Extends decision theory to handle unlikely events and varying risk attitudes.
problem Handling preferences for unlikely events and varying risk attitudes.
method Derives a subjective lexicographic expected utility representation.
result Provides foundations for models in finance and infinite dynamic games.
The paper proposes a method to infer multi-objective rewards from preferences.
problem Modeling preferences based on multiple, often competing objectives.
method Modeling priorities lexicographically and inferring multi-objective rewards from observed preferences.
result Lexicographically-ordered rewards provide a better understanding of preferences and improve policies.
The paper tackles lexicographic multiarmed bandit problems with bounded regret.
problem Selecting lexicographic optimal arms in multiobjective bandit problems.
method Defining lexicographic regret, considering prior information, and proposing algorithms for both settings.
result Achieves uniformly bounded regret in time for both prior settings and sublinear gap-free regret in the prior-free case.
Researchers found a regular language for maximal lexicographic representatives in braid monoids.
problem Understanding the language of maximal lexicographic representatives in braid monoids.
method Detailed description of the smallest Finite State Automaton and analysis of the proportion of elements.
result The proportion of elements of length k whose maximal lexicographic representative finishes with the first generator tends to a number P_{n,1} ≥ 1/8 as k tends to infinity.
We study the degree of polynomial representations of knots. We obtain the lexicographic degree for two-bridge torus knots and generalized twist knots. The proof uses the braid theoretical method developed by Orevkov to study real plane curves, combined with previous results from [KP10] and [BKP14]. We also give a sharp…
We study the degree of polynomial representations of knots. We give the lexicographic degree of all two-bridge knots with 11 or fewer crossings. First, we estimate the total degree of a lexicographic parametrisation of such a knot. This allows us to transform this problem into a study of real algebraic trigonal plane c…
A new algorithm Zeus for multi-objective clustering with lexicographic ordering and slack.
problem Improving clustering quality with lexicographic objectives and slack.
method Introduced a slack mechanism and proposed Zeus algorithm to solve multi-objective clustering problems.
result Empirical validation of Zeus on real-world data demonstrates its effectiveness.
New theory for nonsmooth systems helps optimize and control complex functions.
problem Optimizing and controlling systems with nonsmooth functions.
method Higher-order averaging theory with nonsmooth near-identity transformation and lexicographic differentiation.
result Closed formula for nonsmooth first and second-order averaging.
New fairness concept extends minimax fairness to lexicographic fairness.
problem Fairness in supervised learning, especially lexicographic fairness.
method Introduced approximate lexifairness, derived algorithms for finding solutions, and proved generalization bounds.
result Proved that approximate lexifairness on training data implies approximate lexifairness on true distribution.
The heights of Alexandroff square transformation groups are computed and proven.
problem Computing possible heights of Alexandroff square transformation groups.
method Analyzing the heights of transformation groups for Alexandroff square, unit square with lexicographic order, and unit square with Euclidean topology.
result Proven heights for transformation groups of Alexandroff square, unit square with lexicographic order, and unit square with Euclidean topology.
New connection found between shape reconstruction methods and persistent homology.
problem Connecting shape reconstruction methods with persistent homology.
method Wrap complexes and lexicographic optimal homologous cycles.
result Lexicographically optimal homologous cycles are supported on Wrap complexes.
The kth finite subset space of a topological space X is the space exp_k X of non-empty finite subsets of X of size at most k, topologised as a quotient of X^k. The construction is a homotopy functor and may be regarded as a union of configuration spaces of distinct unordered points in X. We show that the finite subset …
Study how regularization and optimization affect margin in deep models.
problem Understanding margin maximization in deep learning models.
method Analyze the limit of loss minimization with diverging norm constraints and margin paths.
result Discovers lexicographic max-margin solutions for homogeneous models and shows convergence under certain conditions.
Let N and P be smooth manifolds of dimensions n and p (n>=p>=2). Let Omega^{I}(N,P) denote an open subspace of J(N,P) which consists of all Boardman submanifolds Sigma^{J}(N,P) with J=< I in the lexicographic order. We will prove the homotopy principle in the existence level for Omega^{I}(N,P).
Groups with specific curvature have a regular language of geodesics.
problem Understanding the language of geodesics in non-positively curved triangle groups.
method Proving finitely many cone types and regularity of geodesic languages.
result The language of lexicographically first geodesics is regular and satisfies the fellow traveller property.
DFL framework improves action and outcome fairness in policy learning.
problem Fairness in policy learning, especially action and outcome fairness.
method Integrates action and outcome fairness into a multi-objective optimization problem using a lexicographic weighted Tchebyshev method.
result DFL framework improves both action and outcome fairness with minimal value reduction.
