Turnpike results for risk tolerance in incomplete markets under time-monotone criteria.
problem Turnpike results for risk tolerance in incomplete markets under time-monotone criteria.
method Time-monotone forward performance criteria, analysis of limits, dependence on measure support.
result Temporal and spatial limits do not coincide and depend on measure support.
We consider the problem of optimal portfolio selection under forward investment performance criteria in an incomplete market. The dynamics of the prices of the traded assets depend on a pair of stochastic factors, namely, a slow factor (e.g. a macroeconomic indicator) and a fast factor (e.g. stochastic volatility). We …
Study optimal strategies under uncertain market parameters and borrowing costs.
problem Optimal portfolio-consumption strategies in uncertain markets.
method Robust utility maximization framework with explicit solutions.
result Impacts of uncertain parameters, constraints, and borrowing costs quantified.
Study robust utility maximization with uncertain endowments.
problem Optimal strategy under nondominated model uncertainty.
method General representation result, Choquet's capacitability theorem, medial limits.
result Existence of optimal strategy and dual representation for optimal utility.
Study forward investment performance in semimartingale markets with stochastic factors.
problem Investigate forward investment performance in incomplete semimartingale markets with power risk preferences and stochastic integrated factors.
method Develop necessary and sufficient conditions for FIPP existence, use integral representations, and solve ill-posed HJB equations.
result Explicit constructions for time-monotone FIPPs in semimartingale models, generalizing from Brownian to semimartingale markets.
Paper presents a robust time-series retrieval method using segmental alignment.
problem Noise and local non-causal perturbations in time-series data.
method Joint segmentation and alignment of sequences using a modified pair-HMM with a new distance metric.
result Improved classification performance and robustness to noise.
New model analyzes customer churn with tensor completion and binary data.
problem Analyzing the impact of interventions on customer churn.
method Tensorized latent factor block hazard model with 1-bit tensor completion.
result Effective categorization of interventions by similar impacts.
Criteria ensure manifold triangulation without differentiable structure.
problem Ensuring a manifold can be triangulated without differentiable structure.
method Local coordinate chart criteria for homeomorphism verification.
result Criteria guarantee triangulation of manifolds without Delaunay property.
We give some general criteria of being a homeomorphism for continuous mappings of topological manifolds, as well as criteria of being a diffeomorphism for smooth mappings of smooth manifolds. As an illustration, we apply these criteria to the problems arising in two- and three-dimensional grid generation.
The study reveals flaws in pruning criteria and proposes a new assumption for better filter selection.
problem Flaws in existing pruning criteria for CNNs.
method Empirical experiments and Convolutional Weight Distribution Assumption.
result The Convolutional Weight Distribution Assumption improves filter selection in pruning.
New method finds optimal hyperparameters for multiple tasks and criteria.
problem Finding optimal hyperparameters for multiple tasks and criteria.
method Multi-Task Multi Criteria (MTMC) method that provides Pareto-optimal solutions.
result The method selects optimal hyperparameters based on given criteria significance coefficients.
Improved recommendations using latent embeddings from user reviews.
problem Lack of consideration for latent embeddings in multi-criteria recommender systems.
method Utilized variational autoencoders to map user reviews into latent embeddings, which are then compressed into discrete vectors for multi-criteria recommendation.
result The proposed method significantly outperforms baselines across various datasets and evaluation measures.
New criteria for Heegaard splittings ensure strong irreducibility and finite Goeritz groups.
problem Determining strong irreducibility and finite Goeritz groups of Heegaard splittings.
method Two diagrammatic criteria for Heegaard splittings, accepting arbitrary disk systems.
result Criteria ensure strong irreducibility and finite Goeritz groups for Heegaard splittings.
Develops scenario theory for multi-criteria decision making.
problem Need for robustness assessment with multiple criteria and datasets.
method Collectively treats risks associated with individual criteria for multi-criteria decision problems.
result More accurate robustness certificates and sharper quantification of simultaneous criterion satisfaction.
We consider the problem of identifying patterns in a data set that exhibit anomalous behavior, often referred to as anomaly detection. In most anomaly detection algorithms, the dissimilarity between data samples is calculated by a single criterion, such as Euclidean distance. However, in many cases there may not exist …
The paper evaluates criteria for selecting cryptocurrencies based on historical data.
problem High risk of cryptocurrencies due to volatility.
method Characterized returns and risks using historical data in short time windows (7 and 15 days). Analyzed the importance of criteria using various methods.
result Importance of criteria for selecting cryptocurrencies is analyzed and evaluated.
