TSMB handles time delays in multivariate time series data.
problem Varying time delays in multivariate time series data complicate predictions.
method Time Series Model Bootstrap (TSMB) framework for nonparametric time delay estimation.
result TSMB improves model performance in dynamic data environments.
BayTiDe discovers time-delayed differential equations from noisy data.
problem Discovering time-delayed differential equations from data with large delays and noise.
method Bayesian inference with a sparsity-promoting prior.
result BayTiDe accurately identifies time-delayed differential equations with accuracy proportional to data resolution.
Study on synchronization in financial markets with time delays.
problem Understanding market dynamics and synchronization in financial systems with time delays.
method Examined a system of coupled non-linear delay-differential equations, linearized for small delays, and analyzed collective dynamics using bifurcation diagrams and numerical solutions.
result Demonstrated that limit cycles can be maintained in coupled N-asset models with appropriate parameterization, leading to market synchronization.
Proposes a nonparametric model for predicting conversion rates with delayed feedback.
problem Predicting conversion rates with time delays and unknown distribution.
method Nonparametric delayed feedback model without assuming a specific distribution.
result The proposed model outperforms existing methods in conversion rate prediction.
Neural Laplace Control tackles offline RL for continuous-time delayed systems with irregular observations.
problem Offline reinforcement learning problems involving continuous-time environments with delays and irregular observations.
method Combines a Neural Laplace dynamics model with a model predictive control (MPC) planner.
result Achieves near expert policy performance on continuous-time delayed environments.
New method estimates traffic congestion delays using statistical causality.
problem Accurate estimation of traffic congestion delays during accidents.
method Proposes a novel time delay estimation method using lag-specific transfer entropy (TE) and Markov bootstrap techniques.
result Validated the method's efficacy using simulated and real data.
In this paper we studied about the wavelet identification of the thresholds and time delay for more general case without the constraint that the time delay is smaller than the order of the model. Here we composed an empirical wavelet from the SETAR (Self-Exciting Threshold Autoregressive) model and identified the thres…
Develops a stochastic approach to financial market delays.
problem Modeling delays in financial markets with multiple assets.
method Introduces a general stochastic framework for information and order execution delays.
result Delayed markets maintain fundamental asset pricing theorems and no asymptotic free lunch condition.
Model analyzes how delayed information impacts option pricing.
problem Effects of delayed information on option pricing.
method Binomial model, closed form formula for convex contingent claims, convergence analysis.
result Delayed information exaggerates the volatility smile.
New algorithm handles delayed feedback robustly, reducing regret without knowing delay bounds.
problem Bandits with variably delayed feedback, especially excessive delays.
method Implicit exploration scheme, adaptive skipping, drifted regret control.
result Can tolerate arbitrary excessive delays up to order T, reducing regret.
Delay-SDE-net models time series with memory and uncertainty, outperforming other models.
problem Accurately modeling time series with memory and uncertainty.
method Stochastic delay differential equations (SDDEs) neural network model with aleatoric and epistemic uncertainty.
result The Delay-SDE-net consistently outperforms other models in predicting time series values and uncertainties.
Improved GRU model with weighted time-delay feedback for long-term dependencies.
problem Modeling long-term dependencies in sequential data.
method Introducing a gated recurrent unit (GRU) with a weighted time-delay feedback mechanism.
result τ-GRU outperforms state-of-the-art models on various tasks.
Capacity-Constrained Online Convex Optimization with Delayed Feedback
problem Online learning with delayed feedback under a hard capacity constraint
method Reduction to a delayed and weighted OCO problem using a scheduler
result First regret guarantees for capacity-constrained OCO under convex and strongly convex losses
Study a dual risk model with innovation delays, focusing on ruin probability and time.
problem Analyzing risk models with innovation delays affecting ruin probability and time.
method Delayed dual risk model with innovation delays, focusing on ruin probability and time.
result Closed-form formulas for ruin probability and time in some special cases.
Derives a Feynman-Kac formula for a fixed delay CIR model.
problem Modeling financial processes with fixed delay.
method Proves existence and uniqueness of a strong solution for a specific SDDE.
result Derives a Feynman-Kac type formula leading to an affine bond pricing formula.
Survey of RL methods for control systems with time delays.
problem Time delays in cyber-physical systems degrade RL performance and stability.
method Categorizes and analyzes five major families of RL methods for time delays.
result Identifies key trade-offs and practical guidelines for selecting RL methods.