Proof shows imitation of expert's reward and solutions in multi-objective optimization.
problem Multi-objective optimization with reward and solution imitation.
method Wasserstein inverse reinforcement learning.
result Wasserstein inverse reinforcement learning enables imitation of expert's reward and solutions in multi-objective optimization.
We introduce a method for creating a special type of tree, called a tree position, from a weighted graph. Leaves of the tree correspond to vertices of the original graph, and the tree edges contain information which can be used to partition these vertices. By repeatedly applying reducing operations to the tree position…
Let N and P be smooth closed manifolds of dimensions n and p respectively. Given a Thom-Boardman symbol I, a smooth map f:N→P is called an ΩI-regular map if and only if the Thom-Boardman symbol of each singular point of f is not greater than I in the lexicographic order. We will represent the gr…
New method allows backtesting of systemic risk forecasts.
problem Systemic risk measures are not elitable and identifiable, making backtesting impossible.
method Introduces multi-objective elicitability and Diebold--Mariano type tests.
result Proposes a traffic-light approach for backtesting.
The study explores properties and mutations in oriented matroids, proving new results on Euclidean and non-Euclidean structures.
problem Investigating the Euclidean and non-Euclidean properties of oriented matroids.
method Analyzing the minimum number of mutations, using lexicographic extensions, and mutation-flips to prove properties.
result For rank 4 uniform oriented matroids, the minimum number of mutations adjacent to an element is at most 3.
Study a specific line arrangement and compute its fundamental group via braid monodromy.
problem Compute the fundamental group of a specific line arrangement's complement.
method Use braid monodromy to compute the fundamental group.
result The resulting presentation of the fundamental group coincides with the modified Artin presentation.
Deep learning agent improves pedestrian navigation in urban environments.
problem Autonomous driving among pedestrians in urban areas.
method Multi-objective deep reinforcement learning using a deep Q-learning variant.
result The multi-objective DQN agent outperforms single-objective DQN in various environments.
The paper studies geometric properties of geodesic spaces using Rips and Čech filtrations.
problem Understanding geometric properties of geodesic spaces.
method Applying fundamental group and homology groups to Rips or Čech filtrations.
result Rips critical points correspond to circles of specific lengths and persistence encodes space properties.
Simple rectilinear polygons (i.e. rectilinear polygons without holes or cutpoints) can be regarded as finite rectangular cell complexes coordinatized by two finite dendrons. The intrinsic l1-metric is thus inherited from the product of the two finite dendrons via an isometric embedding. The rectangular cell complexe…
The paper finds formulas for word lengths and conjugacy classes in surface groups.
problem Finding formulas for word lengths and conjugacy classes in surface groups.
method Investigating symmetric presentations and normal forms of conjugacy classes.
result Derives three formulae for word lengths and provides efficient algorithms for conjugacy problems.
The paper predicts coincidences in homological densities of spaces of 0-cycles on manifolds.
problem Predicting coincidences in homological densities of spaces of 0-cycles on manifolds.
method Using Weil's analogy and Björner--Wachs theory of lexicographic shellability.
result The topological predictions are true and provide new homological stability theorems.
New method calculates growth rates of Artin-Tits monoids, linking to partial theta function.
problem Growth rates of Artin-Tits monoids and their connection to partial theta function.
method Determining growth functions using simple matrix determinants and atomic generators.
result Exponential growth rates of Artin-Tits monoids of type An tend to 3.233636... as n increases. This work tackles asymmetric community estimation in multi-layer directed networks.
problem Estimating different numbers of sender and receiver communities in multi-layer directed networks.
method Proposes a goodness-of-fit test based on the largest singular value of an aggregated normalized residual matrix.
result Develops sequential and ratio-based testing procedures to consistently determine true sender and receiver community numbers.
New RL algorithm ensures stable, replicable policies.
problem Stability and replicability issues in RL algorithms.
method Introduced weak and strong forms of list replicability, developed a novel planning strategy, and tested state reachability.
result Proved efficient tabular RL algorithm with polynomial list complexity.
New method for fair resource allocation in AI-aware networks with unknown utility functions.
problem Fair resource allocation in AI-aware communication networks with unknown utility functions.
method Distributed, data-driven bilevel optimization approach to learn surrogate utility functions.
result The proposed algorithm learns from data to autotune surrogate utility functions for unknown utility functions.
Optimizes portfolios with utility theory, diversification, and leverage.
problem Finding optimal portfolio allocation strategies.
method Utility theory, exponential and logarithmic utilities, compound probability distributions, maximum expected utility, generalized mean-variance.
result Enhanced portfolio allocation strategies with natural explanations.
