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.
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.
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.
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.
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 task of unsupervised domain adaptation is proposed to transfer the knowledge of a label-rich domain (source domain) to a label-scarce domain (target domain). Matching feature distributions between different domains is a widely applied method for the aforementioned task. However, the method does not perform well whe…
SCARLET-NAS improves neural architecture search by stabilizing feature inconsistencies.
problem Difficulty in ranking subnetworks due to feature inconsistency in skip connections.
method Introduced an equivariant learnable stabilizer to homogenize feature disparities.
result SCARLET-A achieves 76.9% top-1 accuracy on ImageNet.
Note that a newer expanded version of this paper is now available at: arXiv:1802.03888 It is critical in many applications to understand what features are important for a model, and why individual predictions were made. For tree ensemble methods these questions are usually answered by attributing importance values to i…
Proposes a method to improve multi-output Gaussian process for transfer learning.
problem Negative transfer and domain inconsistency in multi-output Gaussian process.
method Regularized MGP with convolution process and domain adaptation.
result Outperforms state-of-the-art benchmarks in simulation and real-world studies.
Semantic segmentation is an established while rapidly evolving field in medical imaging. In this paper we focus on the segmentation of brain Magnetic Resonance Images (MRI) into cerebral structures using convolutional neural networks (CNN). CNNs achieve good performance by finding effective high dimensional image featu…
Proposes CI-GMVC to improve graph-based multi-view clustering performance.
problem Inconsistency in multi-view data affects clustering performance.
method Integrates consistent and inconsistent parts of multiple views using a unified matrix.
result Demonstrates improved clustering performance on real-world datasets.
DNN2LR bridges DNN power and LR interpretability.
problem Combining DNN power and LR interpretability for real-world tabular data.
method Automatic feature crossing method based on DNN interpretation inconsistencies.
result DNN2LR outperforms complex DNN models and feature crossing methods.
Optimizes dividend payments to balance risk and reward.
problem Maximizing mean-variance of accumulated discounted dividends up to ruin.
method Develops a time-consistent equilibrium strategy using a verification lemma.
result Equilibrium strategy is a barrier strategy for low risk aversion.
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.
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 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.
Large-scale classification of data where classes are structurally organized in a hierarchy is an important area of research. Top-down approaches that exploit the hierarchy during the learning and prediction phase are efficient for large scale hierarchical classification. However, accuracy of top-down approaches is poor…
We study consistency properties of machine learning methods based on minimizing convex surrogates. We extend the recent framework of Osokin et al. (2017) for the quantitative analysis of consistency properties to the case of inconsistent surrogates. Our key technical contribution consists in a new lower bound on the ca…
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.
BERT improves Chinese word segmentation performance.
problem Chinese word segmentation task.
method Applying BERT to CWS task using benchmark datasets.
result BERT can improve performance even with inconsistent labels.
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.
This paper considers a time-inconsistent stopping problem in which the inconsistency arises from non-constant time preference rates. We show that the smooth pasting principle, the main approach that has been used to construct explicit solutions for conventional time-consistent optimal stopping problems, may fail under …
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.
A new method integrates Fourier basis expansion and mapping for improved time series forecasting.
problem Inconsistent starting cycles and series length issues in Fourier-based methods.
method Fourier Basis Mapping (FBM) method that integrates time-frequency features through Fourier basis expansion and mapping.
result FBM addresses inconsistencies and preserves temporal characteristics, achieving SOTA performance.
Feature selection methods are usually evaluated by wrapping specific classifiers and datasets in the evaluation process, resulting very often in unfair comparisons between methods. In this work, we develop a theoretical framework that allows obtaining the true feature ordering of two-dimensional sequential forward feat…
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.
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.
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.
We solve a continuous-time game-theoretic problem for Kihlstrom-Mirman preferences.
problem Dynamic inconsistency in preferences due to multiattribute utility theory.
method Formalized an equilibrium control theory for continuous-time Markov processes.
result Equilibrium strategy and value function as solution to extended HJB system.
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.
Proposes a neural network method to improve consistencies in high dimensional data analysis.
problem Inconsistencies among dimensionality reduction, clustering, and visualization tasks in high dimensional data analysis.
method Consistent Representation Learning (CRL) neural network that performs NLDR transformations to satisfy LGP constraints.
result Improves consistencies in data interpretation through end-to-end task execution.
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.
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.
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.
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.
SJS model predicts label shifts in multinomial datasets.
problem Predicting label shifts in multinomial datasets.
method Sparse joint shift model for dataset shift.
result Valid predictions and class prior probabilities estimates.
The paper formalizes feature attribution to address inconsistent definitions and evaluate methods.
problem Inconsistent definitions of feature relevance in feature attribution.
method Formalization based on relaxed functional dependence, extended to instance-wise setting.
result State-of-the-art methods often fail to verify necessary properties for candidate selection.
Interpreting predictions from tree ensemble methods such as gradient boosting machines and random forests is important, yet feature attribution for trees is often heuristic and not individualized for each prediction. Here we show that popular feature attribution methods are inconsistent, meaning they can lower a featur…
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.
FSL-Net detects and localizes feature shifts in large, high-dimensional datasets.
problem Feature shifts between data sources lead to erroneous features in various applications.
method FSL-Net is a neural network trained on multiple datasets to localize feature shifts.
result FSL-Net accurately localizes feature shifts from unseen datasets without re-training.
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.