End-to-end network predicts and aligns continuous emotion labels.
problem Inconsistent alignment of continuous emotion labels with speech signals.
method Convolutional neural network with a multi-delay sinc layer.
result State-of-the-art results in predicting and aligning continuous emotion labels.
The study analyzes how bonus-malus systems and delayed claims settlement affect insurance companies' financial stability.
problem Analyzing the impact of bonus-malus systems and delayed claims settlement on insurance companies' financial stability.
method Examined a discrete-time risk model with time-varying premiums, evaluating two types of claims and settlement delays.
result Delayed settlement of by-claims leads to lower ruin probabilities under specific assumptions.
We construct and analyze symmetrized delay correlation matrices for empirical data sets for atmopheric and financial data to derive information about correlation between different entities of the time series over time. The information about correlations is obtained by comparing the results for the eigenvalue distributi…
Novel algorithm for decentralized optimization in time-varying networks with delays.
problem Decentralized optimization in networks with communication delays.
method DT-GO algorithm, applicable to general directed graphs, converges to same complexity as centralized SGD.
result Algorithm DT-GO achieves convergence rates for convex and non-convex objectives, similar to centralized SGD.
Study utility indifference pricing with delayed investment information in a Bachelier model.
problem Investment decisions based on delayed information in a Bachelier model.
method Developed discrete-time duality and used techniques from [7] to compute scaling limits.
result Utility indifference prices scaling limit for vanishing delay with quadratic penalty.
New algorithm for multiarmed bandits with variable, unbounded delays achieves similar regret bounds.
problem Variable, unbounded delays in multiarmed bandits.
method Introduces a new algorithm that skips rounds with excessively large delays and uses a doubling scheme.
result Achieves the same regret bound as Exp3 with variable, unbounded delays.
Study improves risk evaluation timing with right-censored reporting delays.
problem Improving risk evaluation under short observation windows due to administrative censoring.
method Jointly models parametric hazards for event and reporting processes, uses Monte Carlo expectation-maximization algorithm, and proposes transfer-learning procedure.
result Improves accuracy of timely risk evaluation under administrative censoring.
In this paper we investigate novel applications of a new class of equations which we call time-delayed backward stochastic differential equations. Time-delayed BSDEs may arise in finance when we want to find an investment strategy and an investment portfolio which should replicate a liability or meet a target depending…
DASA speeds up SA with delayed agents, achieving N-fold speedup.
problem Speeding up Stochastic Approximation with asynchronous delays.
method DASA: Delay-Adaptive Multi-Agent Stochastic Approximation algorithm.
result First algorithm with convergence rate dependent on mixing time and average delay.
Time-delayed embeddings avoid self-intersections for high enough delay.
problem Analyzing self-intersections in time-delayed embeddings.
method Study of time-delayed coordinate maps for diffeomorphisms on compact manifolds.
result For high enough delay, time-delayed embeddings avoid self-intersections almost everywhere.
This paper provides a mathematical framework for time-delay reservoir computing.
problem Lack of rigorous mathematical foundations for reservoir computing properties.
method Control-theoretic framework, formal definitions of separation and fading memory, explicit lower bound derivation.
result Established formal definitions and connections to stability notions for time-delay systems.
Study utility maximization with delayed information in continuous time Gaussian markets.
problem Maximizing utility with delayed information in continuous time Gaussian markets.
method Purely probabilistic approach based on Radon-Nikodym derivatives of Gaussian measures.
result Solution for optimal control and value in a specific Gaussian framework.
Banker-OMD improves online learning with delayed feedback.
problem Handling delayed feedback in online learning.
method Generalized Online Mirror Descent (OMD) framework.
result Achieves nearly-optimal performance in three bandit scenarios.
The paper develops methods for time-varying constrained online convex optimization.
problem Time-varying loss and constraint functions in online convex optimization.
method Model-based augmented Lagrangian methods (MALM) for time-varying and delayed feedback.
result Sublinear regret and constraint violation for both time-varying and delayed feedback scenarios.
Study market delay effects on contingent claims pricing.
problem Delayed market information impacts contingent claims pricing.
method Analyzes Black-Scholes and binomial models with delay.
result Scaling limit of super-replication prices equals G-expectation.
In this paper we show that several dynamical systems with time delay can be described as vector fields associated to smooth functions via a bracket of Leibniz structure. Some examples illustrate the theoretical considerations.
Optimizes insurance processing capacity to minimize costs.
problem Processing delays and backlogs in insurance claims.
method Optimal capacity selection to minimize delay-adjusted and fixed costs.
result Minimizes claims costs by balancing processing capacity and delays.