New algorithm tackles unknown utility network resource allocation.
problem Maximizing network utility with unknown agent utilities.
method Modeling as a bandit problem, proposing algorithms for resource allocation.
result Proposed algorithms are optimal when all agents have the same utility.
Study robust utility maximization with uncertain continuous semimartingales.
problem Maximizing utility in continuous time under model uncertainty.
method Duality and conjugate problems for logarithmic, exponential, and power utilities.
result Existence of optimal portfolios for various utilities.
Theory integrates loss aversion into expected utility for monetary returns.
problem Modeling loss aversion in expected utility theory.
method Develops state-dependent linear utility functions incorporating loss aversion.
result Contracts from monopolists in insurance markets.
The maximum entropy principle can be used to assign utility values when only partial information is available about the decision maker's preferences. In order to obtain such utility values it is necessary to establish an analogy between probability and utility through the notion of a utility density function. According…
This paper studies stability of the exponential utility maximization when there are small variations on agent's utility function. Two settings are considered. First, in a general semimartingale model where random endowments are present, a sequence of utilities defined on R converges to the exponential utility. Under a …
Study adds investment gains and losses to recursive utility model, proving existence and uniqueness of utility process.
problem Existence and uniqueness of utility process in a recursive utility model with investment gains and losses.
method Generalized recursive utility model with constant elasticity of intertemporal substitution and relative risk aversion degree. Proved existence and uniqueness in a specific, finite-state Markovian setting.
result Utility process exists and is unique when agent derives nonnegative gain-loss utility, and non-existent or non-unique otherwise.
Novel framework for portfolio selection considering utility and risk.
problem Maximizing utility subject to risk constraints with various utility and risk functionals.
method General framework accommodating non-concave utilities and non-convex risk measures. Characterization of well-posedness using a simple either-or criterion.
result Minimal condition for well-posedness: either utility or risk must be sensitive to large losses.
Closed-form optimal portfolios for exponential utility in small/large markets.
problem Optimal portfolios maximizing exponential utility in small/large financial markets.
method Closed-form expressions for optimal portfolios in small markets, convergence to large market optimal utility, numerical procedure for general utility functions.
result Optimal utility in large markets converges to optimal utility in small markets, requiring infinite diversification.
Optimizing S-shaped utility shows VaR and ES are ineffective for risk management.
problem Ineffective risk measures like VaR and ES for S-shaped utility maximization.
method Optimization of investor utility under risk management constraints.
result Conventional risk management constraints can reduce S-shaped utility.
The purpose of this paper relies on the study of long term yield curves modeling. Inspired by the economic litterature, it provides a financial interpretation of the Ramsey rule that links discount rate and marginal utility of aggregate optimal consumption. For such a long maturity modelization, the possibility of adju…
The paper examines utility maximization in markets with hidden Gaussian drift, finding restrictions on model parameters.
problem Utility maximization problems in markets with hidden Gaussian drift mean-reverting processes.
method Derives sufficient conditions for bounded maximum expected utility of terminal wealth for models with full and partial information.
result Restrictions on model parameters for bounded maximum expected utility.
Study on hedging with delayed strategies for exponential utility maximization.
problem Maximizing exponential utility in semistatic hedging.
method Explicit computations for delayed semistatic hedging.
result Developed methods for hedging with delayed strategies.
Bayesian optimization method for privacy-utility trade-off.
problem Quantifying privacy-utility trade-off for complex machine learning tasks.
method Bayesian optimization methodology for empirical utility measurement.
result Efficiently characterizes privacy-utility trade-off for differentially private algorithms.
This paper solves a coinsurance problem using fuzzy numbers and expected utility operators.
problem Formulating a coinsurance problem in the possibilistic setting of expected utility operators.
method Developed a framework using expected utility operators to model risk aversion and solve the coinsurance problem.
result Various formulas for the optimal T-coinsurance rate are derived for specific utility functions and fuzzy numbers. A new framework for mining high utility patterns in interval-based sequences.
problem Mining patterns in events that persist over varying time intervals and considering event utility.
method Integrates utility into interval-based sequences and proposes HUIPMiner algorithm with pruning strategy.
result HUIPMiner efficiently finds high utility patterns in real datasets.
Study on robust utility maximization with nonconcave utility functions under projective determinacy.
problem Investor's optimal investment strategy under model ambiguity and nonconcave utility.
method Projective functions of the path and sets of priors, upper-semicontinuous utility.
result Existence of optimal investment strategy under PD.