selection.
method Unified framework with minimal assumptions, proving existence and uniqueness of solution.
result Existence and uniqueness of square-integrable solution for the integral equation.
Kernel interpolation is inconsistent for norms with smoothness above a constant.
problem Inconsistency of kernel interpolation in reproducing kernel Hilbert spaces.
method Lower bounds for generalization error in Sobolev norms.
result Kernel interpolation is always inconsistent for norms with smoothness above a constant.
Study time-inconsistent control problems with model uncertainty, solving portfolio selection.
problem Time-inconsistent Markovian control problems under model uncertainty.
method Combining sub-game perfect strategies with adaptive robust stochastic methods.
result Solved numerically the mean-variance portfolio selection problem.
Aux-Net model handles dynamic systems with inconsistent inputs.
problem Inconsistent or unreliable input data in real-world scenarios.
method Aux-Net uses a weighted ensemble of classifiers and online gradient descent.
result Aux-Net provides scalable and agile online learning for dynamic systems.
Proposes a robust equilibrium strategy for mean-variance portfolio selection.
problem Time-inconsistency in mean-variance portfolio selection.
method Introduces a novel definition of robust equilibrium strategy and solves the corresponding PDE system.
result A classical solution to the PDE system implies a robust equilibrium strategy.
The study evaluates saliency metrics for image classifier outputs, finding inconsistencies and unreliability.
problem Inconsistencies and unreliability in saliency metrics for evaluating pixel relevance.
method Investigated existing saliency metrics, calculated and compared their consistency, and applied psychometric testing methods.
result Saliency metrics can be statistically unreliable and inconsistent, affecting comparative rankings.
New method improves cross-validation for sparse reduced rank regression models.
problem Inconsistent parameter selection in cross-validation for high-dimensional data.
method Proposes cross-validation of projection-selection patterns to avoid inconsistency issues.
result Develops new scale-free information criteria for minimax optimal error rate.
Paper addresses regression with permuted data, proposing robust methods.
problem Regression with permuted data, where response and predictor variables are mismatched.
method Proposes robust regression methods to handle inconsistent least squares estimators.
result Robust regression methods can recover permutation and estimate regression parameters.
Time inconsistency leads to intra-personal conflict and reconciliation strategies.
problem Time inconsistency in dynamic choice problems.
method Rigorous treatment of intra-personal equilibrium in continuous-time settings.
result A new approach to understanding and reconciling intra-personal conflicts.
Proposes a new multi-view graph learning framework to model consistency and inconsistency.
problem Graph learning methods often neglect inconsistency across multiple views, making them vulnerable to noisy datasets.
method Proposes a unified objective function to simultaneously model consistency and inconsistency, iteratively learning consistent and unified graphs.
result Demonstrates robustness and efficiency of the proposed approach on twelve multi-view datasets.
Separable losses are inconsistent for structured prediction models.
problem Inconsistency of separable losses in structured prediction models.
method Analysis of separable negative log-likelihood losses for structured prediction.
result Separable losses are not Bayes consistent and may not predict the most probable structure.
Paper proves existence and uniqueness of solutions to nonlocal systems, generalizing stochastic game theory.
problem Time inconsistency in stochastic differential games.
method Proves existence and uniqueness of solutions to nonlocal fully-nonlinear parabolic systems.
result Generalizes stochastic game theory to include time-inconsistent preferences.
The paper tackles inconsistency in removal-based explanations and proposes methods to reduce it.
problem Inconsistency in removal-based explanations.
method Established the Impossible Trinity Theorem and proposed two novel algorithms to minimize interpretation error.
result The proposed methods achieve a substantial reduction in interpretation error, up to 31.8 times lower.
Introduces strong equilibrium for time-inconsistent stopping problems in continuous time.
problem Time-inconsistent stopping problems in continuous time.
method Introduces strong equilibrium, compares with existing mild and weak equilibria, and provides an iteration method to construct optimal mild equilibria.
result Optimal mild equilibria are always strong equilibria under certain conditions.
New research shows the bandwagon effect doesn't cause bias but can make estimators inconsistent.
problem The bandwagon effect in recommender systems makes estimators inconsistent.
method Theoretical analysis investigating conditions for inconsistency and proposing mitigation approaches.
result The bandwagon effect can make estimators inconsistent, not just cause bias.
We consider a general time-inconsistent stochastic linear-quadratic differential game. The time-inconsistency arises from the presence of quadratic terms of the expected state as well as state-dependent term in the objective functionals. We define an equilibrium strategy, which is different from the classical one, and …
The paper solves TIC LQ control problems using stochastic differential games.
problem Time-inconsistent linear-quadratic stochastic control problems.
method Stochastic differential games, spike variation approach.
result Achieves Nash equilibrium for TIC problems, demonstrating impact of ambiguity aversion.
The paper analyzes time-inconsistent strategies in financial markets with rough volatility.
problem Time-inconsistency in financial markets with rough volatility.
method Functional Itô calculus and game-theoretic framework to solve path-dependent Hamilton-Jacobi-Bellman equations.
result Explicit solutions to MVP problems under rough volatility, showing performance benefits.
New method detects inconsistencies in AHP matrices using triadic preference reversals.
problem Challenges in assessing consistency in AHP pairwise comparison matrices.
method Triadic preference reversals to detect inconsistencies between pairs of elements.
result 97% accuracy in detecting inconsistencies, significantly surpassing traditional methods.
Detects corruption in agentic models during execution.
problem Inconsistent context, retrieval errors, or adversarial inputs corrupt intermediate steps of reasoning chains.
method Analyzes token graphs induced by attention and computes spectral statistics to emit accept/reject signals.
result A single threshold on the high frequency energy ratio optimally detects context inconsistency in agentic models.
The paper analyzes optimal dividend and capital injection strategies under time-inconsistent preferences.
problem Optimal dividend and capital injection strategies under time-inconsistent preferences.
method Diffusion risk model with general discount functions, weak equilibrium definition, HJB equation system.
result Explicit solutions and threshold types of optimal strategies derived under different discount functions.
Paper addresses inconsistency between offline and online LTR performance.
problem Inconsistency between offline and online LTR performance in E-commerce.
method Proposes an evaluator-generator framework to maximize evaluator score using reinforcement learning.
result Significant improvement in Conversion Rate (CR) over existing models.
Investigates time-inconsistent portfolio selection under MMV preferences.
problem Time-inconsistent optimal strategies for MMV preferences.
method Nash equilibrium controls for MMV and MV preferences, solving FBSDE and HJB equations.
result MMV optimal strategies lead to higher investment amounts than MV strategies, narrowing over time.
Researchers improve Gaussian processes to model inconsistent preferences.
problem Model inconsistent preferences and clusters of comparable items.
method Generalized Gaussian processes with spectral decomposition and universal RKHS.
result Competitive with state-of-the-art methods on simulated and real-world data.