Fairness criteria may harm over time, contrary to conventional wisdom.
problem The impact of fairness criteria on long-term population well-being.
method Study of fairness criteria in a one-step feedback model, analyzing long-term outcomes.
result Static fairness criteria do not necessarily promote improvement over time and may cause harm.
New criteria detect anomaly detection algorithms without labeled data.
problem Lack of labeled data for evaluating anomaly detection algorithms.
method Developed two new criteria based on Excess-Mass and Mass-Volume curves, and a feature sub-sampling methodology.
result Empirically validated new criteria outperform classical ROC and PR curves in non-labeled data scenarios.
Study compares different complexity criteria for free boundary minimal surfaces.
problem Comparing different complexity criteria for free boundary minimal surfaces.
method Global theory of free boundary minimal surfaces.
result Provides a complete picture of how area, topology, and Morse index compare.
New approach uses causal reasoning to address fairness issues.
problem Fairness criteria based on observational data are limited and unreliable.
method Shifts focus from observational criteria to causal reasoning.
result Formalizes why and when observational criteria fail.
The paper analyzes performance criteria for competing fund managers in Ito-diffusion markets.
problem Analyzing performance of competing fund managers in Ito-diffusion markets.
method Developed forward relative performance criteria and forward Nash equilibrium for passive and competitive cases.
result Extended performance criteria for investment problems in Ito-diffusion markets.
Paper defines numerical criteria to test handlebody link irreducibility.
problem Determining the irreducibility of handlebody links.
method A set of numerical criteria to test handlebody links for irreducibility.
result Effective method to recognize irreducibility of handlebody knots and most handlebody links.
A new Tsallis entropy criterion unifies decision tree split criteria.
problem Improving decision tree performance using a unified split criterion.
method Proposes a Tsallis Entropy Criterion (TEC) algorithm to unify Shannon entropy, Gain Ratio, and Gini index.
result TEC algorithm achieves statistically significant improvement over classical algorithms.
We shall give useful criteria of lips, beaks and swallowtail singularities of smooth map from the plane into the plane. As an application of criteria, we will discuss the singularities of Cauchy problem of single conservation law.
A new method for multi-criteria recommender systems using graph attention networks.
problem Lack of nuanced relationships between users and items based on specific criteria.
method MDGAT, a multi-edge bipartite graph with dual attention networks and contrastive learning.
result MDGAT achieves higher accuracy in predicting item ratings compared to baseline methods.
New framework for resilient bi-criteria optimization under noisy feedback.
problem Bi-criteria combinatorial optimization with noisy function evaluations.
method Introducing (α,β,δ,extttN)-resilience and developing a black-box framework. result Achieves sublinear regret and constraint violation for bi-criteria bandit problems.
New algorithms minimize risk in MNL bandits, achieving near-optimal performance.
problem Minimizing risk in multi-armed bandit problems.
method Designing algorithms for various risk criteria (e.g., CVaR, Sharpe ratio, entropy risk).
result Near-optimal regret for the designed algorithms.
A game-theoretic approach to multi-criteria ranking from ordinal data.
problem Ranking objects from ordinal data with multiple criteria.
method Generalizing von Neumann winner to multi-criteria setting using Blackwell's approachability.
result The Blackwell winner can be computed as a convex optimization problem and achieves near-optimal sample complexity.
Criteria for Morin singularities in lower dimensions with applications to bifurcation.
problem Understanding Morin singularities in maps into lower dimensions.
method Providing criteria for Morin singularities and studying bifurcations of Lefschetz singularities.
result Criteria for Morin singularities in maps into lower dimensions.
Two stopping criteria proposed for real-time fMRI experiments.
problem Developing accurate stopping criteria for real-time fMRI experiments.
method Empirical study of two proposed stopping criteria.
result Performance of two stopping criteria empirically studied.
Criteria found for graph drawings on surfaces.
problem Graph drawings on surfaces.
method Criteria for integer and modulo 2 embeddability.
result Found criteria for graph drawings on surfaces.
Proposes a multi-criteria AutoML system to optimize additional criteria like fairness and interpretability.
problem Current AutoML systems limit model choices and preprocessing steps, ignoring secondary criteria.
method Optimizes additional criteria directly to guide the search for optimal machine learning pipelines.
result Demonstrates the need and usefulness of a multi-criteria AutoML system.