Gradient descent with delayed updates converges faster with noise, even when delays are significant.
problem Analyzing convergence of gradient descent with delayed gradients and stochastic noise.
method Novel technique using generating functions for convergence analysis.
result Convergence bounds show that stochastic noise mitigates the negative effects of delays, improving performance.
Adapts Exp3 to adversarial bandits with delays and data.
problem Adversarial multi-armed bandits with delayed feedback.
method Tuned Exp3 variants with step-size adaptation and implicit exploration.
result Optimal regret bounds of log ( K ) ( T K + D ) \sqrt{\log(K)(TK + D)} log ( K ) ( T K + D ) with high probability. This study predicts flight delays for American Airlines using data mining and machine learning.
problem Flight delays and cancellations by American Airlines.
method Data mining and machine learning approaches, specifically Gradient Boosting Classifier Model.
result Achieved a maximum accuracy of 85.73% in predicting flight delays.
Proposes neural delay differential equations for stable system identification with partially observed states.
problem Learning stable models for systems with partial or delayed observations.
method Augments states with history, uses neural delay differential equations, and ensures stability through time delay analysis.
result The approach ensures stability of learned models for partially observed systems.
New algorithms explain Naive Bayes classifiers in polynomial time and delay.
problem Computing explanations for Naive Bayes classifiers efficiently.
method Developed log-linear time and polynomial delay algorithms for PI-explanations.
result Efficiently computed PI-explanations for linear classifiers.
New algorithms reduce forecasting errors by leveraging optimistic learning and hinting.
problem Real-time climate forecasting with delayed feedback.
method Developed optimistic online learning algorithms that reduce regret under delayed feedback.
result Optimistic learning algorithms achieve optimal regret guarantees under delayed feedback.
Algorithm improves RL by discovering delayed causal relations.
problem Improving data-efficiency and interpretability in RL.
method Predicts observations with Markov assumption, introduces hidden variables to explain past events.
result Significantly improves RL performance on simulated and real tasks.
New model for disability insurance reserving handles delays in claim information.
problem Disability insurance claims are affected by long delays and adjudication processes.
method Proposes a new individual reserving model for real-time claim evolution.
result Shows that new reserves can be calculated as modifications of classic reserves.
Develops variable-lag Granger causality for more accurate time series analysis.
problem Fixed time delay assumption in Granger causality does not fit many real-world applications.
method Variable-lag Granger causality, inferring with arbitrary time delays.
result Performs better than existing methods in coordinated collective behavior studies.
Solves utility maximization for delayed informed investors.
problem Maximizing utility in a discrete time framework with delayed information.
method Utilizes theory from [4] and optimal portfolio guessing.
result Solution for exponential utility maximization in a multivariate normal setting with delay.
This study aims to predict vessel stay and delay times at ports to optimize logistics.
problem Uncertainties in maritime logistics, including weather, cargo diversity, and port dynamics, lead to increased costs and inefficiencies.
method Developed predictive analytics to address shortcomings in previous works, using feature analysis and SHAP explanations.
result Predictive analytics can assist in efficient planning and scheduling of port operations, reducing costs and improving logistics.
Modeling delayed Granger causality in Hawkes processes.
problem Capturing the time lag between causal events in multivariate Hawkes processes.
method Proposed a Hawkes process model with latent time lags, using Variational Auto-Encoder (VAE) for inference.
result Identified and inferred time lags with posterior distributions, improving event prediction and root cause analysis.
The paper models delayed event occurrences in insurance data.
problem Systematic underestimation of event occurrence due to observation delays.
method Modeling the time between event occurrence and observation, considering event day and calendar effects.
result A granular model for event observation delay heterogeneity.
PCTS optimizes noisy, delayed, multi-fidelity feedbacks in black-box optimization.
problem Optimizing unknown functions with noisy, delayed, and multi-fidelity feedbacks.
method ProCrastinated Tree Search (PCTS) with DUCB1 and DUCBV algorithms.
result PCTS achieves better regret bounds for delayed, noisy, and multi-fidelity feedbacks.
Develops variable-lag Granger causality and Transfer Entropy for time series analysis.
problem Fixed time delay assumption in Granger causality and Transfer Entropy does not hold in many applications.
method Variable-lag Granger causality and Transfer Entropy, using optimal warping path of Dynamic Time Warping (DTW).
result Proposed methods perform better than existing methods in both simulated and real-world datasets.