Study on MMV in jump-diffusion models resolves MV's non-monotonicity issues.
problem Non-monotonicity and free cash flow stream problems in MV preferences.
method Explicit solution for MMV preferences in jump-diffusion models, proving non-negative potential measures.
result MMV resolves MV's non-monotonicity and free cash flow stream issues.
Introduces new performance criteria for investment under distorted probabilities.
problem Reconciling time-consistent performance with probability distortions.
method Two definitions of forward rank-dependent criteria, equivalence established; characterization of viable probability distortion processes.
result Characterization of optimal wealth process and new distorted measure.
The paper introduces risk consistency properties for credit ratings.
problem Promoting prudent investment decisions in credit ratings.
method Introducing and studying risk consistency properties in the framework of Choquet rating criteria.
result Characterization of Choquet risk measures and rating criteria satisfying risk consistency properties.
Many machine learning frameworks, such as resource-allocating networks, kernel-based methods, Gaussian processes, and radial-basis-function networks, require a sparsification scheme in order to address the online learning paradigm. For this purpose, several online sparsification criteria have been proposed to restrict …
Local criteria for non-embeddability of complex manifolds.
problem Smooth non-embeddability of Levi-flat manifolds.
method Analogue of Ueda theory on neighborhood structure of hypersurfaces.
result Local criteria for non-embeddability of Levi-flat manifolds.
Study tackles criterion collapse in learning criteria, showing conditions for loss minimization.
problem Criterion collapse in optimization, focusing on error probability minimizers.
method Analyzes various learning criteria, including DRO, OCE risks, and non-monotonic criteria.
result Non-monotonic criteria can avoid collapse, while monotonic ones cannot.
The paper characterizes when numerical criteria for PDE solvability fail and provides effective criteria for existence.
problem Characterizing when numerical criteria for PDE solvability fail.
method Finite number of subvarieties violating Nakai type criterion, and their rigidity.
result Finite number of subvarieties violating the Nakai type criterion, and these subvarieties are rigid.
Study proves conditions for geometric flow blowup on surfaces.
problem Conditions for geometric flow blowup on surfaces.
method Splitting of geometric flows, new compactness theorem, and blow-up criteria.
result Proves blow-up criteria for harmonic Ricci flow and spinor flow on surfaces.
Managing risk in dynamic decision problems is of cardinal importance in many fields such as finance and process control. The most common approach to defining risk is through various variance related criteria such as the Sharpe Ratio or the standard deviation adjusted reward. It is known that optimizing many of the vari…
Simple criteria for codimension two surface singularities.
problem Identifying singularities in surfaces of codimension two.
method Provided criteria for singularities in surfaces of codimension less than or equal to two.
result Conditions for codimension two singularities in ruled surfaces and center maps.
SPX optimizes multiple graph drawing metrics for better readability.
problem Graph drawing algorithms often optimize one metric at a time, leading to suboptimal layouts.
method Introduces Stress-Plus-X (SPX) framework that optimizes stress, crossings, angles, and upwardness simultaneously.
result SPX achieves results close to state-of-the-art algorithms that optimize metrics individually.
This paper evaluates criteria for a versatile classifier.
problem Choosing an optimal classifier for all problems.
method Data analysis and scoring of six popular classifiers.
result Random forests are the best generalist classifiers.
Developed criteria for selecting non-normalized models using NCE and score matching.
problem No information criteria for non-normalized models estimated by NCE or score matching.
method Developed information criteria based on discrepancy measures for non-normalized models estimated by NCE or score matching.
result The proposed criteria enable selection of the appropriate non-normalized model in a data-driven manner.
New criteria judge combinatorial equivalence of polytopes to products of simplices.
problem Determining combinatorial equivalence of polytopes to products of simplices.
method Combination of combinatorial, geometric, and topological conditions inspired by toric topology.
result New criteria for judging combinatorial equivalence of polytopes to products of simplices.
Study finite-type solutions of elliptic sinh-Gordon equation with Durham boundary conditions.
problem Finite-type solutions of elliptic sinh-Gordon equation with Durham boundary conditions.
method Determine rationality criteria for Durham conditions and analyze spectral curve properties.
result Rationality criteria are sufficient for finite-type solutions with complementary boundary conditions.
We give criteria for Morin singularities into higher dimensions. As an application, we study the number of A-isotopy classes of Morin singularities.